Relevant bibliographies by topics / Random parameters logit

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

Academic literature on the topic 'Random parameters logit'

Author: Grafiati
Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Random parameters logit"

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Zeng, Tong, and R. Carter Hill. "Shrinkage Estimation in the Random Parameters Logit Model." Open Journal of Statistics 06, no. 04 (2016): 667–74. http://dx.doi.org/10.4236/ojs.2016.64056.

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Bansal, Prateek, Ricardo A. Daziano, and Martin Achtnicht. "Extending the logit-mixed logit model for a combination of random and fixed parameters." Journal of Choice Modelling 27 (June 2018): 88–96. http://dx.doi.org/10.1016/j.jocm.2017.10.001.

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Wei, Fulu, Zhenggan Cai, Zhenyu Wang, Yongqing Guo, Xin Li, and Xiaoyan Wu. "Investigating Rural Single-Vehicle Crash Severity by Vehicle Types Using Full Bayesian Spatial Random Parameters Logit Model." Applied Sciences 11, no. 17 (August 25, 2021): 7819. http://dx.doi.org/10.3390/app11177819.

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The effect of risk factors on crash severity varies across vehicle types. The objective of this study was to explore the risk factors associated with the severity of rural single-vehicle (SV) crashes. Four vehicle types including passenger car, motorcycle, pickup, and truck were considered. To synthetically accommodate unobserved heterogeneity and spatial correlation in crash data, a novel Bayesian spatial random parameters logit (SRP-logit) model is proposed. Rural SV crash data in Shandong Province were extracted to calibrate the model. Three traditional logit approaches—multinomial logit model, random parameter logit model, and random intercept logit model—were also established and compared with the proposed model. The results indicated that the SRP-logit model exhibits the best fit performance compared with other models, highlighting that simultaneously accommodating unobserved heterogeneity and spatial correlation is a promising modeling approach. Further, there is a significant positive correlation between weekend, dark (without street lighting) conditions, and collision with fixed object and severe crashes and a significant negative correlation between collision with pedestrians and severe crashes. The findings can provide valuable information for policy makers to improve traffic safety performance in rural areas.
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Gong, Hongren, Ting Fu, Yiren Sun, Zhongyin Guo, Lin Cong, Wei Hu, and Ziwen Ling. "Two-vehicle driver-injury severity: A multivariate random parameters logit approach." Analytic Methods in Accident Research 33 (March 2022): 100190. http://dx.doi.org/10.1016/j.amar.2021.100190.

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Rusmevichientong, Paat, David Shmoys, Chaoxu Tong, and Huseyin Topaloglu. "Assortment Optimization under the Multinomial Logit Model with Random Choice Parameters." Production and Operations Management 23, no. 11 (March 13, 2014): 2023–39. http://dx.doi.org/10.1111/poms.12191.

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Jafari, Habib. "On Locally Optimal Criterion for a Logit Model with Random Parameters." Applied Mathematics & Information Sciences 7, no. 2L (June 1, 2013): 723–28. http://dx.doi.org/10.12785/amis/072l50.

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MCCONNELL, KENNETH E., and WEI-CHUN TSENG. "Some Preliminary Evidence on Sampling of Alternatives with the Random Parameters Logit." Marine Resource Economics 14, no. 4 (December 1999): 317–32. http://dx.doi.org/10.1086/mre.14.4.42629276.

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Coppola, Pierluigi, Luigi dell’Olio, and Fulvio Silvestri. "Random-Parameters Behavioral Models to Investigate Determinants of Perceived Safety in Railway Stations." Journal of Advanced Transportation 2021 (August 24, 2021): 1–11. http://dx.doi.org/10.1155/2021/5530591.

