Alison Heppenstall
Alison Heppenstall
Professor in Geocomputation, University of Leeds
Verified email at leeds.ac.uk - Homepage
Title
Cited by
Cited by
Year
Agent-based models of geographical systems
AJ Heppenstall, AT Crooks, LM See, M Batty
Springer Science & Business Media, 2011
3142011
Introduction to agent-based modelling
AT Crooks, AJ Heppenstall
Agent-based models of geographical systems, 85-105, 2012
2282012
Calibration of a fuzzy cellular automata model of urban dynamics in Saudi Arabia
K Al-Ahmadi, L See, A Heppenstall, J Hogg
Ecological complexity 6 (2), 80-101, 2009
1632009
Crime reduction through simulation: An agent-based model of burglary
N Malleson, A Heppenstall, L See
Computers, environment and urban systems 34 (3), 236-250, 2010
1252010
Creating realistic synthetic populations at varying spatial scales: A comparative critique of population synthesis techniques
K Harland, A Heppenstall, D Smith, MH Birkin
Journal of Artificial Societies and Social Simulation 15 (1), 2012
1222012
Timing error correction procedure applied to neural network rainfall—runoff modelling
RJ Abrahart, AJ Heppenstall, LM See
Hydrological sciences journal 52 (3), 414-431, 2007
702007
Genetic algorithm optimisation of an agent-based model for simulating a retail market
AJ Heppenstall, AJ Evans, MH Birkin
Environment and Planning B: Planning and Design 34 (6), 1051-1070, 2007
672007
Using hybrid agent-based systems to model spatially-influenced retail markets
A Heppenstall, A Evans, M Birkin
Journal of Artificial Societies and Social Simulation 9 (3), 2006
632006
“Space, the final frontier”: How good are agent-based models at simulating individuals and space in cities?
A Heppenstall, N Malleson, A Crooks
Systems 4 (1), 9, 2016
552016
A hybrid multi‐agent/spatial interaction model system for petrol price setting
AJ Heppenstall, AJ Evans, MH Birkin
Transactions in GIS 9 (1), 35-51, 2005
542005
Symbiotic adaptive neuro-evolution applied to rainfall–runoff modelling in northern England
CW Dawson, LM See, RJ Abrahart, AJ Heppenstall
Neural Networks 19 (2), 236-247, 2006
482006
A conceptual and neural network model for real-time flood forecasting of the Tiber River in Rome
G Napolitano, L See, B Calvo, F Savi, A Heppenstall
Physics and Chemistry of the Earth, Parts A/B/C 35 (3-5), 187-194, 2010
472010
Modelling built-up expansion and densification with multinomial logistic regression, cellular automata and genetic algorithm
A Mustafa, A Heppenstall, H Omrani, I Saadi, M Cools, J Teller
Computers, Environment and Urban Systems 67, 147-156, 2018
462018
Using an agent-based crime simulation to predict the effects of urban regeneration on individual household burglary risk
N Malleson, A Heppenstall, L See, A Evans
Environment and Planning B: Planning and Design 40 (3), 405-426, 2013
462013
Implementing comprehensive offender behaviour in a realistic agent-based model of burglary
N Malleson, L See, A Evans, A Heppenstall
Simulation 88 (1), 50-71, 2012
452012
Synthesising carbon emission for mega-cities: A static spatial microsimulation of transport CO2 from urban travel in Beijing
J Ma, A Heppenstall, K Harland, G Mitchell
Computers, Environment and Urban Systems 45, 78-88, 2014
442014
A fuzzy cellular automata urban growth model (FCAUGM) for the city of Riyadh, Saudi Arabia. Part 1: Model structure and validation
K Al-Ahmadi, A Heppenstall, J Hogg, L See
Applied Spatial Analysis and Policy 2 (1), 65-83, 2009
422009
Daily travel behaviour in Beijing, China: An analysis of workers' trip chains, and the role of socio-demographics and urban form
J Ma, G Mitchell, A Heppenstall
Habitat International 43, 263-273, 2014
402014
A fuzzy cellular automata urban growth model (FCAUGM) for the city of Riyadh, Saudi Arabia. Part 2: scenario testing
K Al-Ahmadi, A Heppenstall, J Hogg, L See
Applied Spatial Analysis and Policy 2 (2), 85-105, 2009
242009
Agent-based modelling and geographical information systems: a practical primer
A Crooks, N Malleson, E Manley, A Heppenstall
SAGE Publications Limited, 2018
192018
The system can't perform the operation now. Try again later.
Articles 1–20