Academic literature on the topic 'Svir method'
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Journal articles on the topic "Svir method"
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Parhusip, Hanna Arini, Suryasatriya Trihandaru, Bernadus Aryo Adhi Wicaksono, Denny Indrajaya, Yohanes Sardjono, and Om Prakash Vyas. "Susceptible Vaccine Infected Removed (SVIR) Model for COVID-19 Cases in Indonesia." Science and Technology Indonesia 7, no. 3 (2022): 400–408. http://dx.doi.org/10.26554/sti.2022.7.3.400-408.
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Analysis of data on COVID-19 cases in Indonesia is shown by using the Susceptible Vaccine Infected Removed (SVIR) in this article. In the previous research, cases in the period March-May 2021 were studied, and the reproduction number was computed based on the Susceptible Infected Removed (SIR) model. The prediction did not agree with the real data. Therefore the objective of this article is to improve the model by adding the vaccine variable leading to the new model called the SVIR model as the novelty of this article. The used data are collected from COVID-19 cases of the Indonesian population published by the Indonesian government from March 2020-April 2022. However, the vaccinated persons with COVID-19 cases have been recorded since January 2022. Therefore the models rely on the period January 2021-March 2022, where the parameters in the SIR and SVIR models are determined in this period. The method used is discretizing the models into linear systems, and these systems are solved by Ordinary Least Square (OLS) for time-dependent parameters. It is assumed that the birth rate and death rate in the considered period are constant. Additionally, individuals who have recovered from COVID-19 will not be infected again, and vaccination is not necessarily twice. Furthermore, individuals who have been vaccinated will not be infected with the COVID-19 virus. The SVIR model has captured 3 waves of COVID-19 cases that are appropriate to the real situation in Indonesia from January 2021-March 2022. Additionally, the reproduction numbers as functions of time have been generated. The fluctuations of reproduction numbers agree with the real data. For further research, different regions such as districts in Java and other islands will also be analyzed as the implication of this research.
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Yang, Junyuan, Zhen Jin, Lin Wang, and Fei Xu. "A note on an age-of-infection SVIR model with nonlinear incidence." International Journal of Biomathematics 10, no. 05 (2017): 1750064. http://dx.doi.org/10.1142/s1793524517500644.
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In this paper, nonlinear incidence rate is incorporated into an age-of-infection SVIR epidemiological model. By the method of Lyapunov functionals, it is shown that the basic reproduction number [Formula: see text] of the model is a threshold parameter in the sense that if [Formula: see text], the disease dies out, while if [Formula: see text], the disease persists.
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Xu, Jinhu, and Yan Geng. "Dynamics of a Diffusive Multigroup SVIR Model with Nonlinear Incidence." Complexity 2020 (December 7, 2020): 1–15. http://dx.doi.org/10.1155/2020/8847023.
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In this paper, a multigroup SVIR epidemic model with reaction-diffusion and nonlinear incidence is investigated. We first establish the well-posedness of the model. Then, the basic reproduction number ℜ 0 is established and shown as a threshold: the disease-free steady state is globally asymptotically stable if ℜ 0 < 1 , while the disease will be persistent when ℜ 0 > 1 . Moreover, applying the classical method of Lyapunov and a recently developed graph-theoretic approach, we established the global stability of the endemic equilibria for a special case.
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Peralta, Raúl, Cruz Vargas-De-León, and Pedro Miramontes. "Global Stability Results in a SVIR Epidemic Model with Immunity Loss Rate Depending on the Vaccine-Age." Abstract and Applied Analysis 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/341854.
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We formulate a susceptible-vaccinated-infected-recovered (SVIR) model by incorporating the vaccination of newborns, vaccine-age, and mortality induced by the disease into the SIR epidemic model. It is assumed that the period of immunity induced by vaccines varies depending on the vaccine-age. Using the direct Lyapunov method with Volterra-type Lyapunov function, we show the global asymptotic stability of the infection-free and endemic steady states.
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Zhao, Yanan, and Daqing Jiang. "The asymptotic behavior and ergodicity of stochastically perturbed SVIR epidemic model." International Journal of Biomathematics 09, no. 03 (2016): 1650042. http://dx.doi.org/10.1142/s179352451650042x.
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In this paper, we introduce stochasticity into an SIR epidemic model with vaccination. The stochasticity in the model is a standard technique in stochastic population modeling. When the perturbations are small, by the method of stochastic Lyapunov functions, we carry out a detailed analysis on the dynamical behavior of the stochastic model regarding of the basic reproduction number [Formula: see text]. If [Formula: see text], the solution of the model is oscillating around a steady state, which is the disease-free equilibrium of the corresponding deterministic model. If [Formula: see text], there is a stationary distribution and the solution has the ergodic property, which means that the disease will prevail.
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Attaullah, Attaullah, Adil Khurshaid, Zeeshan Zeeshan, Sultan Alyobi, Mansour F. Yassen, and Din Prathumwan. "Computational Framework of the SVIR Epidemic Model with a Non-Linear Saturation Incidence Rate." Axioms 11, no. 11 (2022): 651. http://dx.doi.org/10.3390/axioms11110651.
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In this study, we developed an autonomous non-linear epidemic model for the transmission dynamics of susceptible, vaccinated, infected, and recovered individuals (SVIR model) with non-linear saturation incidence and vaccination rates. The non-linear saturation incidence rate significantly reduces the death ratio of infected individuals by increasing human immunity. We discuss a detailed explanation of the model equilibrium, its basic reproduction number R0, local stability, and global stability. The disease-free equilibrium is observed to be stable if R0<1, while the endemic equilibrium exists and the disease exists permanently in the population if R0>1. To approximate the solution of the model, the well-known Runge–Kutta (RK4) methodology is utilized. The implications of numerous parameters on the population dynamics of susceptible, vaccinated, infected, and recovered individuals are addressed. We discovered that increasing the value of the disease-included death rate ψ has a negative impact on those affected, while it has a positive impact on other populations. Furthermore, the value of interaction between vaccinated and infected λ2 has a decreasing impact on vulnerable and vaccinated people, while increasing in other populations. On the other hand, the model is solved using Euler and Euler-modified techniques, and the results are compared numerically and graphically. The quantitative computations demonstrate that the RK4 method provides very precise solutions compared to the other approaches. The results show that the suggested SVIR model that approximates the solution method is accurate and useful.
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Wang, Chuncheng, Dejun Fan, Ling Xia, and Xiaoyu Yi. "Global stability for a multi-group SVIR model with age of vaccination." International Journal of Biomathematics 11, no. 05 (2018): 1850068. http://dx.doi.org/10.1142/s1793524518500687.
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In this paper, a multi-group SVIR epidemic model with age of vaccination is considered. The model allows the vaccinated individuals to become susceptible after the vaccine loses its protective properties, and the vaccination classes satisfy first-order the partial differential equations structured by vaccination age. Combining the Lyapunov functional method with a graph-theoretic approach, we show that the global stability of endemic equilibrium for the strongly connected system is determined by the basic reproduction number. In addition, the dynamics for non-strongly connected model are also investigated, depending on the basic reproduction numbers corresponding to each strongly connected component. Numerical simulations are carried out to support the theoretical conclusions.
