Imperial College London

Alireza Zolfaghari

Faculty of MedicineSchool of Public Health

Research Associate in Data Science and Machine Learning
 
 
 
//

Contact

 

a.zolfaghari Website

 
 
//

Location

 

615Skempton BuildingSouth Kensington Campus

//

Summary

 

Publications

Publication Type
Year
to

11 results found

Zolfaghari A, Polak J, Sivakumar A, 2016, Choice set imputation in atomistic spatial choice models, Transportation Research Record, Vol: 2564, Pages: 138-146, ISSN: 0361-1981

Constructing the universal choice set in spatial choice models developed at the level of elemental alternatives (atomistic models) is challenging because disaggregate data on the attributes of nonchosen alternatives are often not available. Even when the disaggregate data on nonchosen alternatives are available, matching two data sources will inevitably be error prone given that they might be collected at different times and they might have different coding for categorical variables. An important practical question in the estimation of such atomistic models, therefore, is how to construct the universal choice set in the absence of disaggregate data on the attributes of the nonchosen alternatives. This paper presents a novel approach for spatial imputation of attributes of nonchosen alternatives for estimation and application of atomistic spatial choice models in the absence of disaggregate data. The proposed approach uses the iterative proportional fitting algorithm to impute the attributes of nonchosen alternatives from aggregated data on elemental alternatives. The proposed method is validated with a Monte Carlo experiment and applied to real data in the London residential location choice context.

Journal article

Le Vine S, Zolfaghari A, Polak J, 2015, Autonomous cars: The tension between occupant experience and intersection capacity, TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, Vol: 52, Pages: 1-14, ISSN: 0968-090X

Journal article

Pawlak J, Zolfaghari A, Polak J, 2015, Imputing Socioeconomic Attributes for Movement Data by Analysing Patterns of Visited Places and Google Places Database: Bridging between Big Data and Behavioural Analysis, 4th International Choice Modelling Conference

Conference paper

Zolfaghari A, Sivakumar A, Polak JW, 2014, Simplified probabilistic choice set formation models in a residential location choice context

The implementation of a theoretically sound, two-stage discrete-choice modelling paradigm incorporating probabilistic choice sets is impractical when the number of alternatives is large, which is a typical case in most spatial choice contexts. In the context of residential location choice, Kaplan et al., 2009, Kaplan et al., 2011 and Kaplan et al., 2012 (KBS) developed a semi-compensatory choice model incorporating data of individuals searching for dwellings observed using a customised real estate agency website. This secondary data is used to compute the probability of considering a choice set that takes the form of an ordered probit model. In this paper, we illustrate that the simplicity of the KBS model arises because of an unrealistic assumption that individuals' choice sets only contain alternatives that derive from their observed combination of thresholds. Relaxing this assumption, we introduce a new probabilistic choice set formation model that allows the power set to include all potential choice sets derived from variations in thresholds' combinations. In addition to extending the KBS model, our proposed model asymptotically approaches the classical Manski model, if a suitable structure is used to categorise alternatives. In order to illustrate the biases inherent in the original KBS approach, we compare it with our proposed model and the MNL model using a Monte Carlo experiment. The results of this experiment show that the KBS model causes biases in predicted market share if individuals are free to choose from any potential choice sets derived from combinations of thresholds.

Journal article

Zolgafhari A, Sivakumar A, Polak JW, 2012, Choice set pruning in residential location choice modelling: a comparison of sampling and choice set generation approaches in greater London, 43rd Annual Conference of the Universities-Transport-Studies-Group (UTSG), Publisher: TAYLOR & FRANCIS LTD, Pages: 87-106, ISSN: 0308-1060

The discrete choice analysis of residential location choice forms an important part of land use-transport modelling systems but gives rise to a number of significant modelling

Conference paper

Zolfaghari A, Sivakumar A, Polak JW, 2012, Simplified Two-stage Choice Set Formation Models Incorporating Observed Choice Set Data, Toronto, Canada, International Conference on Travel Behaviour Research (IATBR)

Conference paper

Zolfaghari A, Sivakumar A, Polak JW, 2012, Choice Set Formation in Residential Location Choice Modelling: Empirical Comparison of Alternative Approaches, Washington DC, US, Transportation Research Board (TRB)

Conference paper

Zolfaghari A, Sivakumar A, Polak JW, 2012, Choice set pruning in residential location choice modelling: a comparison of sampling and choice set generation approaches in greater London, Transportation Planning and Technology, Vol: 35, Pages: 87-106, ISSN: 0308-1060

Journal article

Zolfaghari A, Sivakumar A, Polak JW, 2012, Simplified Two-stage Choice Set Formation Models in Residential Location Choice Modelling, Aberdeen, UK, Annual UTSG meeting

Conference paper

Zolfaghari A, Sivakumar A, Polak JW, 2011, Choice Set Pruning in Residential Location Choice Modelling, Milton Keynes, UK, Annual UTSG meeting

Conference paper

Zolfaghari A, Sivakumar A, Polak JW, 2011, Choice Set Formation in Residential Location Choice Modelling: Implementation of a Hazard-based Approach, Leeds, UK, International Choice Modelling Conference (ICMC)

Conference paper

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: http://wlsprd.imperial.ac.uk:80/respub/WEB-INF/jsp/search-html.jsp Request URI: /respub/WEB-INF/jsp/search-html.jsp Query String: respub-action=search.html&id=00522953&limit=30&person=true