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Recent studies have highlighted the existence of a gap between actual and perceived safety and have shown that feelings of insecurity can affect individuals’ travel behavior before and during the journey. In this paper, a methodology is proposed for assessing determinants of travelers’ perception of safety and security in railway stations. The methodological approach includes focus groups, stated preference (SP) surveys, and the estimation of behavioral models with fixed parameters (Binomial Logit) and random parameters (Mixed Logit). The estimation results for a medium-sized railway station (Frosinone, Italy) confirmed that safety and security measures are not equally perceived by individuals and the use of random-parameters models leads to more robust estimates. The proposed modeling approach allows the identification of the interventions that should be prioritized to increase travelers’ perceived levels of safety, highlighting those factors, such as, for the considered case study, the presence of security personnel and the level of decorum and maintenance, which are perceived by users as more important than others (e.g., surveillance cameras).
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Camarena, Dena M., and Ana I. Sanjuán. "Heterogeneidad de preferencias y experimentos de elección: Aplicación de un logit con parámetros aleatorios a la demanda de nueces." Economía Agraria y Recursos Naturales 4, no. 8 (October 21, 2011): 105. http://dx.doi.org/10.7201/earn.2004.08.06.

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Consumers’ stated preferences towards walnuts are studied by means of a choice experiment, with a double objective: first, to identify the main attributes searched by consumer at purchase and second, to analyse the chances for the introduction into the Spanish market of the Pecan variety. From this study, commercial guidelines may be derived, that helps distribution and import companies to commercialise this nut. A mixed or random parameters logit is estimated which relaxes the IIA property (independence of irrelevant alternatives) present in the logit model with fixed parameters. In a mixed logit, coefficients of each attribute/level vary randomly across consumers, reflecting the heterogeneity of individuals’ preferences. This model also allows estimate efficiently the parameters when each individual chooses several times, as in the present study.
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Adanu, Emmanuel Kofi, and Steven Jones. "Effects of Human-Centered Factors on Crash Injury Severities." Journal of Advanced Transportation 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/1208170.

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Factors related to drivers and their driving habits dominate the causation of traffic crashes. An in-depth understanding of the human factors that influence risky driving could be of particular importance to facilitate the application of effective countermeasures. This paper sought to investigate effects of human-centered crash contributing factors on crash outcomes. To select the methodology that best accounts for unobserved heterogeneity between crash outcomes, latent class (LC) logit model and random parameters logit (RPL) model were developed. Model estimation results generally show that serious injury crashes were more likely to involve unemployed drivers, no seatbelt use, old drivers, fatigued driving, and drivers with no valid license. Comparison of model fit statistics shows that the LC logit model outperformed the RPL model, as an alternative to the traditional multinomial logit (MNL) model.
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Dissertations / Theses on the topic "Random parameters logit"

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Raharjo, Tatok Raharjo. "The Effects of Age and Gender on Pedestrian Traffic Injuries: A Random Parameters and Latent Class Analysis." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6360.

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Pedestrians are vulnerable road users because they do not have any protection while they walk. They are unlike cyclists and motorcyclists who often have at least helmet protection and sometimes additional body protection (in the case of motorcyclists with body-armored jackets and pants). In the US, pedestrian fatalities are increasing and becoming an ever larger proportion of overall roadway fatalities (NHTSA, 2016), thus underscoring the need to study factors that influence pedestrian-injury severity and potentially develop appropriate countermeasures. One of the critical elements in the study of pedestrian-injury severities is to understand how injuries vary across age and gender ‒ two elements that have been shown to be critical injury determinants in past research. In the current research effort, 4829 police-reported pedestrian crashes from Chicago in 2011 and 2012 are used to estimate multinomial logit, mixed logit, and latent class logit models to study the effects of age and gender on resulting injury severities in pedestrian crashes. The results from these model estimations show that the injury severity level for older males, younger males, older females, and younger females are statistically different. Moreover, the overall findings also show that older males and older females are more likely to have higher injury-severity levels in many instances (if a crash occurs on city streets, state maintained urban roads, the primary cause of the crash is failing to yield right-of way, pedestrian entering/ leaving/ crossing is not at intersection, road surface condition is dry, and road functional class is a local road or street). The findings suggest that well-designed and well-placed crosswalks, small islands in two-way streets, narrow streets, clear road signs, provisions for resting places, and wide, flat sidewalks all have the potential to result in lower pedestrian-injury severities across age/gender combinations.
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Bienenfeld, Jason Michael. "Consumer Willingness to Pay for Organic, Environmental and Country of Origin Attributes of Food Products." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1396017355.