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Ogunmiloro, Oluwatayo Michael, Fatima Ohunene Abedo, and Hammed Kareem. "NUMERICAL AND STABILITY ANALYSIS OF THE TRANSMISSION DYNAMICS OF SVIR EPIDEMIC MODEL WITH STANDARD INCIDENCE RATE." MALAYSIAN JOURNAL OF COMPUTING 4, no. 2 (2019): 349. http://dx.doi.org/10.24191/mjoc.v4i2.5828.
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In this article, a Susceptible – Vaccinated – Infected – Recovered (SVIR) model is formulated and analysed using comprehensive mathematical techniques. The vaccination class is primarily considered as means of controlling the disease spread. The basic reproduction number (Ro) of the model is obtained, where it was shown that if Ro<1, at the model equilibrium solutions when infection is present and absent, the infection- free equilibrium is both locally and globally asymptotically stable. Also, if Ro>1, the endemic equilibrium solution is locally asymptotically stable. Furthermore, the analytical solution of the model was carried out using the Differential Transform Method (DTM) and Runge - Kutta fourth-order method. Numerical simulations were carried out to validate the theoretical results.
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Ismail, Halet, Amar Debbouche, Soundararajan Hariharan, Lingeshwaran Shangerganesh, and Stanislava V. Kashtanova. "Stability and Optimality Criteria for an SVIR Epidemic Model with Numerical Simulation." Mathematics 12, no. 20 (2024): 3231. http://dx.doi.org/10.3390/math12203231.
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The mathematical modeling of infectious diseases plays a vital role in understanding and predicting disease transmission, as underscored by recent global outbreaks; to delve deep into the dynamic of infectious disease considering latent period presciently is inevitable as it bridges the gap between realistic nature and mathematical modeling. This study extended the classical Susceptible–Infected–Recovered (SIR) model by incorporating vaccination strategies during incubation. We introduced multiple time delays to an account incubation period to capture realistic disease dynamics better. The model is formulated as a system of delay differential equations that describe the transmission dynamics of diseases such as polio or COVID-19, or diseases for which vaccination exists. Critical aspects of the study include proving the positivity of the model’s solutions, calculating the basic reproduction number (R0) using next-generation matrix theory, and identifying disease-free and endemic equilibrium points. The local stability of these equilibria is then analyzed using the Routh–Hurwitz criterion. Due to the complexity introduced by the delay components, we examine the stability by studying the roots of a fourth-degree exponential polynomial. The effects of educational campaigns and vaccination efficacy are also investigated as control measures. Furthermore, an optimization problem is formulated, based on Pontryagin’s maximum principle, to minimize the number of infections and associated intervention costs. Numerical simulations of the delay differential equations are conducted, and a modified Runge–Kutta method with delays is used to solve the optimal control problem. Finally, we present a few simulation results to illustrate the analytical findings.
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Liqing, Qiu, and Liu Shuqi. "SVIR rumor spreading model considering individual vigilance awareness and emotion in social networks." International Journal of Modern Physics C 32, no. 09 (2021): 2150120. http://dx.doi.org/10.1142/s0129183121501205.
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Rumor, as a form of information, can be widely spread in a short time. A host of researchers focus on the spread of rumor, aiming to explore the rules of rumor spreading and put forward effective measures to help control the spread of rumor. In real life, when the individual is not interested in the rumor spread or feels that the rumor is not related to him, it is easy to trigger the individual’s vigilance awareness. On the contrary, if the rumor is more closely related to the individual’s life, the individual will usually be less alert and have great motivation to share it with friends. Based on the typical Susceptible–Infected–Recovered (SIR) model, a new vigilant state is added to describe the above phenomenon and a Susceptible–Vigilant–Infectious–Recovered (SVIR) rumor model is proposed. In addition, considering the fact that the infectious with high emotion may cause emotional resonance among individuals, this model adds a connection edge from the recovered to the infectious triggered by emotional infection. Based on the obtained dynamic equations, the steady state of the model is analyzed by utilizing basic reproduction number method and verified on the generated homogeneous network as well as Facebook network. Simulation results reveal that the improvement of individual vigilance awareness can reduce the influence of rumor. Although high emotional infectious can promote the spread of rumor, appealing them to clarify the fact for curbing rumor spreading is a forceful measure.
Dissertations / Theses on the topic "Svir method"
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Петринська, Є. В. "Формування конкурентних переваг підприємства на засадах ощадливого управління". Thesis, Одеський національний економічний університет, 2021. http://local.lib/diploma/Petrynska.pdf.
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Доступ до роботи тільки на території бібліотеки ОНЕУ, для переходу натисніть на посилання нижче<br>У роботі розглядаються теоретичні основи формування конкурентних
переваг, у т.ч. встановлено сутність поняття «конкурентна перевага».
Проаналізовано ринок вантажних перевезень, виявлено конкурентну силу, яка має
найбільшого впливу на ринку.
Запропоновано заходи щодо формування та підтримки конкурентних
переваг підприємства ТОВ "Далекс Агро".<br>The paper considers the theoretical foundations of the competitive advantages'
formation. Тhe essence of the concept of "competitive advantage" is established.
The market of freight transportation is analyzed. It is found the force which has the
greatest competitive influence in the market.
It was proposed measures to form and maintain the competitive advantages of the
company LLC "Dalex Agro".
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Gustafsson, Karin, and Nana Johansson. "Barns svar på pressande frågetyper." Thesis, Örebro universitet, Institutionen för samhällsvetenskap, 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-22940.
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Syftet är att undersöka hur pressande frågetyper vid polisförhör påverkar barns (3-7 år gamla) svar. Tio förhörsutskrifter i dialogform har använts. Olika kategorier av pressande frågetyper samt av svarstyper konstruerades. Resultaten visar att barn i regel är känsliga för suggestion, men det förekommer undantag. Barn ändrar ofta svar när samma fråga upprepas.<br>The purpose is to study how pressing questions during police interrogations influence children´s answers. Ten transcriptions of police interrogations were analyzed for children 3 - 7 years old. The results show that children as a rule are influenced by suggestions. Children often change answers when the same question is repeated.
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Öhman, Adam. "The Calibrated SSVI Method - Implied Volatility Surface Construction." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-257501.
