Relevant bibliographies by topics / Dynamic series

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Dynamic series'

Author: Grafiati
Published: 7 June 2025
Last updated: 26 June 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Dynamic series.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Dynamic series"

1

Roslan, Muhammad Amirul Asyraf, Nadia Nazieha Nanda, and Siti Hajar Yusoff. "SERIES-SERIES AND SERIES-PARALLEL COMPENSATION TOPOLOGIES FOR DYNAMIC WIRELESS CHARGING." IIUM Engineering Journal 22, no. 2 (2021): 199–209. http://dx.doi.org/10.31436/iiumej.v22i2.1660.

Full text
Abstract:
Electric vehicles (EV) have gained worldwide attention since the implementation of a wireless power transfer (WPT) to charge their batteries. With WPT, it can be very convenient for EV to be charged dynamically. Nevertheless, there are some issues in dynamic WPT, such as maintaining the power transfer efficiency. Several factors that lead to these problems include disruption of the alignment and the optimum distance between the transmitter and receiver coils. It is thus contributing to the loss of power efficiency when charging the EV. Not to mention, manufacturers build different specifications of EV charging station for different types of EV models in order to meet customer demands. An incompatible charging device will not utilize EV wireless charging to its maximum potential. Hence, to improve the power output capability as well as stabilizing the maximum power transfer during the charging process, a compensation circuit is added to the system. This article focuses on comparing two available compensation circuits (series-series (SS) topology and series-parallel (SP) topology) under the application of dynamic wireless charging. The simulations are conducted using NI Multisim based on the relationship of power transfer efficiency with resonance frequency, coefficient of coupling, and the load resistance. The WPT efficiency for SP-topology shows that it is sensitive to the change of resonance frequency and coupling coefficient, whereas SS-topology maintains good efficiency during the WPT process. Nonetheless, SS-topology performance suffers efficiency loss when paired with a higher load, while SP-topology acts differently. This article will observe the best conditions on the selected compensation designs for better application in EV charging systems in a moving state. ABSTRAK: Kenderaan elektrik (EV) telah menarik perhatian dunia sejak pelaksanaan alih kuasa wayarles (WPT) bagi mengecas bateri. Melalui WPT, EV lebih mudah kerana ia boleh dicas secara dinamik. Namun, pengecasan dinamik WPT turut mengalami masalah, seperti mengimbang kecekapan pemindahan kuasa. Beberapa faktor yang membawa kepada masalah ini adalah kerana terdapat gangguan penjajaran dan jarak optimum antara gegelung pemancar dan penerima. Kerana ini, ia menyumbang kepada kehilangan kecekapan kuasa semasa mengecas EV. Pengeluar juga membina spesifikasi stesen pengisian EV berlainan mengikut jenis model EV demi memenuhi permintaan pelanggan. Namun, platform pengecas EV yang berbeza, tidak dapat mengecas EV secara wayarles dengan maksimum. Oleh itu, bagi membaiki keupayaan jana kuasa serta menstabilkan pengeluaran kuasa maksimum semasa proses pengecasan, litar gantian ditambah ke dalam sistem. Artikel ini memberi keutamaan pada dua litar gantian berbeza (topologi bersiri (SS) dan siri-selari (SP)) di bawah aplikasi pengecasan wayarles dinamik. Simulasi dibuat menggunakan NI Multisim mengikut kecekapan pemindahan kuasa dengan frekuensi resonan, pekali gandingan dan rintangan beban. Kecekapan WPT bagi topologi-SP menunjukkan ianya sensitif pada perubahan frekuensi resonan dan pekali gandingan. Manakala topologi-SS kekal cekap semasa proses WPT. Walau bagaimanapun, prestasi topologi-SS berkurangan ketika diganding dengan beban besar, begitu juga berbeza bagi topologi-SP. Artikel ini akan mengkaji keadaan terbaik pada reka bentuk gantian terpilih bagi aplikasi EV dalam sistem pengecasan bergerak.
APA, Harvard, Vancouver, ISO, and other styles
2

Wall, Kent D., Christian Gourieroux, and Alain Monfort. "Time Series and Dynamic Models." Journal of the American Statistical Association 93, no. 443 (1998): 1248. http://dx.doi.org/10.2307/2669890.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

de Jong, Robert M., and Tiemen Woutersen. "DYNAMIC TIME SERIES BINARY CHOICE." Econometric Theory 27, no. 4 (2011): 673–702. http://dx.doi.org/10.1017/s0266466610000472.