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Nowotny, Klaus, and Dieter Pennerstorfer. "Network migration: do neighbouring regions matter?" Routledge by Taylor & Francis Group, 2019. http://dx.doi.org/10.1080/00343404.2017.1380305.

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This paper analyses the role of the spatial structure of migrant networks in the location decision of migrants to the European Union at the regional level. Using a random parameters logit specification, a significant positive effect of migrant networks in neighbouring regions on migrants' location decisions is found. Although this spatial spillover effect is smaller than the effect of networks in the host regions, omitting to control for this spatial dependence results in a 40% overestimation of the effect of regional migrant networks on the location decision of newly arriving migrants.
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Rusli, Rusdi Bin. "Traffic safety along rural mountainous highways in Malaysia." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/113718/2/Rusdi_Bin_Rusli_Thesis.pdf.

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This research has generated an in-depth understanding of road traffic crashes along rural mountainous highways in Sabah, Malaysia that will enable development of targeted countermeasures. To achieve this, an extensive set of road traffic data was collected through field surveys and secondary sources, and a set of cutting-edge statistical and economic models were developed to investigate (i) single-vehicle crashes, (ii) multi-vehicle crashes, and (iii) injury severity of traffic crashes along rural mountainous highways. Findings from this research will contribute to the design of a safer environment along rural mountainous highways, which are common in many developing countries.
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Ndunda, E. N. (Ezekiel Nthee). "Wastewater reuse in urban and peri-urban irrigation : an economic assessment of improved wastewater treatment, low-risk adaptations and risk awareness in Nairobi, Kenya." Thesis, University of Pretoria, 2013. http://hdl.handle.net/2263/40235.

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The overall goal of this study was to analyse the welfare effect of improved wastewater treatment with the view of making policy recommendations for sustainable urban and peri-urban irrigation agriculture in Kenya. This goal was achieved by investigating three specific objectives. The first objective was to assess the farmers’ awareness of health risks in urban and peri-urban wastewater irrigation. Second objective was to analyse the factors that affect the choice of low-risk adaptations in reuse of untreated wastewater for irrigation. The third objective was to estimate the value that urban and peri-urban farmers who practice wastewater irrigation impute to improvements in specific characteristics of the wastewater input in agriculture. In order to achieve the first objective, an ordered probit model was used to identify the factors that influence farmers’ awareness of health risks in untreated wastewater irrigation. The model was fitted to data collected from a cross-sectional survey of 317 urban farm households in the Kibera informal settlement of Kenya. Results of this study show that gender of household head, household size, education level of household head, farm size, ownership of the farm, membership to farmers’ group, and market access for the fresh produce significantly affect awareness of farmers about health risks in wastewater irrigation. Therefore, there is need for awareness programs to promote public education through regular training and local workshops on wastewater reuse in order to improve the human capital of the urban and peri-urban farmers. To achieve the second objective, the study used a multinomial logit model to analyse the farmers’ choice of low-risk adaptations in untreated wastewater irrigation. A survey of 317 urban and peri-urban farmers was conducted and measures for risk-reduction in wastewater reuse were analysed. The urban and peri-urban farmers were found to have adopted low-risk wastewater irrigation techniques such as cessation of irrigation before harvesting, crop restriction and safer application methods. Results of the study show that adoption of risk-reduction measures is significantly influenced by the following factors: household size, age of the household head, education of household head, access to extension, access to media, access to credit, farmers’ group membership, and risk awareness. Also, marginal analysis of the coefficients confirmed the socio-economic characteristics are key determinants in adoption of low-risk measures in wastewater reuse. The study recommends that policies in support of low-risk urban and peri-urban irrigation agriculture should disaggregate farmers according to their socio-economic and institutional characteristics in order to achieve their intended objectives. To achieve the third objective, the study employed the discrete choice experiment approach to estimate the benefits farmers impute to improvements in attributes of the wastewater irrigation input, whose aim is to reduce the health risks associated with untreated wastewater irrigation. Urban and peri-urban farmers who practice wastewater irrigation drawn from Motoine-Ngong River in Nairobi were randomly selected for the study. A total of 241 farmers completed the presented choice cards for the choice model estimation. A random parameter logit model was used to estimate the individual level willingness to pay for wastewater treatment. The results show that urban and peri-urban farmers are willing to pay significant monthly municipality taxes for treatment of wastewater. Conclusion of this study was that, quality of treated wastewater, quantity of treated wastewater and the riverine ecosystem restoration are significant factors of preference over policy alternative designs in wastewater treatment and reuse.
Thesis (PhD)--University of Pretoria, 2013.
gm2014
Agricultural Economics, Extension and Rural Development
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Skahan, Denise A. "Consumer Willingness to Pay for E85." 2010. http://trace.tennessee.edu/utk_gradthes/749.