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In this thesis will the question of how to construct implied volatility surfaces in a robust and arbitrage free way be investigated. To be able to know if the solutions are arbitrage free was an initial investigation about arbitrage in volatility surfaces made. From this investigation where two comprehensive theorems found. These theorems came from Roper in \cite{Roper2010}. Based on these where then two applicable arbitrage tests created. These tests came to be very important tools in the remaining thesis.The most reasonable classes of models for modeling the implied volatility surface where then investigated. It was concluded that the classes that seemed to have the best potential where the stochastic volatility models and the parametric representation models. The choice between these two classes where concluded to be based on a trade-off between simplicity and quality of the result. If it where possible to make the parametric representation models improve its result the best applicable choice would be that class. For the remaining thesis was it therefore decided to investigate this class. The parametric representation model that was chosen to be investigated where the SVI parametrization family since it seemed to have the most potential outside of its already strong foundation.The SVI parametrization family is diveded into 3 parametrizations, the raw SVI parametrization, the SSVI parametrization and the eSSVI parametrization. It was concluded that the raw SVI parametrization even though it gives very good market fits, was not robust enough to be chosen. This ment that the raw SVI parametrization would in most cases generate arbitrage in its surfaces. The SSVI model was concluded to be a very strong model compared to the raw SVI, since it was able to generate completely arbitrage free solutions with good enough results. The eSSVI is an extended parametrization of the SSVI with purpose to improve its short maturity results. It was concluded to give small improvements but with the trade of making the optimization procedure harder. It was therefore concluded that the SSVI parametrization might be the better application.To try to improve the results of the SSVI parametrization was a complementary procedure developed which got named the calibrated SSVI method. This method compared to the eSSVI parametrization would not change the parametrization but instead focusing on calibrating the initial fit that the SSVI generated. This method would heavily improve the initial fit of the SSVI surface but was less robust since it generated harder cases for the interpolation and extrapolation.<br>I det här examensarbetet undersöks frågan om hur man bör modellera implied volatilitetsytor på ett robust och arbitragefritt sätt. För att kunna veta om lösningarna är arbigtragefria börjades arbetet med en undersökning inom arbitrageområdet. De mest heltäckande resultatet som hittades var två theorem av Roper i \cite{Roper2010}. Baserat på dessa theorem kunde två applicerbara arbitragetester skapas som sedan kom att bli en av hörnstenarna i detta arbete. Genom att undersöka de modellklasser som verkade vara de bästa inom området valdes den parametriseringsbeskrivande modellklassen. I denna klass valdes sedan SVI parametriseringsfamiljen för vidare undersökning eftersom det verkade vara den familj av modeller som hade störst potential att uppnå jämnvikt mellan enkel applikation samt bra resultat. För den klassiska SVI modellen i SVI familjen drogs slutsatsen att modellen inte var tillräcklig för att kunna rekommenderas. Detta berodde på att SVI modellen i princip alltid genererade lösningar med arbitrage i. SVI modellen genererar dock väldigt bra lösningar mot marknadsdatan enskilt och kan därför vara ett bra alternativ om man bara ska modellera ett implied volatilitetssmil. SSVI modellen ansågs däremot vara ett väldigt bra alternativ. SSVI modellen genererar komplett aribragefria lösningar men har samtidigt rimligt bra marknadspassning. För att försöka förbättra resultaten från SSVI modellen, var en kompleterande metod kallad den kalibrerade SSVI metoden skapad. Denna metod kom att förbättra marknadspassningen som SSVI modellen genererade men som resultat kom robustheten att sjunka, då interpoleringen och extrapoleringen blev svårare att genomföra arbitragefritt.
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Hlaváč, Martin. "Srovnání MKP modelů spojů." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2011. http://www.nusl.cz/ntk/nusl-229961.
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This thesis deals with the comparison of alternative models of the simplified joints used in the FEM models of complex models with detailed joint details. This is essentially a screw connection with dowel bolt and standard bolt, weld connection "T" and overlap weld connection. Individual connections are compared in the simulation results of matching models.
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Spjuth, Linda. "Di(2-ethylhexyl) phthalate and semen quality in boars : effects of pre-pubertal oral exposure on sperm production, viability and function post-puberty /." Uppsala : Dept. of Clinical Sciences, Swedish University of Agricultural Sciences, 2006. http://epsilon.slu.se/2006104.pdf.
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Vild, Martin. "Zesilování ocelových prutů namáhaných osovou silou pod zatížením." Doctoral thesis, Vysoké učení technické v Brně. Fakulta stavební, 2018. http://www.nusl.cz/ntk/nusl-390269.
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Dissertation focuses on strengthening of axially loaded steel members strengthened under load. Strengthening under load using welding is time and financially efficient. Plastic design can be used for members without stability problems. However, the design of members susceptible to buckling is difficult and opinions of researchers differ on this matter and there are only several experiments. The dissertation is focused on strengthening under load of members with selected cross-sections susceptible to flexural buckling. It is necessary to check the resistance of the base member weakened by the elevated temperatures caused by welding. The preload and welding – residual stress and deformations – must be taken into account for the determination of the buckling resistance of the member strengthened under load. The aim of this dissertation is to provide the load resistance of selected compressed members strengthened under load. Author performed experiments on members with the H and L shaped cross-sections and seamless tubes. Other experiments were performed on members with H shaped cross-section and rectangular hollow sections to determine the resistance of base member during welding. These served to validate numerical models which helped to increase the number of specimens for statistical evaluation. Analytical models to determine the load resistances of the base member during welding and the strengthened member were developed using experiments from literature and author’s experiments and numerical models. The simplified model is conservative and suitable for practical design. The complex model is suitable for scientific purpose and it provides both deformation and load resistance using modified imperfection factor. It provides a good agreement with the experiments. Doctoral thesis also includes practical recommendations for design and execution of strengthening under load using welding.
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Dallari, Pietro. "DSGEs and PVARs: applications to macroeconomics." Doctoral thesis, Universitat Pompeu Fabra, 2014. http://hdl.handle.net/10803/146249.
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This thesis adopts DSGE and PVAR models to examine three questions in macroeconomics. The first chapter singles out some pitfalls that DSGE models face when a fraction of rule-of-thumb consumers is assumed in order to replicate the positive response of consumption to government spending shocks observed in SVAR models. The second chapter quantifies the importance of the tourism channel for the international transmission of cyclical fluctuations to the Mediterranean basin. We show that, absent tourism flows, the output effects in a typical destination country would be one-fourth smaller. The third chapter examines the impact of austerity shocks on labor markets in the euro area. We find that the cross-country responses of labor market variables differ, notwithstanding similar output multipliers, as institutional reforms and dedicated policy plans foster the link between fiscal impulses and the domestic labor market.<br>Esta tesis adopta modelos DSGE y PVAR para examinar tres preguntas de macroeconomía. El primer capítulo identifica algunas dificultades que enfrentan los modelos DSGE cuando se supone que una fracción de consumidores sea de tipo rule-of-thumb con el fin de replicar la respuesta positiva del consumo a los shocks de gasto público que se observa en los modelos SVAR. El segundo capítulo cuantifica la importancia del canal de turismo para la transmisión internacional de las fluctuaciones cíclicas en la cuenca mediterránea. Se demuestra que, ausentes los flujos de turismo, los efectos sobre el producto en un país mediterráneo sería un cuarto menor. El tercer capítulo examina el impacto de los shocks de austeridad en los mercados laborales de la zona Euro. Encontramos que las respuestas de las variables del mercado laboral difieren entre los países, no obstante multiplicadores de producción similares. Las cuasas parecen estar relacionadas con reformas institucionales y planes de política económica dedicados que fomentan el vínculo entre los impulsos fiscales y del mercado laboral nacional.