Full text
Abstract:
This paper considers dynamic time series binary choice models. It proves near epoch dependence and strong mixing for the dynamic binary choice model with correlated errors. Using this result, it shows in a time series setting the validity of the dynamic probit likelihood procedure when lags of the dependent binary variable are used as regressors, and it establishes the asymptotic validity of Horowitz’s smoothed maximum score estimation of dynamic binary choice models with lags of the dependent variable as regressors. For the semiparametric model, the latent error is explicitly allowed to be correlated. It turns out that no long-run variance estimator is needed for the validity of the smoothed maximum score procedure in the dynamic time series framework.
APA, Harvard, Vancouver, ISO, and other styles
4

Caby, Errol. "Time Series and Dynamic Models." Technometrics 40, no. 2 (1998): 158. http://dx.doi.org/10.1080/00401706.1998.10485204.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

So, Mike K. P., and Ray S. W. Chung. "Dynamic seasonality in time series." Computational Statistics & Data Analysis 70 (February 2014): 212–26. http://dx.doi.org/10.1016/j.csda.2013.09.010.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Solodusha, S. V. "Software Package «Dynamics» for Studying Dynamic Processes by Volterra Series." Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics 17, no. 2 (2017): 83–92. http://dx.doi.org/10.14529/ctcr170207.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Heitmann, Stewart, and Michael Breakspear. "Putting the “dynamic” back into dynamic functional connectivity." Network Neuroscience 2, no. 2 (2018): 150–74. http://dx.doi.org/10.1162/netn_a_00041.

Full text
Abstract:
The study of fluctuations in time-resolved functional connectivity is a topic of substantial current interest. As the term “dynamic functional connectivity” implies, such fluctuations are believed to arise from dynamics in the neuronal systems generating these signals. While considerable activity currently attends to methodological and statistical issues regarding dynamic functional connectivity, less attention has been paid toward its candidate causes. Here, we review candidate scenarios for dynamic (functional) connectivity that arise in dynamical systems with two or more subsystems; generalized synchronization, itinerancy (a form of metastability), and multistability. Each of these scenarios arises under different configurations of local dynamics and intersystem coupling: We show how they generate time series data with nonlinear and/or nonstationary multivariate statistics. The key issue is that time series generated by coupled nonlinear systems contain a richer temporal structure than matched multivariate (linear) stochastic processes. In turn, this temporal structure yields many of the phenomena proposed as important to large-scale communication and computation in the brain, such as phase-amplitude coupling, complexity, and flexibility. The code for simulating these dynamics is available in a freeware software platform, the Brain Dynamics Toolbox.
APA, Harvard, Vancouver, ISO, and other styles
8

Jardim França, Gleisson, and Braz de Jesus Cardoso Filho. "Series-shunt compensation for harmonic mitigation and dynamic power factor correction." Eletrônica de Potência 17, no. 3 (2012): 641–50. http://dx.doi.org/10.18618/rep.2012.3.641650.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Li, Peiqiang, Jiang Zhang, Canbing Li, et al. "Dynamic Similar Sub-Series Selection Method for Time Series Forecasting." IEEE Access 6 (2018): 32532–42. http://dx.doi.org/10.1109/access.2018.2843774.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Borgards, Oliver. "Dynamic time series momentum of cryptocurrencies." North American Journal of Economics and Finance 57 (July 2021): 101428. http://dx.doi.org/10.1016/j.najef.2021.101428.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Dynamic series"

1

Haas, Markus. "Dynamic mixture models for financial time series /." Berlin : Pro Business, 2004. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=012999049&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

VASSALLO, Danilo. "Dynamic models for financial and sentiment time series." Doctoral thesis, Scuola Normale Superiore, 2022. http://hdl.handle.net/11384/109584.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Zhang, Guangjian. "Bootstrap procedures for dynamic factor analysis." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1153782819.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Zhou, Pu. "A dynamic approximate representation scheme for streaming time series." Connect to thesis, 2009. http://repository.unimelb.edu.au/10187/6766.

