Geography Reference
In-Depth Information
Deng, Z. W., & Ji, M. H. (2010). Deriving rules for trip purpose identification from GPS travel
survey data and land use data: A machine learning approach. In B. Mao, Z. Tian, H. Huang, &
Z. Gao (Eds.),
Proceedings of the seventh international conference on traffic and transportation
studies
, held in Kunming, China, August 3-5. Published by ASCE (American Society of Civil
Engineering).
Draijer, G., Kalfs, N., & Perdok, J. (2000). Global positioning system as data collection method
for travel research.
Transportation Research Record, 1719
, 147-153.
Forrest, S. (1993). Genetic algorithms: Principles of natural selection applied to computation.
Science, New Series, 261
(5123), 872-878. Aug. 13, 1993.
Forrest, T. L., & Pearson, D. F. (2005). Comparison of trip determination methods in household
travel surveys enhanced by a global positioning system.
Transportation Research Record:
Journal of the Transportation Research Board, 1917
(2005), 63-71.
Freitas, A. A. (2002). A survey of evolutionary algorithms for data mining and knowledge
discovery. In A. Ghosh & S. Tsutsui (Eds.),
Advances in evolutionary computation
(pp. 819-
845). New York: Springer.
Gen, M., Li, Y. Z., & Ida, K. (1999). Solving multi-objective transportation problem by spanning
tree-based genetic algorithm.
Journal of IEICE Trans Fundamentals, E82A
, 2802-2810.
Goldberg, D. E. (1989).
Genetic algorithms in search, optimization, and machine learning
. Boston:
Addison-Wesley Longman.
Greene, D. P., & Smith, S. F. (1993). Competition-based induction of decision models from
examples.
Machine Learning, 13
, 220-257.
Griffin, T., & Huang, Y. (2005, November 9-11). A decision tree classification model to automate
trip purpose. In S. Dascalu (Ed.),
Derivation: Proceedings of the ISCA 18th international
conference on computer applications in industry and engineering
(pp. 44-49). Honolulu: ISCA.
ISBN 1-880843-57-9
Holland, J. H. (1992, July). Genetic algorithms.
Scientific American
, pp. 66-72.
Janikow, C. Z. (1993). A knowledge-intensive genetic algorithm for supervised learning.
Machine
Learning, 13
, 189-229.
Kaplan, E. D., & Hegarty, C. J. (2005).
Understanding GPS: Principles and applications
(2nd ed.,
p. 726). Boston: Artech.
Lu, X., & Pas, E. I. (1999). Socio-demographics, activity participation and travel behaviour.
Transportation Research Part A, 33
, 1-18.
Moiseeva, A., Jessurun, J., & Timmermans, H. (2010). Semiautomatic imputation of activity-travel
diaries using GPS traces, prompted recall, and context-sensitive learning algorithms. In 89th
annual meeting of Transportation Research Board, Washington, DC.
Nicolas, P. G., & Hao, J. K. (2001). A genetic algorithm for the classification of natural corks.
In
Proceedings of the genetic and evolutionary computation conference
(pp. 1382-1388). San
Francisco: Morgan Kaufmann.
Noda, E., Freitas, A. A., & Lopes, H. S. (1999). Discovering interesting prediction rules with a 805
genetic algorithm. In
Proceedings of the Congress on Evolutionary Computation-1999 (CEC
1999)
(pp. 1322-1329). Washington, DC: IEEE.
Park, B., Messer, C. J., & Urbanik, T. (1999). Traffic signal optimization program for oversaturated
conditions: Genetic algorithm approach.
Journal of the Transportation Research Board, 1683
,
133-142.
Pattnaik, S. B., Mohan, S., & Tom, V. M. (1998). Urban bus transit route network design using
genetic algorithm.
Journal of Transportation Engineering, 1998
, 124(4).
Punch, W., Goodman, E., Pei, M., Chia-Shun, L., Hovland, P., & Enbody, R. (1993). Further
research on feature selection and classification using genetic algorithms. In
Proceedings of
the 5th international conference on genetic algorithms
(pp. 557-564). San Francisco: Morgan
Kaufmann
Razali, N. M., & Geraghty, J. (2011). Genetic algorithm performance with different selection
strategies in solving TSP. In Proceedings of the World Congress on engineering 2011: Vol
2, London, UK.
Search WWH ::
Custom Search