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Sa'ad, Aisha. "Developing integrated maintenance strategies for renewable energy sources based on analytical methods and artificial intelligence (AI) : comparisons and case study." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0080.
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Au cours de ces récentes années, le développement des énergies renouvelables, en particulier l'énergie solaire et l'énergie éolienne, a attiré comme méthode alternative de production d'énergie, l'attention du monde entier avec une croissance exceptionnelle de sa production. Selon le rapport de Global Energy, l'énergie solaire mondiale devrait avoir atteint une capacité cumulée de 1 TW, tandis que l'énergie éolienne devrait avoir été multipliée par 3 ou 4 mégas par rapport à la production en 2020. Cette augmentation des énergies solaire et éolienne implique des investissements financiers très importants. Cependant, avec cet énorme potentiel d'investissement et l'augmentation significative de la capacité de production, il y a une responsabilité supplémentaire, souvent négligée : la gestion des centrales électriques pour assurer le coût total du cycle de vie le plus bas (Life Cycle Cost). Comme tout système de production standard, les composants de production d'énergie renouvelable (solaire et éolienne dans notre cas) sont sujets à des défaillances aléatoires qui interrompent la production et l'approvisionnement de la demande. La maintenance est identifiée comme une cause majeure d'accidents, on peut noter le manque de savoir-faire technique dans l'exploitation d'un équipement ou l'absence d'un bon plan de routine de maintenance. Dans le cadre des efforts visant à améliorer l'efficacité et la performance des centrales électriques à énergie renouvelable, nous proposons des modèles pour optimiser la production d'énergie et la maintenance dans nos études de cas sélectionnées (centrale solaire de Sokoto et parc éolien de Katsina au Nigéria). À cet égard, nous avons développé de nouvelles politiques de maintenance intégrées à la production d'énergie des systèmes d'énergie solaire et éolienne. La stratégie de maintenance préventive adoptée dans cette thèse est une stratégie de maintenance parfaite sur les composants sélectionnés pour la maintenance et une maintenance sélective imparfaite sur le système (solaire PV et éolienne). Le manque de batterie en cas de sous-production et les pertes de maintenance sont des défis considérés dans cette étude. La méthodologie que nous avons développée consiste à résoudre le problème d'optimisation de la production d'énergie et de la maintenance en utilisant la méthode théorique ainsi que la méthode d'apprentissage automatique (ANN et SVM) afin de satisfaire une demande aléatoire d'énergie pendant un horizon fini. Nous avons également étudié l'influence des conditions environnementales et opérationnelles des systèmes, puis validé les modèles par des exemples numériques et des études de sensibilité prouvant la robustesse des modèles développés<br>The development of renewable energy, especially solar and wind energy, over the recent years has gained global attention as an alternative method of generating energy experiencing exceptional growth in its production. In The Global Energy report, global solar energy is expected to have reached a cumulative capacity of 1TW while the wind energy is expected to have multiplied up to 3 to 4 times from mega production in the year 2020. This increase in the solar and wind power implies very significant financial investments. However, with this huge investment potential and significant increase in generation capacity, there is an additional, often overlooked responsibility: managing the power plants to ensure the lowest total life cycle cost (Life Cycle Cost). Like any standard production system, renewable energy (solar and wind energy in our case) generation components are subject to random failure, which interrupts production and supply of demand. Maintenance is identified as a major cause of accidents, lack of technical know-how of an equipment and the absence of a good maintenance routine plan. As part of the efforts to improve the efficiency and performance of renewable energy power plants, we propose models to optimize the power production and maintenance of our selected case studies (Sokoto solar plant and Katsina wind farm). In this regard, we developed new integrated maintenance policies integrated with production of the energy production from solar and wind energy systems. The preventive maintenance strategy adopted in this thesis is perfect maintenance strategy on the selected components for maintenance and an imperfect selective maintenance on the system (solar PV and wind turbine). Battery shortage in case of under-production and maintenance losses are challenges considered in this study. The methodology we developed entails solving the problem of energy production and maintenance optimization by using the theoretical method as well as machine learning method (ANN and SVM) in order to satisfy a random demand of energy during a finite horizon. We also studied the influence of environmental and operational condition of the systems and then validated the models by numerical examples and sensitivity studies proving the robustness of the developed models
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Falk, Anton, and Daniel Holmgren. "Sales Forecasting by Assembly of Multiple Machine Learning Methods : A stacking approach to supervised machine learning." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184317.
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Today, digitalization is a key factor for businesses to enhance growth and gain advantages and insight in their operations. Both in planning operations and understanding customers the digitalization processes today have key roles, and companies are spending more and more resources in this fields to gain critical insights and enhance growth. The fast-food industry is no exception where restaurants need to be highly flexible and agile in their work. With this, there exists an immense demand for knowledge and insights to help restaurants plan their daily operations and there is a great need for organizations to continuously adapt new technological solutions into their existing processes. Well implemented Machine Learning solutions in combination with feature engineering are likely to bring value into the existing processes. Sales forecasting, which is the main field of study in this thesis work, has a vital role in planning of fast food restaurant's operations, both for budgeting purposes, but also for staffing purposes. The word fast food describes itself. With this comes a commitment to provide high quality food and rapid service to the customers. Understaffing can risk violating either quality of the food or service while overstaffing leads to low overall productivity. Generating highly reliable sales forecasts are thus vital to maximize profits and minimize operational risk. SARIMA, XGBoost and Random Forest were evaluated on training data consisting of sales numbers, business hours and categorical variables describing date and month. These models worked as base learners where sales predictions from a specific dataset were used as training data for a Support Vector Regression model (SVR). A stacking approach to this type of project shows sufficient results with a significant gain in prediction accuracy for all investigated restaurants on a 6-week aggregated timeline compared to the existing solution.<br>Digitalisering har idag en nyckelroll för att skapa tillväxt och insikter för företag, dessa insikter ger fördelar både inom planering och i förståelsen om deras kunder. Det här är ett område som företag lägger mer och mer resurser på för att skapa större förståelse om sin verksamhet och på så sätt öka tillväxten. Snabbmatsindustrin är inget undantag då restauranger behöver en hög grad av flexibilitet i sina arbetssätt för att möta kundbehovet. Det här skapar en stor efterfrågan av kunskap och insikter för att hjälpa dem i planeringen av deras dagliga arbete och det finns ett stort behov från företagen att kontinuerligt implementera nya tekniska lösningar i befintliga processer. Med väl implementerade maskininlärningslösningar i kombination med att skapa mer informativa variabler från befintlig data kan aktörer skapa mervärde till redan existerande processer. Försäljningsprognostisering, som är huvudområdet för den här studien, har en viktig roll för verksamhetsplaneringen inom snabbmatsindustrin, både inom budgetering och bemanning. Namnet snabbmat beskriver sig själv, med det följer ett löfte gentemot kunden att tillhandahålla hög kvalitet på maten samt att kunna tillhandahålla snabb service. Underbemanning kan riskera att bryta någon av dessa löften, antingen i undermålig kvalitet på maten eller att inte kunna leverera snabb service. Överbemanning riskerar i stället att leda till ineffektivitet i användandet av resurser. Att generera högst tillförlitliga prognoser är därför avgörande för att kunna maximera vinsten och minimera operativ risk. SARIMA, XGBoost och Random Forest utvärderades på ett träningsset bestående av försäljningssiffror, timme på dygnet och kategoriska variabler som beskriver dag och månad. Dessa modeller fungerar som basmodeller vars prediktioner från ett specifikt testset används som träningsdata till en Stödvektorsreggresionsmodell (SVR). Att använda stapling av maskininlärningsmodeller till den här typen av problem visade tillfredställande resultat där det påvisades en signifikant förbättring i prediktionssäkerhet under en 6 veckors aggregerad period gentemot den redan existerande modellen.