Full text
Abstract:
The huge volume of time series data generated in many applications poses new challenges in the techniques of data storage, transmission, and computation. Further more, when the time series are in the form of streaming data, new problems emerge and new techniques are required because of the streaming characteristics, e.g. high volume, high speed and continuous flowing. Approximate representation is one of the most efficient and effective solutions to address the large-volume-high-speed problem. In this thesis, we propose a dynamic representation scheme for streaming time series. Existing methods use a unitary function form for the entire approximation task. In contrast, our method adopts a set of function candidates such as linear function, polynomial function(degree ≥ 2), and exponential function. We provide a novel segmenting strategy to generate subsequences and dynamically choose candidate functions to approximate the subsequences.<br>Since we are dealing with streaming time series, the segmenting points and the corresponding approximate functions are incrementally produced. For a certain function form, we use a buffer window to find the local farthest possible segmenting point under a user specified error tolerance threshold. To achieve this goal, we define a feasible space for the coefficients of the function and show that we can indirectly find the local best segmenting point by the calculation in the coefficient space. Given the error tolerance threshold, the candidate function representing more information by unit parameter is chosen as the approximate function. Therefore, our representation scheme is more flexible and compact. We provide two dynamic algorithms, PLQS and PLQES, which involve two and three candidate functions, respectively. We also present the general strategy of function selection when more candidate functions are considered. In the experimental test, we examine the effectiveness of our algorithms with synthetic and real time series data sets. We compare our method with the piecewise linear approximation method and the experimental results demonstrate the evident superiority of our dynamic approach under the same error tolerance threshold.
APA, Harvard, Vancouver, ISO, and other styles
5

Jemwa, Gorden Takawadiyi. "Multivariate nonlinear time series analysis of dynamic process systems." Thesis, Stellenbosch : University of Stellenbosch, 2003. http://hdl.handle.net/10019.1/16339.