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Concerns regarding energy security, resource sustainability, and environmental protection have heightened interests in renewable fuels and sparked the research and development of ethanol as a transportation fuel. This study examines consumers’ willingness to pay for ethanol from various potential feedstocks; corn, switchgrass and wood wastes. Data was collected via a survey of fuel consumers across the United States in 2009. Results show that consumers have a preference for E85 (a fuel blend with 85 percent ethanol and 15 percent gasoline) from corn, switchgrass and wood wastes compared to E0 (gasoline) and a preference for E85 from switchgrass and wood wastes, but not corn when compared to E10 (10 percent ethanol and 90 percent gasoline). Also, consumers have a preference for E85 compared to E10 but not compared to E0. Mean WTP for E85 was insignificant across all models, but significant for all other product attributes; percentage of fuel imported, percentage of greenhouse gas emissions reduced, and the proximity of fuel in driving distance. This suggests a WTP for a combination of fuel attributes associated with ethanol rather than just for E85. Results suggest that price and proximity of the fuel have a greater impact on fuel selection than percentage of the fuel imported and reductions in greenhouse gas emissions. Republicans had a positive WTP for E85 compared to E10 and a negative WTP for E85 compared to E0 regardless of feedstock, which may suggest that Republicans actually have no preference for E85; however, these findings may also suggest that Republicans view E85 as a voluntary “policy” whereas E10 is an example of government intrusion in the free market. Thus, they may ultimately have preferences over the manner in which the blend is being introduced to the market. Across all models, those undecided in political affiliation, those previously familiar with ethanol, and those who prefer to devote U.S. farmland to food instead of fuel generally exhibited a lower WTP for E85 while Westerners, those worried about the environment, and those believe that reducing dependence on foreign oil is more important than environmental protection generally had a greater WTP for E85.
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(6992318), Tariq Usman Saeed. "Road Infrastructure Readiness for Autonomous Vehicles." Thesis, 2019.

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Contemporary research indicates that the era of autonomous vehicles (AVs) is not only inevitable but may be reached sooner than expected; however, not enough research has been done to address road infrastructure readiness for supporting AV operations. Highway agencies at all levels of governments seek to identify the needed infrastructure changes to facilitate the successful integration of AVs into the existing roadway system. Given multiple sources of uncertainty particularly the market penetration of AVs, agencies find it difficult to justify the substantial investments needed to make these infrastructure changes using traditional value engineering approaches. It is needed to account for these uncertainties by doing a phased retrofitting of road infrastructure to keep up with the AV market penetration. This way, the agency can expand, defer, or scale back the investments at a future time. This dissertation develops a real options analysis (ROA) framework to address these issues while capturing the monetary value of investment timing flexibility. Using key stakeholder feedback, an extensive literature review, and discussions with experts, the needed AV-motivated changes in road infrastructure were identified across two stages of AV operations; the transition phase and the fully-autonomous phase. For a project-level case study of a 66-mile stretch of Indiana’s four-six lane Interstate corridor, two potential scenarios of infrastructure retrofitting were established and evaluated using the net present value (NPV) and ROA approaches. The results show that the NPV approach can lead to decisions at the start of the evaluation period but does not address the uncertainty associated with AV market penetration. In contrast, ROA was found to address uncertainty by incorporating investment timing flexibility and capturing its monetary value. Using the dissertation’s framework, agencies can identify and analyze a wide range of possible scenarios of AV-oriented infrastructure retrofitting to enhance readiness, at both the project and network levels.
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"An Assessment of Consumers’ Willingness to Pay for Attributes of Milk and Dairy Products with the 100% Canadian Milk Symbo." Thesis, 2013. http://hdl.handle.net/10388/ETD-2013-07-1124.