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Smělý, Pavel. "Rozpoznávání hudební nálady a emocí za pomoci technik Music Information Retrieval." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-401982.
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This work focuses on scientific area called Music Information Retrieval, more precisely it’s subdivision focusing on the recognition of emotions in music called Music Emotion Recognition. The beginning of the work deals with general overview and definition of MER, categorization of individual methods and offers a comprehensive view of this discipline. The thesis also concentrates on the selection and description of suitable parameters for the recognition of emotions, using tools openSMILE and MIRtoolbox. A freely available DEAM database was used to obtain the set of music recordings and their subjective emotional annotations. The practical part deals with the design of a static dimensional regression evaluation system for numerical prediction of musical emotions in music recordings, more precisely their position in the AV emotional space. The thesis publishes and comments on the results obtained by individual analysis of the significance of individual parameters and for the overall analysis of the prediction of the proposed model.
Books on the topic "Svir method"
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(Editor), Austin J. Lewis, and L. Lee Southern (Editor), eds. Swine Nutrition, Second Edition. 2nd ed. CRC, 2000.
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Kosanović, Saja, Nevena Novaković, and Alenka Fikfak. PREGLEDI ODRŽIVOSTI I OTPORNOSTI GRAĐENE SREDINE. TU Delft Bouwkunde, 2018. http://dx.doi.org/10.47982/bookrxiv.10.
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Održiva i otporna građena sredina je složen sistem čije se značenje kontinualno razvija. Cilj ove publikacije je da problemu održivosti i otpornosti pristupi kroz sistematsko istraživanje različitih segmenata i razmera izgrađenog okruženja, odnosno da predstavljanjem preglednih radova (poglavlja), među kojima je uspostavljena odgovarajuća funkcionalna veza, podstakne razvoj specijalizovanog znanja, podigne kritičku svest o potrebi za interdisciplinarnim i transdiciplinarnim istraživanjem i ojača vezu između univerzitetskog obrazovanja i naučnog istraživanja. Analiza razvoja održivosti i otpornosti, istraživanje aktuelnih pitanja i predviđanja o mogućoj održivoj i otpornoj budućnosti zajedno omogućavaju sveobuhvatno razumevanje ovih koncepata i njihovih međusobnih odnosa u kontekstu građene sredine. Publikacija je izbor recenziranih radova, objavljenih na engleskom jeziku u okviru tematske serije pod naslovom Reviews of Sustainability and Resilience of the Built Environment for Education, Research and Design. I pomenuta serija i ova publikacija predstavljaju rezultate Erazmus+ projekta Stvaranje mreže laboratorija znanja za održive i otporne sredine (skr. en. KLABS), koji je posvećen uspostavljanju sveobuhvatne obrazovne platforme u okviru drugog ciklusa visokog obrazovanja na prostoru zapadnog Balkana. Širi cilj svih KLABS publikacija je bio da se razviju pregledi održivosti i otpornosti građene sredine, korisni za studente, nastavnike, istraživače i stručnjake koji se ovim važnim temama bave na međunarodnom nivou. Publikacija se sastoji iz dva dela. Prvi se bavi održivošću i otpornošću urbanog prostora a drugi nivoom zgrada. Istraživanje počinje teorijskim pregledom istorijske i savremene debate o problemu urbanizacije u svrhu razumevanja i novih tumačenja (urbane) održivosti. Zatim se tumače poreklo, istorija i razvoj koncepta otpornosti, evolucija njegove definicije, tipovi i ključni principi. U trećem poglavlju istraživanje je usmereno na neka fundamentalna pitanja u okviru socio-kulturološke ravni građene sredine. Sledeće poglavlje pruža pregled pojmova i strategija koncepata „efikasnosti resursa“ i „otpornosti“, prikazuje njihova zajednička područja delovanja, kao i potencijalne protivrečnosti i suprotnosti, u svrhu nalaženja uzajamne ravnoteže i davanja doprinosa ispunjavanju širih ciljeva održivosti. Istraživanje alternativnih modela potrošnje, potrebnih za postizanje održivih urbanih transformacija, predstavlja predmet petog poglavlja u okviru ove publikacije. U nastavku se pažnja usmerava na rekonstrukciju trenutnog naučnog istraživanja i nalaženje ograničenja i mogućnosti inicijativa koje su do sada preduzete, kao i na sintezu metodoloških i praktičnih predloga, kako bi se javnoj upravi i lokalnim organima ponudio „praktičan način” stvaranja efikasnijih klimatskih politika i planova. „Pouka Milana”, u sedmom poglavlju, pokazuje kako aktivno uključivanje poljoprivrednika može pomoći javnim politikama, štiteći zajedničko dobro u teškim okolnostima i dajući povod za alternativne načine planiranja; ona naročito može da inspiriše istraživanje u kontekstima gde su otvoreni prostori oko gradova ugroženi, a uključivanje u proces donošenja odluka predstavlja cilj koji treba postići. U poslednjem poglavlju prvog dela elaboriraju se definicija, klasifikacija i kritička analiza uticaja braunfilda na okruženje i definišu ciljevi održivosti koje treba postići kroz njihovu obnovu i ponovni razvoj. Drugi deo publikacije počinje uspostavljanjem veze između efikasnog korišćenja prirodnih resursa i smanjenja ekoloških uticaja zgrada. Ovde se daje pregled sadašnjih trendova i izazova u pogledu upotrebe energije, materijala, vode i zemljišta i promišljaju mogući scenariji efikasne budućnosti u kojoj bi šire socijalne i ekonomske sheme postale relevantnije za uspešno projektovanje ekološki ispravnih zgrada. Fokus se, zatim, usmerava na analizu složenosti i dinamike klimatskih promena kao ključnih faktora u oblikovanju strategija za projektovanje zgrada otpornih na delovanje klime. Na osnovu značaja sagledanih rizika, varijabilnosti i neizvesnosti u vezi sa klimatskim promenama izvodi se opšti projektantski okvir, obrazlaže značenje termina „transponovani regionalizam“ i diskutuje odnos između otpornosti i adaptacije zgrada u (ne)izvesnoj klimatskoj budućnosti. U trećem poglavlju drugog dela istražuju se međusobni odnosi održive arhitekture i arhitekture otporne na promenu klime tako što se upoređuju njihovi osnovni postulati i analiziraju ključni ciljevi, kroz prizmu uzajamnih (ne)konzistentnosti. Sledeće poglavlje obrazlaže hijerarhijski pristup projektovanju održivih zgrada i daje pregled niza aktivnih i pasivnih projektantskih mera koje su, pre svega, u funkciji postizanja energetske efikasnosti, poput toplotne zaštite, ostvarivanja solarnih dobitaka, disipacije toplote, generisanja toplote, aktivnog ventilisanja i hlađenja, kao i generisanja električne energije iz obnovljivih izvora. Energetska svojstva i toplotni komfor u zgradama, u petom poglavlju drugog dela, razmatrani su sa aspekta uticaja materijala. Na primeru karakterističnih tipova stambenih zgrada sa područja Beograda, koje su prikazane i analizirane, razmatran je stepen zadovoljavanja ukupnih zahteva komfora, kao i međuzavisnost koja postoji između različitih tipova komfora (toplotnog, vazdušnog, zvučnog i svetlosnog). Poslednje poglavlje prikazuje činjenice i primere koji su relevantni za razumevanje i primenu metodologije ocene životnog ciklusa u različitim projektantskim i inženjerskim okvirima. Ovde se detaljno analizira struktura metode ocene životnog ciklusa (en. Life Cycle Assessment – LCA), koja se koristi za kvantifikovanje ekoloških uticaja.