Full text
Abstract:
Thesis (MScIng)--University of Stellenbosch, 2003.<br>ENGLISH ABSTRACT: Physical systems encountered in process engineering are invariably ill-defined, multivariate, and exhibit complex nonlinear dynamical behaviour. The increasing demands for better process efficiency and high product quality have led to the development and implementation of advanced control strategies in process plants. These modern control strategies are based on the use of a mathematical model defined for the process. Traditionally, linear models have been used to approximate the dynamics of processes whereas most processes are governed by nonlinear mechanisms. Since linear systems theory is well-established whereas nonlinear systems theory is not, recent developments in nonlinear dynamical systems theory present opportunities for improved approaches in modelling these process systems. It is now known that a nonlinear description of a process can be obtained from using time-delayed copies reconstructed from measurements taken from the process. Due to low signal to noise ratios associated with measured data it is logical to exploit redundant information in multivariate time signals taken from the systems in reconstructing the underlying dynamics. This study investigated the extension of univariate nonlinear time series analysis to the situation where multivariate measurements are available. Using simulated data from a coupled continuously stirred tank reactor and measured data from a flotation process system, the comparative advantages of using multivariate and univariate state space reconstructions were investigated. With respect to detection of nonlinearity multivariate surrogate analysis were found to give potentially robust results because of preservation of cross-correlations among components in the surrogate data. Multivariate local linear models showed a deterministic structure in both small and large neighbourhood sizes whereas for scalar embeddings determinism was defined only in smaller neighbourhood sizes. Non-uniform multivariate embeddings gave local linear models that resembled models from a trivial reconstruction of the original state space variables. With regard to global nonlinear modelling, multivariate embeddings gave models with better predictability irrespective of the model class used. Further improvements in the performance of models were obtained for multivariate non-uniform embeddings. A relatively new statistical learning algorithm, the least-squares support vector machine (LSSVM), was evaluated using multilayer perceptrons (MLP) as a benchmark in modelling nonlinear time series using simulated and plant data. It was observed that in the absence of autocorrelations in the variables and sparse data LSSVMs performed better than MLPs. Simulation of trained models gave consistent results for the LSSVMs, which was not the case for MLPs. However, the computational costs incurred in training the LSSVM model was significantly higher than for MLPs. LSSVMs were found to be insensitive to dimensionality reduction methods whereas the performance of MLPs degraded with increasing complexity of the dimension reduction method. No relative merits were found for using complex subspace dimension reduction methods for the data used. No general conclusions could be drawn with respect to the relative superiority of one class of models method over the other. Spatiotemporal structures are routinely observed in many chemical systems, such as reactive-diffusion and other pattern forming systems. We investigated the modelling of spatiotemporal time series using the coupled logistic map lattice as a case study. It was found that including both spatial and temporal information improved the performance of the fitted models. However, the superiority of spatiotemporal embeddings over individual time series was found to be defined for certain choices of the spatial and temporal embedding parameters.<br>AFRIKAANSE OPSOMMING: Fisiese stelsels wat in prosesingenieurswese voorkom is dikwels nie goed gedefinieer nie, multiveranderlik en vertoon komplekse nie-lineˆere gedrag. Toenemende vereistes vir ho¨e prosesdoeltreffendheid en produkgehalte het gelei tot die ontwikkeling en implementering van gevorderde beheerstrategie¨e vir prosesaanlegte. Hierdie morderne beheerstrategie¨e is gebaseer op die gebruik van wiskundige prosesmodelle. Lineˆere modelle word gewoonlik ontwikkel, al is die onderliggende prosesmeganismes in die algemeen nie-lineˆere, aangesien lineˆere stetselteorie goed gevestig is, en nie-line¨ere stelselteorie nie. Onlangse verwikkelinge in die teorie van nie-lineˆeredinamiese stelsels bied egter geleenthede vir verbeterde modellering van prosesstelsels. Dit is bekend dat ‘n nie-lineˆere beskrywing van ‘n progses verkry kan word deur tydvertraagde kopie¨e van metings van die prosesse te rekonstrueer. Met die lae seintot- geraasverhoudings wat met gemete data geassosieer word, is dit logies om die oortollige informasie in meerveranderlike seine te benut tydens die rekonstruksie van die onderliggende prosesdinamika. In die tesis is die uitbreiding van enkel-veranderlike nie-lineˆere tydreeksontleding na meer-veranderlike stelsels ondersoek. Met data van twee aaneengeskakelde gesimuleerde geroerde tenkreaktore en werklike data van ‘n flottasieproses, is die meriete van enkel- en meerveranderlike rekonstruksies van toestandruimtes ondersoek. Meerveranderlike surrogaatdata-ontleding het nie-lineariteite in die data op ‘n meer robuuste wyse ge¨ıdentifiseer, a.g.v. die behoud van kruis-korrelasies in die komponente van die data. Meerveranderlike lokale lineˆere modelle het ‘n deterministiese struktuur in beide klein en groot naasliggende omgewings ge¨ıdentifiseer, terwyl enkelveranderlike metodes dit slegs vir klein naasliggende omgewings kon doen. Nie-uniforme meerveranderlike inbeddings het lokale lineˆere modelle gegenereer wat soos globale modelle afkomstig van triviale rekonstruksies van die data gelyk het. M.b.t globale nie-lineˆere modellering, het meerveranderlike inbedding deurgaans beter modelle opgelewer. Verdere verbetering in die prestasie van modelle kon verkry word d.m.v. meerveranderlike nie-uniforme inbedding. ‘n Relatief nuwe statistiese algoritme, die kleinste-kwadrate-steunvektormasjien (KKSVM) is ge¨evalueer teenoor multilaag-perseptrons (MLP) as ‘n standaard vir die modellering van nie-lineˆere tydreekse, deur gebruik te maak van gesimuleerde en werklike aanlegdata. Daar is gevind dat die KKSVM beter presteer het as die MLPs wanneer die opeenvolgende waarnemings swak gekorreleer en min was relatief tot die aantal veranderlikes. Die KKSVMs het beduidend langer geneem as die MLPs om te ontwikkel. Hulle was ook minder sensitief vir die metodes wat gevolg is om die dimensionaliteit van die data te verlaag, anders as die MLPs. Ook is gevind dat meer komplekse metodes tot die verlaging van die dimensionaliteit weinig nut gehad het. Geen algemene gevolgtrekkings kan egter gemaak word m.b.t die verskillende modelle nie. Ruimtelik-temporale strukture word algemeen waargeneem in baie chemiese stelsels, soos reaktiewe diffusie e.a. patroonvormende sisteme. Die modellering van ruimtelik-temporale stelsels is bestudeer aan die hand van ‘n gekoppelde logistiese projeksierooster. Insluiting van beide die ruimtelike en temporale inligting het tot beduidend beter modelle gelei, solank as wat di´e inligting op die regte wyse ontsluit is.
APA, Harvard, Vancouver, ISO, and other styles
6

Sümbül, Uygar. "Improved time series reconstruction for dynamic magnetic resonance imaging /." May be available electronically:, 2009. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Dahlberg, Love. "Dynamic algorithm selection for machine learning on time series." Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-72576.