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Consumers are becoming increasingly concerned about their foods and more particularly, the origin of their foods and the ingredients they contain. In light of the demand for additional origin information, the 100% Canadian milk branding initiative was launched in 2009 as a means of informing consumers about the origin of milk in their dairy products. The information is indicated by the presence of the 100% Canadian milk symbol on dairy products and can be characterized a form of co-branding. The literature on co-branding stipulates that co-branding can result in changed product perceptions either negatively or positively. In addition, the willingness to pay (WTP) literature stipulates that WTP is determined by product attributes and individuals’ characteristics. This thesis therefore seeks to ascertain the factors affecting consumers’ preferences and WTP for products with the 100% Canadian milk symbol. Specifically, the effects of individual characteristics such as health consciousness, patriotic values and risk perceptions on preferences for dairy products with the symbol are evaluated. Concurrently, the study explores the relationship between respondents’ knowledge of the Canadian dairy industry and WTP for the symbol. Data were gathered from a total of 1012 milk and ice cream consumers using two nationwide internet surveys. Estimations are carried out using the Multinomial Logit (MNL) and the Random Parameter Logit models (RPL). The results suggest that consumers in general have positive perceptions of milk and ice cream with the 100% Canadian milk symbol but negatively perceive store brand and organic labels. However, in some cases, combining a store brand label or organic label with the 100% Canadian milk symbol, are shown to alter consumers’ perceptions of the product. Some socio-demographic variables and individual characteristics were also found to be influential in intended purchase behaviours and WTP for milk and ice cream. The findings from this study provide information on consumers’ perceptions and attribute preferences and are expected therefore to contribute to the marketing strategies of the Canadian dairy industry as a whole.
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Books on the topic "Random parameters logit"

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Hynes, Stephen. Analysing preference heterogeneity using random parameter logit and latent class modelling techniques. Galway: Department of Economics, National University of Ireland, Galway, 2005.

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Book chapters on the topic "Random parameters logit"

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Mariel, Petr, David Hoyos, Jürgen Meyerhoff, Mikolaj Czajkowski, Thijs Dekker, Klaus Glenk, Jette Bredahl Jacobsen, et al. "Econometric Modelling: Basics." In Environmental Valuation with Discrete Choice Experiments, 61–81. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62669-3_5.

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AbstractThis chapter addresses basic topics related to choice data analysis. It starts by describing the coding of attribute levels and choosing the functional form of the attributes in the utility function. Next, it focuses on econometric models with special attention devoted to the random parameter mixed logit model. In this context, the chapter compares different coefficient distributions to be used, addresses specifics of the cost attribute coefficient and it pays attention to potential correlations between random coefficients. Finally, topics related to the estimation procedure such as assuring its convergence or random draws are discussed.
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Zeng, Tong, and R. Carter Hill. "Pretest Estimation in the Random Parameters Logit Model." In Maximum Simulated Likelihood Methods and Applications, 107–36. Emerald Group Publishing Limited, 2010. http://dx.doi.org/10.1108/s0731-9053(2010)0000026008.

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Diligenti, Michelangelo, Francesco Giannini, Marco Gori, Marco Maggini, and Giuseppe Marra. "Chapter 8. A Constraint-Based Approach to Learning and Reasoning." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210355.