Book chapters on the topic "Svir method"
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Zhou, Guo-Chang, Yang-Ming Guo, and Jie-Zhong Ma. "Time Series Weighted Prediction Method Using Multikernel LS-SVR." In Proceedings of the First Symposium on Aviation Maintenance and Management-Volume I. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54236-7_28.
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Liu, Bing, Shoujuan Huang, Ruidong Wu, and Ping Fu. "Implementation Method of SVR Algorithm in Resource-Constrained Platform." In Advances in Intelligent Information Hiding and Multimedia Signal Processing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9710-3_9.
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Zhao, Yang, Lanfang Dong, Guoxin Li, et al. "SVIM: A Skeleton-Based View-Invariant Method for Online Gesture Recognition." In Advanced Data Mining and Applications. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-46674-8_17.
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Bao, Yukun, Wen Wang, and Hua Zou. "SVR-Based Method Forecasting Intermittent Demand for Service Parts Inventories." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11548706_64.
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Wang, Zhiyong, Haibin Cai, and Honghai Liu. "Robust Eye Center Localization Based on an Improved SVR Method." In Neural Information Processing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04239-4_56.
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Yao, Yu, Dongliang Cheng, Gang Peng, and Xuejuan Huang. "Fault Prognosis Method of Industrial Process Based on PSO-SVR." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29933-0_28.
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Huang, Haoqian, Rong Qiu, Aoqi Lv, and Mengdie Zhang. "A Novel Underwater PSO-SVR Calibration Method for SINS/DVL." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2204-7_42.
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Chen, Wei, Zheng Wei, Xinyu Lei, Shaoze Zhou, Xinzhe Song, and Wei Wang. "Stability Analysis of SVI Multi-parallel System Based on Impedance Method." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0869-7_17.
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Tao, Yanyun, Dan Xiang, Yuzhen Zhang, and Bin Jiang. "Swarm ANN/SVR-Based Modeling Method for Warfarin Dose Prediction in Chinese." In Lecture Notes in Computer Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61833-3_37.
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Guo, Yangming, Xiaolei Li, Guanghan Bai, and Jiezhong Ma. "Time Series Prediction Method Based on LS-SVR with Modified Gaussian RBF." In Neural Information Processing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34481-7_2.
Full textConference papers on the topic "Svir method"
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Xu, Hua, and Yang Chen. "Cost Prediction Method of Construction Engineering Based on Improved NSGA-II-SVR." In 2024 8th Asian Conference on Artificial Intelligence Technology (ACAIT). IEEE, 2024. https://doi.org/10.1109/acait63902.2024.11022144.
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Yao, Rui, and Hao Luo. "Research on GNSS multipath error weakening method based on PSO-SVR model." In Fourth International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2025), edited by Jinjian Wu and Juanle Wang. SPIE, 2025. https://doi.org/10.1117/12.3067287.
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Du, Yongkun, Zhineng Chen, Caiyan Jia, et al. "SVTR: Scene Text Recognition with a Single Visual Model." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/124.
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Dominant scene text recognition models commonly contain two building blocks, a visual model for feature extraction and a sequence model for text transcription. This hybrid architecture, although accurate, is complex and less efficient. In this study, we propose a Single Visual model for Scene Text recognition within the patch-wise image tokenization framework, which dispenses with the sequential modeling entirely. The method, termed SVTR, firstly decomposes an image text into small patches named character components. Afterward, hierarchical stages are recurrently carried out by component-level mixing, merging and/or combining. Global and local mixing blocks are devised to perceive the inter-character and intra-character patterns, leading to a multi-grained character component perception. Thus, characters are recognized by a simple linear prediction. Experimental results on both English and Chinese scene text recognition tasks demonstrate the effectiveness of SVTR. SVTR-L (Large) achieves highly competitive accuracy in English and outperforms existing methods by a large margin in Chinese, while running faster. In addition, SVTR-T (Tiny) is an effective and much smaller model, which shows appealing speed at inference. The code is publicly available at https://github.com/PaddlePaddle/PaddleOCR.
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Chen, Yuhao, Mustafa Onur, Nihal Kuzu, and Onur Narin. "Prediction and History Matching of Observed Production Rate and Bottomhole Pressure Data Sets from in Situ Cross-Linked Polymer Gel Conformance Treatments Using Machine Learning Methods." In SPE Europe Energy Conference and Exhibition. SPE, 2024. http://dx.doi.org/10.2118/220110-ms.