Full text
Abstract:
We present a software that can dynamically determine what machine learning algorithm is best to use in a certain situation given predefined traits. The produced software uses ideal conditions to exemplify how such a solution could function. The software is designed to train a selection algorithm that can predict the behavior of the specified testing algorithms to derive which among them is the best. The software is used to summarize and evaluate a collection of selection algorithm predictions to determine  which testing algorithm was the best during that entire period. The goal of this project is to provide a prediction evaluation software solution can lead towards a realistic implementation.
APA, Harvard, Vancouver, ISO, and other styles
8

Lopez, Farias Rodrigo. "Time series forecasting based on classification of dynamic patterns." Thesis, IMT Alti Studi Lucca, 2015. http://e-theses.imtlucca.it/187/1/Farias_phdthesis.pdf.

Full text
Abstract:
This thesis addresses the problem of designing short-term forecasting models for water demand time series presenting nonlinear behaviour difficult to be fitted with single linear models. These behaviours can be identified and classified to build specialised models for performing local predictions given an estimated operational regime. Each behavior class is seen as a forecasting operation mode that activates a forecasting model. For this purpose we developed a general modular framework with three different implementations: An implementation of a Multi-Model predictor that works with Machine Learning regressors, clustering algorithms, classification, and function approximations with the objective of producing accurate forecasts for short horizons. The second and third implementations are hybrid algorithms that use qualitative and quantitative information from time series. The quantitative component contains the aggregated magnitude of each period of time and the qualitative component contains the patterns associated with modes. For the qualitative component we used a low order Seasonal ARIMA model and for the qualitative component a k-Nearest Neighbours that predicts the next pattern used to distribute the aggregated magnitude given by the Seasonal ARIMA. The third implementation is based on the same architecture, assuming the existence of an accurate activity calendar with a sequence of working and rest days, related to the forecast patterns. This scheme is extended with a nonlinear filter module for the prediction of pattern mismatches.
APA, Harvard, Vancouver, ISO, and other styles
9

Correia, Maria Inês Costa. "Cluster analysis of financial time series." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/21016.

Full text
Abstract:
Mestrado em Mathematical Finance<br>Esta dissertação aplica o método da Signature como medida de similaridade entre dois objetos de séries temporais usando as propriedades de ordem 2 da Signature e aplicando-as a um método de Clustering Asimétrico. O método é comparado com uma abordagem de Clustering mais tradicional, onde a similaridade é medida usando Dynamic Time Warping, desenvolvido para trabalhar com séries temporais. O intuito é considerar a abordagem tradicional como benchmark e compará-la ao método da Signature através do tempo de computação, desempenho e algumas aplicações. Estes métodos são aplicados num conjunto de dados de séries temporais financeiras de Fundos Mútuos do Luxemburgo. Após a revisão da literatura, apresentamos o método Dynamic Time Warping e o método da Signature. Prossegue-se com a explicação das abordagens de Clustering Tradicional, nomeadamente k-Means, e Clustering Espectral Assimétrico, nomeadamente k-Axes, desenvolvido por Atev (2011). O último capítulo é dedicado à Investigação Prática onde os métodos anteriores são aplicados ao conjunto de dados. Os resultados confirmam que o método da Signature têm efectivamente potencial para Machine Learning e previsão, como sugerido por Levin, Lyons and Ni (2013).<br>This thesis applies the Signature method as a measurement of similarities between two time-series objects, using the Signature properties of order 2, and its application to Asymmetric Spectral Clustering. The method is compared with a more Traditional Clustering approach where similarities are measured using Dynamic Time Warping, developed to work with time-series data. The intention for this is to consider the traditional approach as a benchmark and compare it to the Signature method through computation times, performance, and applications. These methods are applied to a financial time series data set of Mutual Exchange Funds from Luxembourg. After the literature review, we introduce the Dynamic Time Warping method and the Signature method. We continue with the explanation of Traditional Clustering approaches, namely k-Means, and Asymmetric Clustering techniques, namely the k-Axes algorithm, developed by Atev (2011). The last chapter is dedicated to Practical Research where the previous methods are applied to the data set. Results confirm that the Signature method has indeed potential for machine learning and prediction, as suggested by Levin, Lyons, and Ni (2013).<br>info:eu-repo/semantics/publishedVersion
APA, Harvard, Vancouver, ISO, and other styles
10