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Neural-symbolic models bridge the gap between sub-symbolic and symbolic approaches, both of which have significant limitations. Sub-symbolic approaches, like neural networks, require a large amount of labeled data to be successful, whereas symbolic approaches, like logic reasoners, require a small amount of prior domain knowledge but do not easily scale to large collections of data. This chapter presents a general approach to integrate learning and reasoning that is based on the translation of the available prior knowledge into an undirected graphical model. Potentials on the graphical model are designed to accommodate dependencies among random variables by means of a set of trainable functions, like those computed by neural networks. The resulting neural-symbolic framework can effectively leverage the training data, when available, while exploiting high-level logic reasoning in a certain domain of discourse. Although exact inference is intractable within this model, different tractable models can be derived by making different assumptions. In particular, three models are presented in this chapter: Semantic-Based Regularization, Deep Logic Models and Relational Neural Machines. Semantic-Based Regularization is a scalable neural-symbolic model, that does not adapt the parameters of the reasoner, under the assumption that the provided prior knowledge is correct and must be exactly satisfied. Deep Logic Models preserve the scalability of Semantic-Based Regularization, while providing a flexible exploitation of logic knowledge by co-training the parameters of the reasoner during the learning procedure. Finally, Relational Neural Machines provide the fundamental advantages of perfectly replicating the effectiveness of training from supervised data of standard deep architectures, and of preserving the same generality and expressive power of Markov Logic Networks, when considering pure reasoning on symbolic data. The bonding between learning and reasoning is very general as any (deep) learner can be adopted, and any output structure expressed via First-Order Logic can be integrated. However, exact inference within a Relational Neural Machine is still intractable, and different factorizations are discussed to increase the scalability of the approach.
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Singh, Balvender, and Shree Krishan Bishnoi. "An Application of ANFIS-PID Controller for Multi Area Hybrid Power System." In Artificial Intelligence and Communication Technologies, 613–27. 2022nd ed. Soft Computing Research Society, 2022. http://dx.doi.org/10.52458/978-81-955020-5-9-59.

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In this work adaptive fuzzy- PID (ANFIS-PID) controller is presented for frequency and tie-line regulation of multi-area interconnected power systems (IPS). The proposed controller has the properties of both neural network and fuzzy logic. A novel four area power system comprises two reheat turbines (area1 and area2), one hydropower plant (area 3) with the hydraulic governor and one wind plant (area 4) with a pitch actuator. This hybrid interconnected power system model has been built in MATLAB/ Simulink version 2020(a) and the proposed controller is employed with the same design of ANFIS model in all areas. Further, the performance of power system model is presented with the suggested controller. The step load change is considered in each area. An HVDC lines are considered in each area to improve the performance of the proposed model. Further, a fair comparison is made for the conventional PID and Fuzzy-PID controllers. The designed controller performs best compared to the other compared controller for tie-line power and frequency regulation in all four areas of the IPS. The dynamic response of the proposed model improves with AC/DC line as compared to AC line. The sensitivity analysis with change in plant parameters, step load perturbation (SLP) and random load change is also being applied to check the robustness of the controller.
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Conference papers on the topic "Random parameters logit"

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Hou, Qinzhong, Songcheng Mu, and Mengzhu Zhang. "Marginal Effects for Random Parameters Logit Models: A Case Study of Crash Severity Analysis." In 22nd COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2022. http://dx.doi.org/10.1061/9780784484265.167.

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Echaniz Beneitez, Eneko, Luigi Dell'Olio, and Angel Ibeas Portilla. "MODELLING PERCEIVED QUALITY FOR URBAN TRANSPORT SYSTEMS USING WEIGHTED VARIABLES AND RANDOM PARAMETERS." In CIT2016. Congreso de Ingeniería del Transporte. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.4072.

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In this article, an Ordered Logit model is proposed considering systematic and random variations in tastes. The methodology followed for the creation of this model consisted, in first place, in obtaining data using a revelled preferences survey. In the survey, each user had to evaluate, following a qualitative scale, each one of the attributes of the analysed transport system. The variables evaluated in the survey had been grouped into six groups, and for each group, users had to order the attributes belonging to the group, using a ranking based method, from the most important to de least important, and, in the same way, with the groups itself. Once the database is formed, a generic model have been created, establishing this model as a comparative base for the rest. Next, two more models have been estimated one considering systematic users variations and the other one combining the systematic variations with weighted variables. Additionally, three new models have been calculated as an evolution of the previous ones using random variables as representation of systematic and random variations in user’s tastes. The results shows that as model’s complexity increase, an improvement in model fit is achieved.DOI: http://dx.doi.org/10.4995/CIT2016.2016.4072
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Valencia-Romero, Ambrosio, and José E. Lugo. "Quantification of Symmetry, Parallelism, and Continuity as Continuous Design Variables for Three-Dimensional Product Representations." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59707.