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Abstract The objective of this study is to develop a computationally efficient methodology for the prediction of oil rate, water rate, and injection bottomhole pressure (BHP), and history matching of such well outputs to estimate important rock and fluid parameters that have a significant impact on reservoir conformance after in situ polymer gel treatment. Two different machine learning (ML) proxy methods are investigated for performing prediction and history matching of well output data such as oil production rate, water production rate, and/or injection BHP that may be acquired before and after polymer gel treatment. One of the ML methods used is the least-squares support vector regression (LS-SVR) and the other is the long short-term memory (LSTM) network, a deep learning method based on the recurrent neural network (RNN). The LS-SVR and LSTM proxy models are built on training sets of BHP and rate data generated with a high-fidelity commercial numerical simulator. The high-fidelity model is based on compositional flow simulation using double permeability fracture models. The reservoir models used in history matching are calibrated by using synthetic BHP, oil, and/or water production rate data sets before and after polymer gel treatment. The ensemble smoother multiple data (ES-MDA) method is used for history matching and prediction for the uncertainty assessment of the polymer gel treatment period, while a high-fidelity simulator is used for history matching. When the high-fidelity simulator is replaced with any of the ML-based methods, we use a randomized maximum likelihood estimation (RMLE) method where the gradients are analytically computed for the LS-SVR surrogate model, while the LSTM is replaced by the high-fidelity simulator, we compute the gradients of the LSTM by stochastic simplex approximate gradient (StoSAG) method. Results show that the LS-SVR and LSTM methods provide significant computational savings over the conventional simulation and history matching with a high-fidelity model. LSTM provides better predictions than LS-SVR for the same size of training sets. However, for larger training sets, LSTM provides a significant computational gain over LS-SVR. In addition, the results also identify the key parameters that have a significant impact on the performance of in situ polymer gel treatment. These parameters are the relative permeability curves of oil and water, absolute fracture permeability, polymer and cross-linked concentrations, and residual resistance factors (RRFT) are the key parameters in the performance of in situ polymer gel treatment.
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Golestani, Maziar, and Mostafa Zeinoddini. "Gap-Filling and Predicting Wave Parameters Using Support Vector Regression Method." In ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-49814.
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Knowledge of relevant oceanographic parameters is of utmost importance in the rational design of coastal structures and ports. Therefore, an accurate prediction of wave parameters is especially important for safety and economic reasons. Recently, statistical learning methods, such as Support Vector Regression (SVR) have been successfully employed by researchers in problems such as lake water level predictions, and significant wave height prediction. The current study reports potential application of a SVR approach to predict the wave spectra and significant wave height. Also the capability of the model to fill data gaps was tested using different approaches. Concurrent wind and wave records (standard meteorological and spectral density data) from 4 stations in 2003, 2007, 2008 and 2009 were used both for the training the SVR system and its verification. The choice of these four locations facilitated the comparison of model performances in different geographical areas. The SVR model was then used to obtain predictions for the wave spectra and also time series of wave parameters (separately for each station) such as its Hs and Tp from spectra and wind records. New approach was used to predict wave spectra comparing to similar studies. Reasonably well correlation was found between the predicted and measured wave parameters. The SVR model was first trained and tested using various methods for selecting training data. Also different values for SVM parameters (e.g. tolerance of termination criterion, cost, and gamma in kernel function) were tested. The best possible results were obtained using a Unix shell script (in Linux) which automatically implements different values for different input parameters and finds the best regression by calculating statistical scores like correlation of coefficient, RMSE, bias and scatter index. Finally for a better understanding of the results, Quantile-Quantile plots were produced. The results show that SVR can be successfully used for prediction of Hs and wave spectrum out of a series of wind and spectral wave parameters inputs. Also it was noticed that SVR is an efficient tool to be used when data gaps are present in the data.
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Ahmadi Asl, Farshad, and Mehmet Bodur. "Comparison of Forecasting Methods of House Electricity Consumption for Honda Smart Home." In 12th International Conference on Computer Science and Information Technology (CCSIT 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.121311.
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The electricity consumption of buildings composes a major part of the city’s energy consumption. Electricity consumption forecasting enables the development of home energy management systems, resulting in the future design of more sustainable houses and a decrease in total energy consumption. Energy performance in buildings is influenced by many factors, like ambient temperature, humidity, and a variety of electrical devices. Therefore, multivariate prediction methods are preferred rather than univariate. The Honda Smart Home US data set was selected to compare three methods for minimizing forecasting errors, MAE and RMSE: Artificial Neural Networks (ANN), Support Vector Regression (SVR), and Fuzzy RuleBased Systems (FRBS) for Regression by constructing many models for each method on a multivariate data set in different time-terms. The comparison shows that SVR is a superior method over the alternatives.
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Shengchao, Su, Deng Na, and Hu Yi Gang. "An SVR-Based Online Fault Detection Method." In 2011 International Conference on Measuring Technology and Mechatronics Automation (ICMTMA). IEEE, 2011. http://dx.doi.org/10.1109/icmtma.2011.113.
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Shilei Zhao and Yupeng Liu. "An Fault Detection Method based on Compensation of SVMR." In International Conference on Software Intelligence Technologies and Applications & International Conference on Frontiers of Internet of Things 2014. Institution of Engineering and Technology, 2014. http://dx.doi.org/10.1049/cp.2014.1588.
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Almasov, Azad, and Mustafa Onur. "Life-Cycle Gradient-Based Production Optimization Including Well-Shutoff Option with Least-Squares Support Vector Regression." In SPE Annual Technical Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/215110-ms.
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Abstract The objective of this work is to present an efficient method based on gradient-based optimization using a least-squares support-vector regression (LS-SVR) model to solve well-shutoff and well-control optimization problems. We formulate a continuous differentiable NPV for the well shutoff optimization problem. In our approach, switching well on/off times are considered part of the design variables. Our parameterization is based on a fixed number of cycles, the length of each cycle, and the production time fraction in each cycle. The remaining fraction of each cycle is the shutoff time fraction. We use linear equality constraints so that the summation of the length of each cycle is equal to the life of the production, and thus, we do not need to truncate the length of the last cycle. We consider both the stochastic simplex gradient optimization and the machine learning-based least-squares support vector regression (LS-SVR) proxy but we update it during optimization so that the updated proxy remains predictive toward promising regions of search space during the optimization. We compare the performance of the proposed method using the LS-SVR runs coupled with iterative sampling refinement method (ISR) to update the proxy during optimization with the popular stochastic simplex approximate gradient (StoSAG) and reservoir- simulations runs for a synthetic example considering a waterflooding process in a conventional compositional oil reservoir with 2 water injectors and 4 producers. Results show that higher computational efficiency is achieved using the LS-SVR-based optimization method over the StoSAG-based optimization method using a high-fidelity numerical simulator. The proposed LS-SVR-based framework is shown to be at least 3 to 7 times computationally more efficient, depending on the cases considered than the StoSAG using a high-fidelity numerical simulator. For the waterflooding optimization example, designing multiple shutoffs and making cycle length unknown are found to be not beneficial as compared to single shutoff cases as they yield lower NPVs than single shutoff cases. However, we observe that the size and sampling of the training data, as well as the selection of bound constraints for the well controls, influence the performance of the LS-SVR-based optimization method. The well-shutoff/well-control optimization problem can be handled with the gradient-based optimization methods by introducing a production time fraction as the design variable for each cycle. This is the first LSSVR application for the well shutoff and well-control optimization problem. The proposed LS-SVR-based optimization framework has great potential to be used as an efficient tool for this type of optimization problem.