Rodrigues, Antonio Jose Lopes. "Dynamic regression and supervised learning methods in time series modelling and forecasting." Thesis, Lancaster University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364365.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Dynamic series"

1

Gourieroux, Christian. Time series and dynamic models. Cambridge University Press, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Gourieroux, Christian. Time series and dynamic models. Cambridge University Press, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

C, Spall James, ed. Bayesian analysis of time series and dynamic models. Dekker, 1988.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Barbosa, Emanuel Pimentel. Dynamic Bayesian models for vector time series analysis & forecasting. typescript, 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Vasfi, Gucer, and International Business Machines Corporation. International Technical Support Organization., eds. Deployment guide series. International Technical Support Organization, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Patterson, K. D. The interpretation of growth coefficients in dynamic time series models. [s.n.], 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Wang, Risheng. A phase-space approach to atmospheric dynamics based on observational data: Theory and applications. D. Reimer, 1994.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Brock, William A. A dynamic structural model for stock return volatility and trading volume. National Bureau of Economic Research, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Stock, James H. Implications of dynamic factor models for var analysis. National Bureau of Economic Research, 2005.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Stock, James H. Implications of dynamic factor models for VAR analysis. National Bureau of Economic Research, 2005.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Dynamic series"

1

Doyle, James F. "Dynamic Stability." In Mechanical Engineering Series. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3546-8_8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Chakrabarty, J. "Dynamic Plasticity." In Mechanical Engineering Series. Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4757-3268-9_8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Chakrabarty, J. "Dynamic Plasticity." In Mechanical Engineering Series. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-77674-3_8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Ingold, Lukas, and Fabio Tammaro. "Dynamic Skin." In RIEAeuropa Book-Series. Springer Vienna, 2010. http://dx.doi.org/10.1007/978-3-7091-0228-2_8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Delong, Łukasz. "Dynamic Risk Measures." In EAA Series. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5331-3_13.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Prado, Raquel, Marco A. R. Ferreira, and Mike West. "Dynamic linear models." In Time Series, 2nd ed. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781351259422-4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Miannay, Dominique P. "Dynamic Fracture: Elementary Dynamics and Microscopic Fracture." In Mechanical Engineering Series. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0155-4_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Gross, Dietmar, and Thomas Seelig. "Dynamic fracture mechanics." In Mechanical Engineering Series. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71090-7_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Genta, Giancarlo, and Lorenzo Morello. "Driving Dynamic Performance." In Mechanical Engineering Series. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35709-2_23.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Genta, Giancarlo, and Lorenzo Morello. "Braking Dynamic Performance." In Mechanical Engineering Series. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35709-2_24.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Dynamic series"

1

Jiang, Wenshu, Hang Liu, Zhenying Cheng, and Ruijun Li. "Dynamic uncertainty evaluation of dynamic time series based on mixture density network." In Eleventh International Symposium on Precision Mechanical Measurements, edited by Liandong Yu, Lianqing Zhu, Zai Luo, and Haojie Xia. SPIE, 2024. http://dx.doi.org/10.1117/12.3032442.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Dallachiesa, Lauren, Nicolas K. Fontaine, David T. Neilson, et al. "Multiport O-Band Dynamic Optical Filter." In 2024 IEEE Photonics Society Summer Topicals Meeting Series (SUM). IEEE, 2024. http://dx.doi.org/10.1109/sum60964.2024.10614496.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Song, Yifan, Yu Liu, and Shaolong Shu. "Dynamic Soft Contrastive Learning for Time Series Anomaly Detection." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10889377.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Younis, Raneen, and Zahra Ahmadi. "HyperTime: A Dynamic Hypergraph Approach for Time Series Classification." In 2024 IEEE International Conference on Data Mining (ICDM). IEEE, 2024. https://doi.org/10.1109/icdm59182.2024.00064.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Iosevich, S., G. Arutyunyants, and Z. Hou. "Dynamic aggregation for time series forecasting." In 2015 IEEE International Conference on Big Data (Big Data). IEEE, 2015. http://dx.doi.org/10.1109/bigdata.2015.7363996.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Nembhard, Harriet Black, and David A. Nembhard. "Dynamic simulation for time series modeling." In the 28th conference. ACM Press, 1996. http://dx.doi.org/10.1145/256562.256979.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Wang, Yibing, Sanghyun Cheon, and Qun Wang. "Time Series Analysis of Dynamic Networks." In 2012 5th International Symposium on Computational Intelligence and Design (ISCID). IEEE, 2012. http://dx.doi.org/10.1109/iscid.2012.131.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Chen, Huiling, Aosheng Tian, Ye Zhang, and Hanxin Zhao. "Dynamic Early Time Series Classification Network." In 2022 4th International Conference on Control and Robotics (ICCR). IEEE, 2022. http://dx.doi.org/10.1109/iccr55715.2022.10053847.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Naik, Nitin, Changjing Shang, Qiang Shen, and Paul Jenkins. "Vigilant Dynamic Honeypot Assisted by Dynamic Fuzzy Rule Interpolation." In 2018 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2018. http://dx.doi.org/10.1109/ssci.2018.8628775.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Liao, Fuyuan, and Jue Wang. "Symbolic Dynamic Analysis of Physiological Time Series." In 2008 International Symposium on Intelligent Information Technology Application Workshops (IITAW). IEEE, 2008. http://dx.doi.org/10.1109/iita.workshops.2008.197.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Dynamic series"