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This work introduces a methodology to quantify the form of a three-dimensional (3D) product representation using the Gestalt principles of symmetry, parallelism, and continuity, and how they can be used as descriptive parameters in product design. First, consistent quantifications of these three Gestalt principles for parametrized 3D representations in a zero-one scale are presented. Then, a generalized methodology applicable to any product form is discussed. It starts with the identification of important aesthetic forms of the product shape and the Gestalt principles that best related to those forms, and ends with the quantification of these Gestalt principles of a 3D product representation. The expressions to quantify the Gestalt principles in question are validated through an online survey in which subjects indicated how much they recognize symmetry, parallelism, or continuity from irregular shapes. Finally, random-effects ordered logit regression is used to determine if the expressions effectively describe the level of recognition of each Gestalt principle. Results show that the proposed quantifications for symmetry, parallelism, and continuity are congruent with subjects perception of these Gestalt principles, and the implications for designers and future work are discussed. Further implications in the design process of these quantifications include the optimization of the product shape for aesthetic, semantic, and functional goals.
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Ali Rabbani, Muhammad Babar, Umar Usama, Muhammad Ali Musarat, and Wesam Salah Alaloul. "Indicators of injury severity of truck crashes using random parameter logit modeling." In 2021 International Conference on Decision Aid Sciences and Application (DASA). IEEE, 2021. http://dx.doi.org/10.1109/dasa53625.2021.9682328.

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Martis, Dan. "Fuzzy Logic Estimation Applied to Newton Methods for Gas Turbines." In ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-53978.

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This method, based on fuzzy logic principles, is intended to find the most likely solution of an over-determined system, in specific conditions. The method addresses typical problems encountered in gas turbine performance analysis and, more specifically, to the alignment of a synthesis model with measured data. Generally speaking, the relatively low accuracy of measurements introduces a random noise around the true value of a performance parameter and distorts any deteministic solution of a square matrix-based linear system. The Fuzzy Logic Estimator (FLE) is able to get very close to the real solution by using additional (pseudoredundant) parameters and by building the most likely solution based on each of the measurement accuracies. The accuracy — or “quality” — of a measurement is encapsulated within an extra dimension which is defined as fuzzy and which encompasses the whole range of values, between 0 (false) and 1 (true). The value of the method is shown in two examples. The first simulates compressor fouling, the other deals with actual engine test data following a hardware modification. Both examples experience noisy measurements. The method is stable and effective even at high level of noise. The results are within the close vicinity of the expected levels (within 0.2% accuracy) and the accuracy is about ten times lower than the noise level.
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Anwar, A. H. M., K. Tieu, P. Gibson, K. T. Win, and M. J. Berryman. "Agency in Transport Service: Implications of Traveller Mode Choice Objective and Latent Attributes Using Ransom Parameter Logit Model." In International Symposium for Next Generation Infrastructure. University of Wollongong, SMART Infrastructure Facility, 2014. http://dx.doi.org/10.14453/isngi2013.proc.54.

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Ali Adem, Mohammed. "Energy Optimization of Wireless Sensor Network Using Neuro-Fuzzy Algorithms." In LatinX in AI at Neural Information Processing Systems Conference 2019. Journal of LatinX in AI Research, 2019. http://dx.doi.org/10.52591/lxai2019120814.