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Cebrián, Eduardo, and Josep Domenech. "Simulating the inconsistencies of Google Trends data." In CARMA 2022 - 4th International Conference on Advanced Research Methods and Analytics. Universitat Politècnica de València, 2022. http://dx.doi.org/10.4995/carma2022.2022.15093.
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Google Trends (GT) allows users to obtain reports of the evolution of the popularity of searchers made through the Google Search engine. Its main output is the Search Volume Index (SVI), a relative measure of the popularity of a term, which is computed using a sample of the searches. Due to the sampling error, the reports are not completely consistent, as the same query produces different time series that can widely change from day to day. This paper simulates the process of generating the SVI time series in the same way as GT does. By doing this, it has been shown that the sampling error could be an important issue if the popularity of the term under study is relatively low. Averaging multiple extractions from GT can only partially alleviate this.
Reports on the topic "Svir method"
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Saboin, José Luis, Jorge Hirs, Leandro Gaston Andrian, and Augusto Chávez. The Evolution of External Shocks and Macrofiscal Outcomes in the Andes. Inter-American Development Bank, 2024. http://dx.doi.org/10.18235/0012972.
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The abundance of natural resources can adversely affect the macroeconomic stability of countries. Developing economic institutions that support the proper management of extractive industry resources is one of the fundamental factors for maintaining macroeconomic stability and generating long-term economic growth. This paper evaluates the impact of terms-of-trade shocks on fiscal performance and economic growth in the countries of the Andean region. To adequately capture the variation in both the magnitude of shocks and the sensitivity of economic and fiscal variables to those shocks, this paper makes use of a TV-SVAR model. This method allows us to evaluate whether the presence of fiscal institutions change their sensitivity to external disturbances. The results presented in this paper show a time-varying dynamic of both (1) terms-of-trade shocks and (2) the sensitivity of the Andean regions economies to such shocks, although with marked heterogeneity across countries. This heterogeneity coincides with the uneven development of the economic institutions in the countries of the region. The results highlight the importance of developing adequate economic policy frameworks in order to adequately mitigate the volatility in the terms-of-trade.
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Strömquist, Jennie, and Håkan Wickström. Rekryteringsindex för ål : metodutveckling för framtagning av index för ålrekryter. Department of Aquatic Resources, Swedish University of Agricultural Science, 2025. https://doi.org/10.54612/a.4c493aga8b.
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Ålbeståndets minskning i Sverige började uppmärksammas i början av 1970-talet då fångsterna av adult ål i yrkesfisket minskade kraftigt. I övriga Europa märktes en nedgång i fångsterna av glasål i början av 1980-talet. Som en del av arbetet med att förbättra situationen för europeisk ål utfärdade EU en förordning år 2007, som bland annat innebär att alla medlemsstater ska ta fram förvaltningsplaner för ål. Dessa ska innehålla åtgärder för återhämtning av beståndet av europeisk ål, med beaktande av regionala och lokala förhållanden. Sveriges ålförvaltningsplan fokuserar främst på ökad kontroll, inskränkningar i fisket, förbättrade möjligheter för blankål att vandra ut i havet, och stödutsättningar av importerade ålyngel. För att följa beståndets utveckling, och övervaka om åtgärderna får önskad effekt, används bland annat ett internationellt rekryteringsindex. Arbetet med att ta fram ett rekryteringsindex för Sverige påbörjades år 2010. Som ett första steg behövdes en lämplig metod för att skatta mängd ålyngel i ett vattendrag eller på en plats tas fram. En annan viktig aspekt är att rekryteringsindex inte ska vara påverkade av ålutsättningar. I Sverige märks alla importerade ålyngel sedan 2009 kemiskt med strontium (Sr) innan de sätts ut, vilket skapar en permanent Sr-märkning i ålarnas hörselstenar (otoliter) vilket gör det möjligt att skilja på utsatta ålar och naturliga rekryter. Eftersom denna provtagning är dödande (ålen måste dissekeras för att otoliterna ska kunna användas) så kan även annan viktig biologisk data samlas in, så som längd, vikt, parasitförekomst, och ålder. Denna rapport sammanfattar resultaten från arbetet med att ta fram ett rekryteringsindex för ål i Sverige. Metodutvecklingsförsök för att skatta mängd ålyngel och för att samla in ål för vidare provtagning, gjordes med fallfälla, nättingfälla och elfisken. Fallfälla och nättingfälla användes på sammanlagt 19 platser (2010–2013). Elfiske utfördes i 5-16 vattendrag årligen mellan 2010-2020, . Två av vattendragen valdes ut som ”referensvattendrag”, vattendrag som ligger långt från platser där importerad ål satts ut, där de rekryterande ålynglen borde bestå av naturliga rekryter. Detta för att kunna jämföra storleks- och åldersfördelning hos rekryter mellan vattendrag där populationen endast består av naturliga rekryter, med vattendrag där ålynglen både kan härstamma från importerade utsatta (Sr-märkta) ålyngel och naturligt invandrade. Försöken att samla in yngel med fallfälla i grunda kustområden, respektive med nättingfälla i rinnande vatten, resulterade i ett fåtal fångster. De låga fångsterna kan dels förklaras av praktiska problem med fällorna och dels att den låga tätheten av ålyngel gjorde att fällorna inte fungerade effektivt. Elfiske är den metod som ansågs mest framgångsrik, Största problemet med denna metod var att den inte fungerade tillfredställande vid låga tätheter vilket leder till att skattningar, och därmed jämförelser mellan lokaler blir osäkra. På alla platser som undersöktes (oavsett metod) fann vi ålyngel av naturligt rekryterat ursprung. Importerade utsatta (Sr-märkta) ålyngel återfanns endast på totalt fyra av de undersökta platserna Dessa fyra ligger i närheten av områden där man årligen sätter ut importerade yngel, varför förekomst av utsatta ålyngel var förväntat. Många platser där importerad utsatt ål inte återfanns ligger dock också i närheten av områden där ål sätts ut. Resultatet kan förklaras med att de utsatta ålynglen direkt simmar långt upp i vattendragen (uppströms de lokaler som undersökts), hellre än att stanna kvar i kustnära områden, alternativt att de av någon anledning simmar ut till havs igen, eller att dödligheten är hög. Detta i sig kan tyda på att de rör sig på ett annat sätt än de naturliga rekryterna. Resultatet innebär också att man inte enbart kan använda data över utsättningar för att få ett säkert svar på om ett rekryteringsindex är påverkat av utsättningar eller inte. Sammantaget visar dessa undersökningar att elfiske är den metod (av de tre metoder som undersökts) som lämpar sig bäst för att skatta mängd ål och för att samla in ålrekryter. Undersökningen visar också att flera av de undersökta lokalerna lämpar sig väl för att skapa rekryteringsindex, eftersom många områden inte hade någon förekomst av importerade och utsatta ålyngel.