1

Ricca, Bernard. Nonlinear Time Series Analyses (Part II). Instats Inc., 2024. https://doi.org/10.61700/0emwhpkidie951390.

Full text
Abstract:
This four-day seminar delves into phenomenological modeling of time series, focusing on nonlinear dynamic methodologies such as sparse identification of nonlinear dynamics, dynamic mode decomposition, and hidden Markov models, all implemented using the R programming language. Participants will enhance their research skills by learning to dynamically model, analyze, and interpret time-dependent data, ultimately enabling them to conduct innovative and robust research across various fields.
APA, Harvard, Vancouver, ISO, and other styles
2

Schryver, J. C., and N. Rao. Classification of time series patterns from complex dynamic systems. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/663242.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Hall, Stephen. Time-Series Methods: Dynamic Modeling, Non-Stationarity, and Cointegration. Instats Inc., 2023. http://dx.doi.org/10.61700/vksf9usteps6f469.

Full text
Abstract:
This seminar provides a hands-on exploration of time-series methods useful for econometrics as well as social and health science research. Any modelling exercise involving time series data depends crucially on the correct treatment of any non-stationarity which may be present in the data. The seminar explores the developments in dynamic modelling and non-stationarity which have taken place over the last 50 years in Econometrics, including in-depth coverage types of non-stationarity and tests for them, including cointegrated relationships (shared trends) among multiple variables. A free version of the EViews software can be. An Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent points.
APA, Harvard, Vancouver, ISO, and other styles
4

Hall, Stephen. Time-Series Methods: Dynamic Modeling, Non-Stationarity, and Cointegration. Instats Inc., 2022. http://dx.doi.org/10.61700/nyrm5o8t47qqa469.

Full text
Abstract:
This seminar provides a hands-on exploration of time-series methods useful for econometrics as well as social and health science research. Any modelling exercise involving time series data depends crucially on the correct treatment of any non-stationarity which may be present in the data. The seminar explores the developments in dynamic modelling and non-stationarity which have taken place over the last 50 years in Econometrics, including in-depth coverage types of non-stationarity and tests for them, including cointegrated relationships (shared trends) among multiple variables. A free version of the EViews software can be [url=https://register1.eviews.com/demo/][u]downloaded here[/u][/url]. An Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent points.
APA, Harvard, Vancouver, ISO, and other styles
5

Muthen, Bengt. Using Mplus for Dynamic SEM (Free Seminar). Instats Inc., 2025. https://doi.org/10.61700/59kctofkmc82z1479.

Full text
Abstract:
This seminar provides an in-depth exploration of Dynamic Structural Equation Modeling (DSEM) using Mplus, allowing participants to understand and apply this advanced technique to analyze time series data and capture dynamic processes. Led by expert Bengt Muthen, the workshop equips researchers and PhD students with practical skills and theoretical knowledge essential for implementing complex dynamic models and enhancing their analytical capabilities in longitudinal research.
APA, Harvard, Vancouver, ISO, and other styles
6

Jääskeläinen, Emmihenna. Construction of reliable albedo time series. Finnish Meteorological Institute, 2023. http://dx.doi.org/10.35614/isbn.9789523361782.