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Wireless sensor network (WSN) is one of the recent technologies in communication and engineering world to assist various civilian and military applications. They are deployed remotely in sever environment which doesn’t have an infrastructure. Energy is a limited resource that needs efficient management to work without any failure. Energy efficient clustering of WSN is the ultimate mechanism to conserve energy for longtime. The major objective of this research is to efficiently consume energy based on the Neuro-Fuzzy approach particularly adaptive Neuro fuzzy inference system (ANFIS). The significance of this study is to examine the challenges of energy efficient algorithms and the network lifetime on WSN so that they can assist several applications. Clustering is one of the hierarchical based routing protocols, which manage the communication between sensor nodes and sink via Cluster Head (CH), CH is responsible to send and receive information from multiple sensor nodes and multiple base stations (BS). There are various algorithms that can efficiently select appropriate CH and localize the membership of cluster with fuzzy logic classification parameters to minimize periodic clustering which consumes more energy and we have applied neural network learning algorithm to learn various patterns based on the fuzzy rules and measured how much energy has saved from random clustering. Finally, we have compared to our Neuro-Fuzzy logic and consequently demonstrated that our Neuro-Fuzzy model outperforms than random model.
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8

Barbaro, Giuseppe, Giandomenico Foti, and Giovanni Malara. "Set-Up due to Random Waves: Influence of the Directional Spectrum." In ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-49977.

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This paper deals with the estimation of set-up due to irregular waves. Following the logic of Barbaro and Martino [1], it is derived the analytical expression of the set-up. The solution is based on the hypotheses of straight, parallel depth contours and constant average flow parameters in the longshore direction. In this context, the corresponding value of the set-up is calculated from a specified off-shore directional spectrum. The effect of the assumed directional spectrum is investigated. In particular, set-up is estimated by considering the following frequency spectra: Pierson-Moskowitz [2], JONSWAP [3] and Ochi-Hubble [4]. Further, influence of the spreading function is investigated by assuming a cosine-power [5] and a hyperbolic spreading function [6]. It is shown that the assumed off-shore spectrum significantly modifies the estimated set-up. It is proposed a practical application. The estimation has been carried out by considering various Italian and American locations. The model is applied from buoy data, that are provided by ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale) and by NDBC (National Data Buoy Center).
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Więcek, Paweł. "Intelligent Approach to Inventory Control in Logistics under Uncertainty Conditions." In CIT2016. Congreso de Ingeniería del Transporte. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.3508.

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The article presents a proposal for a combined application of fuzzy logic and genetic algorithms to control the procurement process in the enterprise. The approach presented in this paper draws particular attention to the impact of external random factors in the form of demand and lead time uncertainty. The model uses time-variable membership function parameters in a dynamic fashion to describe the modelled output fuzzy (sets) values. An additional element is the use of genetic algorithms for optimisation of fuzzy rule base in the proposed method. The approach presented in this paper was veryfied according to four criteria based on a computer simulation performed on the basis of the actual data from an enterprise.DOI: http://dx.doi.org/10.4995/CIT2016.2016.3508
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Hodkhasa, Sandip, and Huiping Guo. "Forward Chaining and Self-Embedding Watermarking for Tamper Detection in a Continuous Stream of Data." In 8th International Conference on Artificial Intelligence and Fuzzy Logic System (AIFZ 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.121612.

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Watermarking is extensively used in various media for data transfer, content authentication and integrity. The continuous flow of data is always vulnerable to tamper. This research proposes a new watermarking scheme that detects tampering in a stream of data. The stream of data is dynamically divided into different sized groups using synchronization points. A computed watermark is embedded in each group by hashing the concatenating the current group and the next group. A secondary watermark is generated based on the current group that prevents tampering from any attacks in the current group. Watermark verification table is used to determine all possible scenarios for false results. Experiments are performed to show its efficiency. False results decrease as the group size becomes larger. Random burst attacked requires larger group size. The scheme also shows with the increase in grouping parameter ‘m’ which defines the synchronization point, the false positive rate decreases.
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Reports on the topic "Random parameters logit"

1

Nesheim, Lars, and Joel L. Horowitz. Using penalized likelihood to select parameters in a random coefficients multinomial logit model. The IFS, October 2019. http://dx.doi.org/10.1920/wp.cem.2019.5019.

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2

Nesheim, Lars, and Joel L. Horowitz. Using penalized likelihood to select parameters in a random coefficients multinomial logit model. The IFS, April 2018. http://dx.doi.org/10.1920/wp.cem.2018.2918.

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