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Artificial Intelligence Techniques for Predicting Individuals’ Mode Choice Behavior in Mansoura City, Egypt
16 references·5 citing·38 second hop
Artificial Intelligence Techniques for Predicting Individuals’ Mode Choice Behavior in Mansoura City, Egypt (2023)Artificial Intelligence Techniques for Pr…Machine Learning Travel Mode Choices: Comparing the Performance of an Extreme Gradient Boosting Model with a Multinomial Logit Model (2018)Machine Learning Travel Mode …Applying a random forest method approach to model travel mode choice behavior (2018)Applying a random forest meth…A comparative study of machine learning classifiers for modeling travel mode choice (2017)A comparative study of machin…Mode Choice Analysis Using Random Forrest Decision Trees (2016)Mode Choice Analysis Using Ra…Predicting Travel Mode of Individuals by Machine Learning (2015)Predicting Travel Mode of Ind…Deep learning applications and challenges in big data analytics (2015)Deep learning applications an…Modelling Transport (2011)Modelling TransportTravel Mode Choice Modeling with Support Vector Machines (2008)Travel Mode Choice Modeling w…Testing for IIA in the Multinomial Logit Model (2007)Testing for IIA in the Multin…Multilayer feedforward networks for transportation mode choice analysis: An analysis and a comparison with random utility models (2005)Multilayer feedforward networ…Work Travel Mode Choice Modeling with Data Mining: Decision Trees and Neural Networks (2003)Work Travel Mode Choice Model…Random utility models with implicit availability/perception of choice alternatives for the simulation of travel demand (2001)Random utility models with im…A comparison of the predictive potential of artificial neural networks and nested logit models for commuter mode choice (2000)A comparison of the predictiv…Alternative nested logit models: structure, properties and estimation (1998)Alternative nested logit mode…Discrete choice analysis: Theory and application to travel demand (1988)Discrete choice analysis: The…Specification Tests for the Multinomial Logit Model (1984)Specification Tests for the M…Machine learning in travel mode choice studies: A systematic literature review of applications, methods, and challenges (2025)Machine learning in travel mo…Application of Artificial Neural Networks (ANN) in Investigating Travel Mode Choice: A Case Study of Langsa-Penang Passenger Ferry (2025)Application of Artificial Neu…Analyzing High-Speed Rail’s Transformative Impact on Public Transport in Thailand Using Machine Learning (2025)Analyzing High-Speed Rail’s T…Sensitivity evaluation of machine learning-based calibrated transportation mode choice models: A case study of Alexandria City, Egypt (2024)Sensitivity evaluation of mac…A machine learning comparison of transportation mode changes from high-speed railway promotion in Thailand (2024)A machine learning comparison…The structure of random utility models (1977)A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration (1989)Fuzzy Set Theory and Its Applications (1993)Discrete Choice Models with Applications to Departure Time and Route Choice (2006)On Modelling Route Choice Sets in Transportation Networks: A Synthesis (2008)The constrained multinomial logit: A semi-compensatory choice model (2008)Conditional logit analysis of qualitative choice behavior (1972)Specification Tests in Econometrics (1978)Discrete Choice Methods with Simulation (2001)The Social Attachment to Place (2010)Returning to Dakar: A Mixed Methods Analysis of the Role of Migration Experience for Occupational Status (2012)Natural disasters' impact, factors of resilience and development: A meta-analysis of the macroeconomic literature (2014)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Travel and the Built Environment (2010)Is your dataset big enough? Sample size requirements when using artificial neural networks for discrete choice analysis (2018)Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models (2020)Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach (2021)On the measurement of inequality (1970)Built environments and mode choice: toward a normative framework (2002)The effects of attitudes and personality traits on mode choice (2005)Examining non-linear built environment effects on elderly’s walking: A random forest approach (2020)To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults (2021)Agglomeration benefits and location choice: Evidence from Japanese manufacturing investments in the United States (1995)Measuring Market Power in the Ready-to-Eat Cereal Industry (1998)Economic Choices (2001)Comparison of Four Types of Artificial Neural Network and a Multinomial Logit Model for Travel Mode Choice Modeling (2018)A systematic review of machine learning classification methodologies for modelling passenger mode choice (2020)Big Data technologies: A survey (2017)Machine learning on big data: Opportunities and challenges (2017)Machine Learning With Big Data: Challenges and Approaches (2017)Experience-weighted Attraction Learning in Normal Form Games (1999)UrbanSim: Modeling Urban Development for Land Use, Transportation, and Environmental Planning (2002)Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force (2016)Universal predictability of mobility patterns in cities (2014)Uncovering the spatial structure of mobility networks (2015)Transport and equity in Latin America: a critical review of socially oriented accessibility assessments (2020)Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering (2022)Predicting the travel mode choice with interpretable machine learning techniques: A comparative study (2022)
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References

  • 1988Discrete choice analysis: Theory and application to travel demand3,257 cited
  • 2015Deep learning applications and challenges in big data analytics2,597 cited
  • 1984Specification Tests for the Multinomial Logit Model2,510 cited
  • 2011Modelling Transport1,220 cited
  • 2018Applying a random forest method approach to model travel mode choice behavior491 cited
  • 2017A comparative study of machine learning classifiers for modeling travel mode choice423 cited
  • 2007Testing for IIA in the Multinomial Logit Model364 cited
  • 2018Machine Learning Travel Mode Choices: Comparing the Performance of an Extreme Gradient Boosting Model with a Multinomial Logit Model214 cited
  • 2003Work Travel Mode Choice Modeling with Data Mining: Decision Trees and Neural Networks211 cited
  • 2001Random utility models with implicit availability/perception of choice alternatives for the simulation of travel demand208 cited
  • 1998Alternative nested logit models: structure, properties and estimation190 cited
  • 2000A comparison of the predictive potential of artificial neural networks and nested logit models for commuter mode choice182 cited
  • 2015Predicting Travel Mode of Individuals by Machine Learning149 cited
  • 2005Multilayer feedforward networks for transportation mode choice analysis: An analysis and a comparison with random utility models

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135 cited
  • 2008Travel Mode Choice Modeling with Support Vector Machines127 cited
  • 2016Mode Choice Analysis Using Random Forrest Decision Trees104 cited
  • Cited by

    • 2024A machine learning comparison of transportation mode changes from high-speed railway promotion in Thailand18 cited
    • 2024Sensitivity evaluation of machine learning-based calibrated transportation mode choice models: A case study of Alexandria City, Egypt16 cited
    • 2025Machine learning in travel mode choice studies: A systematic literature review of applications, methods, and challenges9 cited
    • 2025Analyzing High-Speed Rail’s Transformative Impact on Public Transport in Thailand Using Machine Learning7 cited
    • 2025Application of Artificial Neural Networks (ANN) in Investigating Travel Mode Choice: A Case Study of Langsa-Penang Passenger Ferry5 cited