Full text
Abstract:
A reliable satellite-based black-sky albedo time series is a crucial part of detecting changes in the climate. This thesis studies the solutions to several uncertainties impairing the quality of the black-sky albedo time series. These solutions include creating a long dynamic aerosol optical depth time series for enhancing the removal of atmospheric effects, a method to fill missing data to improve spatial and temporal coverage, and creating a function to correctly model the diurnal variation of melting snow albedo. Mathematical methods are the center pieces of the solutions found in this thesis. Creating a melting snow albedo function and the construction of an aerosol optical depth time series lean on a linear regression approach, whereas the process to fill missing values is based on gradient boosting, a machine learning method that is in turn based on decision trees. These methods reflect the basic nature of these problems as well as the need to take into account the large amounts of satellite-based data and computational resources available.
APA, Harvard, Vancouver, ISO, and other styles
7

Muthen, Bengt. Using Mplus for DSEM with Cycles (Free Seminar). Instats Inc., 2025. https://doi.org/10.61700/unxg7sciozj121479.

Full text
Abstract:
This seminar provides an in-depth exploration of Dynamic Structural Equation Modeling (DSEM) using Mplus, focusing on the analysis of cyclical patterns within time-series data across various research fields. Participants will gain comprehensive skills in model construction, data analysis, and application of advanced statistical techniques, enhancing their research capabilities in capturing complex data dynamics.
APA, Harvard, Vancouver, ISO, and other styles
8

Shen, Shiyu, Yuhui Zhai, and Yanfeng Ouyang. Planning and Dynamic Management of Autonomous Modular Mobility Services. Illinois Center for Transportation, 2024. https://doi.org/10.36501/0197-9191/24-029.

Full text
Abstract:
As we enter the next era of autonomous driving, robo-vehicles (which serve as low-cost and fully compliant drivers) are replacing conventional chauffeured services in the mobility market. During just the last few years, companies like Waymo Inc. and Cruise Inc. have already offered fully driverless robo-taxi services to the general public in cities like Phoenix and San Francisco. The rapid evolution of autonomous vehicles is anticipated to reshape the shared mobility market very soon. This project aims to address the following open questions. At the operational level, how should modular units be allocated across multiple categories of customers (e.g., passenger and freight cabins), and how should they be matched in real time? How do we enhance system efficiency by dynamic relocation and swap of modular chassis? At the strategic or tactical level, how should the rolling stock resources (modular chassis, passenger and freight cabins) be planned, and where shall chassis swapping sites be located? How could any potential transaction cost for a chassis swap, such as the time required for a modular chassis to be assembled with a customized cabin, affect the optimal strategy and system performance? How can customer priorities (e.g., passenger vs. freight) affect system performance, and how can service providers manage demand by specific pricing scheme or discriminative customer service strategies? We conducted the following research tasks: (i) analytically derived systems of implicit nonlinear equations in the closed form, including a set of differential equations, to analyze the modular autonomous mobility system and to estimate the expected system performance in the steady state; (ii) conducted a series of agent-based simulation experiments to verify the accuracy of the proposed analytical formulas and to demonstrate the effectiveness of the proposed modular chassis services; and (iii) designed policy instruments to enhance transportation system performance.
APA, Harvard, Vancouver, ISO, and other styles
9

Furnish, M. D. Using power series expansions of moduli to interpolate between release curves from dynamic tests: Technique and application. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/6805755.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Drouillard, Matthew, and Michael Lewis. Time-series reduction for dynamic vector model attribute representation in a geographic information system : exploration of procedure. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49418.

Full text
Abstract:
Spatiotemporal data, generally in the form of temporal rasters, can be used to analyze phenomena, such as weather patterns or other environ-mental conditions, that vary in time and space. However, spatially extensive datasets over large periods of time become cumbersome to visually represent and to analyze efficiently. In addition, the ability to compactly assign the information contained in the raster time series to overlain vector data model objects and to effectively visualize it is lacking. These two drawbacks can limit the ability to use such data in field-based applications, where nimble data size and computational efficiency may be paramount. This body of work pursues a method for efficiently reducing spatiotemporal data into aggregated yearly patterns for data reduction and puts forth a new concept of vector data model attribute representation called dynamic vector model attribute representation.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Dynamic series' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography