References
- Aerts , J. 2003 . Using linear programming for multi‐site land‐use allocation. . Geographical Analysis , 35 (2) : 148 – 169 .
- Akay , A. E. , Karas , I. R. , Sessions , J. , Bozali , N. and Gundogag , R. 2004 . “ Using high‐resolution digital elevation model for computer‐aided forest road design. ” . In Proceedings of the XX ISPRS Congress Istanbul 2004
- Arthur , J. L. and Nalle , D. J. 1997 . Clarification on the use of linear programming and GIS for land‐use modeling. . International Journal of Geographical Information Science , 11 (4) : 397 – 402 .
- Barber , C. B. , Dobkin , D. P. and Huhdanpaa , H. T. 1996 . The Quickhull algorithm for convex hulls. . ACM Transactions on Mathematical Software , 22 (4) : 469 – 483 .
- Batty , M. and Jiang , B. 2000 . “ Multi‐agent simulation: computational dynamics within GIS. ” . In Innovations in GIS VII: Geocomputation , Edited by: Martin , D and Atkinson , P . 55 – 71 . London : Taylor & Francis .
- Bonabeau , E. , Dorigo , M. and Theraulaz , G. 1999 . Swarm Intelligence—From Natural to Artificial Systems , New York : Oxford University Press .
- Brimicombe , A. J. 2005 . “ Cluster detection in point event data having tendency towards spatially repetitive events. ” . In Proceedings of the 8th International Conference on Geocomputation Ann Arbor Michigan, 1–3 Agust 2005
- Chen , J. and Jiang , J. 2000 . An event‐based approach to spatio‐temporal data modeling. . GeoInformatica , 4 (4) : 387 – 402 .
- Dantzig , G. B. 1963 . Linear Programming and Extensions , Princeton, New Jersey : Princeton University Press .
- Dantzig , G. B. , Orden , A. and Wolfe , P. 1955 . Generalized simplex method for minimizing a linear from under linear inequality constraints. . Pacific Journal of Mathematics , 5 : 183 – 195 .
- D'Auria , M. , Nanni , M. and Pedreschi , D. 2005 . “ Time focused density based clustering of trajectories of moving objects. ” . In Proceedings of the Workshop on Mining Spatio‐Temporal Data (MSTD‐2005) Porto, 2 October 2005
- Deneubourg , J. L. , Goss , S. , Franks , N. , Sendova‐Franks , A. , Detrain , C. and Chretien , L. 1991 . “ The dynamics of collective sorting: robot‐like ants and ant‐like robots. ” . In Proceedings of the First International Conference on Simulation of Adaptive Behavior: From Animals to Animats1 , Edited by: Meyer , J.‐A and Wilson , S . 356 – 365 . Cambridge, MA : MIT Press .
- De Vasconcelos , M. J. P. , Goncalves , A. , Carty , F. X. , Paul , J. U. and Barros , F. 2002 . A working prototype of a dynamic geographical information system. . International Journal of Geographical Information Science , 16 (1) : 69 – 91 .
- Di Marzo Serugendo , G. , Gleizes , M.‐P. and Karageorgos , A. 2006 . Self‐organisation and emergence in MAS: an overview. . Informatica , 30 : 45 – 54 .
- Forer , P. 1998 . “ Geometric approaches to the nexus of time, space, and microprocess: implementing practical model for mundane socio‐spatial systems. In: Egenhofer, M.J., and Golledge, R.G. (eds), ” . In Spatial and Temporal Reasoning in Geographic Information Systems , 171 – 190 . Oxford : Oxford University Press .
- Forman , R. T. T. 1995 . Land Mosaics: The Ecology of Landscape and Regions , Cambridge : Cambridge University Press .
- Gahegan , M. and Brodaric , B. 2002 . “ Computational and visual support for geographical knowledge construction: filling in the gaps between Exploration and Explanation. ” . In Proceedings of the Symposium on GeoSpatial Theory, Processing and Applications Ottawa, 2002 (CD‐ROM)
- Gass , S. I. 1985 . Linear Programming: Methods and Applications , New York : International Thomson Publishing . 5th edition
- Gudmundsson , J. , van Kreveld , M. and Speckmann , B. 2004 . “ Efficient detection of motion patterns in spatio‐temporal data sets. ” . In 12th ACM International Workshop on Geographic Information Systems, ACM‐GIS 2004 , Edited by: Pfoser , D , Cruz , I. F and Ronthaler , M . Washington DC : ACM . 12–13 November, Washington, DC, USA
- Guerra , G. and Lewis , J. Spatial optimization and GIS: locating an optimal habitat for wildlife reintroduction. . ARCUSER , 2002 32 – 35 . April–June
- Hall , L. O. and Kanade , P. 2006 . “ Scalable Swarm Based Fuzzy Clustering. ” . In From Data and Information Analysis to Knowledge Engineering, Part 1 , Edited by: Spiliopoulou , M , Kruse , R , Borgelt , C , Numberger , A and Gaul , W . Berlin : Springer .
- Han , J. , Kamber , M. and Ting , A. K. H. 2001 . “ Spatial clustering methods in data mining—a survey. ” . In Geographic Data Mining and Knowledge Discovery , Edited by: Miller , H. J and Han , J . 188 – 217 . Bristol, PA : Taylor and Francis .
- Handl , J. , Knowles , J. and Dorigo , M. 2004 . “ Strategies for the increased robustness of ant‐based clustering. ” . In Engineering Self‐Organising Systems , 90 – 104 . Heidelberg, , Germany : Springer‐Verlag . vol. 2977 of Lecture Notes in Computer Science
- Hooge , P. N. , Eichenlaube , W. M. and Solomon , E. K. 2001 . “ Using GIS to analyze animal movements in the marine environment. ” . In Analyzing Animal Movements , Edited by: Hooge , P. M , Eichenlaube , W. M and Solomon , E. K . Alaska Science Center, Anckorage, AK : US Geological Survey .
- Hornsby , K. and Egenhofer , M. 1998 . “ Identity‐based change operations for composite objects. ” . In Proceedings of the 8th International Symposium on Spatial Data Handling , Edited by: Poiker , T.K and Chrisman , N . 202 – 213 . Vancouver, , Canada : International Geographic Union .
- Hornsby , K. and Egenhofer , M. 2002 . Modeling moving objects over multiple granularities. . Annals of Mathematics and Artificial Intelligence , 36 : 177 – 194 . Special Issue on Spatial and Temporal Granularity
- Kaufman , L. and Rousseeuw , P. 1990 . Finding Groups in Data: An Introduction to Cluster Analysis , New York : John Wiley & Sons .
- Kaur , R. , Srivastava , R. and Betne , R. 2004 . Integration of LP and hydrological model. . Journal of Geographical Information Science , 18 (1) : 73 – 98 .
- Kelly , K. 1994 . Out of Control: The New Biology of Machines, Social Systems and the Economic World , New York : Basic Book, Perseus Books Group .
- K och , A., 2000, Linking multi agent systems and GIS—modelling and simulating spatial interactions. Available online at: www.rwth‐aachen.de/geo/Ww/deutsch/MultiAgentsKoch.pdf (www.rwth-aachen.de/geo/Ww/deutsch/MultiAgentsKoch.pdf) .
- Kwan , M. P. 2004 . GIS methods in time–geographic research: geocomputation and geovisualization of human activity patterns. . Geographic Annals , 86B (4) : 267 – 280 .
- Landau , U. , Prashker , J. N. and Alpern , B. 1982 . Evaluation of activity constrained choice sets to shopping destination choice modeling. . Transportation Research A , 16A : 199 – 207 .
- Langran , G. 1989 . A review of temporal database research and its use in GIS applications. . International Journal of Geographical Information Systems , 3 (3) : 215 – 232 .
- Langran , G. 1993 . Issues of implementing a spatio‐temporal system. . International Journal of Geographical Information Systems , 7 (4) : 305 – 314 .
- Langran , G. 1992 . Time in Geographic Information Systems , London : Taylor & Francis .
- Laube , P. , Imfeld , S. and Weibel , R. 2005 . Discovering relative motion patterns in groups of moving point objects. . International Journal of Geographical Information Science , 19 (6) : 639 – 668 .
- Li , Y. , Han , J. and Yang , J. 2004 . Clustering moving objects, KDD'04, 22–25 August, 2004, Seattle, Washington, USA
- Luenberger , D. G. 1984 . Introduction to Linear and Nonlinear Programming , Boston : Addison Wesley .
- Miller , H. J. 2005 . A measurement theory for time geography. . Geographical Analysis , 37 : 17 – 45 .
- Miller , H. J. and Han , J. 2001 . “ Geographic data mining and knowledge discovery—an overview. ” . In Geographic Data Mining and Knowledge Discovery , Edited by: Miller , H. J and Han , J . 3 – 32 . Bristol, PA : Taylor and Francis .
- Nanni , M. 2005 . Speeding‐up hierarchical agglomerative clustering in presence of expensive metrics. PAKDD 2005 LNAI 3518
- Netanyahu , N. , Friedman , L. and Shoshany , M. 2003 . “ Mean shift‐based clustering for remotely sensed data. ” . In Proceedings of the IGARSS 2003 Toulouse, France
- Openshaw , S. 1994 . “ Two exploratory space–time‐attribute pattern analyzers relevant to GIS. ” . In Spatial Analysis and GIS , Edited by: Fotheringham , A. S and Rogerson , P. A . 83 – 104 . London : Taylor& Francis .
- Openshaw , S. 1998 . “ Building automated geographical analysis and explanation machines. ” . In Geocomputation: A Primer , Edited by: Longley , P.A , Brooks , S.M , McDonnel , R and MacMillan , B . 95 – 115 . Chichester : Wiley .
- Openshaw , S. and Openshaw , C. 1997 . Artificial Intelligence in Geography , New York : John Wiley & Sons .
- Peuquet , D. J. and Duan , N. 1995 . An event‐based spatio‐temporal data model (ESTDM) for temporal analysis of geographical data. . International Journal of Geographical Information Systems , 9 (1) : 7 – 24 .
- Pollard , K. and van der Laan . 2002 . Statistical inference for simultaneous clustering of gene expression data. . Mathematical Biosciences , 176 (1) : 99 – 121 .
- Pun‐Cheng , L. and Chu , A. 2004 . An analysis of shoppers' walking behavior by using GIS. Archive ISPRS WG II/5
- Ramos , V. and Abraham , A. Evolving a stigmergic self‐organized data‐mining. In ISDA'04, International Conference on Intelligent Systems, Design and Applications, . Hungary 2004 (Conference proceedings on ROM)
- Ramos , V. and Almeida , F. 2000 . “ Artificial ant colonies in digital image habitats—a mass behaviour effect study on pattern recognition. ” . In ANTS'00—2nd International Workshop on Ant Algorithms (From Ant colonies to Artificial Ants) Edited by: Dorigo , M , Middendorf , M and Stutzle , T . Belgium (Conference Proceedings on CD ROM)
- Resnick , M. 1994 . Turtles, Termites, and Traffic Jams: Explorations in Massively Parallel Microworlds , Cambridge, MA : MIT Press .
- Shannon , C. E. and Weiner , W. 1949 . The Mathematical Theory of Communication , Urbana : University of Illinois .
- Shoshany , M. and Kelman , E. 2006 . Assessing mutuality of change in soil and vegetation pattern characteristics by means of cellular automata. . Geomorphology , 77 (1–2) : 35 – 46 .
- Sinha , G. and Mark , D. M. 2005 . Measuring similarity between geospatial lifelines in studies of environmental health. . Journal of Geographical Systems , 7 (1) : 115 – 136 .
- Swihart , R. K. and Slade , N. A. 1985 . Testing for independence of observations in animal movements. . Ecology , 66 : 1176 – 1184 .
- Takeyama , M. and Couclelis , H. 1997 . Map dynamics: integrating cellular automata and GIS through Geo‐Algebra. . International Journal of Geographical Information Science , 11 (1) : 73 – 91 .
- Tobler , W. 1981 . A model of geographic movement. . Geographical Analysis , 13 (1) : 1 – 20 .
- Van der Laan , M. J. and Pollard , K. S. 2003 . A new algorithm for hybrid hierarchical clustering with visualization and the bootstrap. , Berkley : University of California . Report of Research within the framework of the Life Sciences Informatics Program
- Viszine , A. L. , de Castro , L. N. , Hruschka , E. D. and Gudwin , R. R. 2005 . Towards improving clustering ants: an adaptive ant clustering algorithm. . Informatica , 29 : 143 – 154 .
- Von Neumann , J. and Burks , A. W. 1966 . Theory of Self‐Reproducing Automata , Urbana : University of Illinois .
- Wang , X. , Qiu , W. and Zamar , R. H. An iterative non‐parametric clustering algorithm based on local shrinking. Proceedings of the IEEE ICDM conference 2002 ,
- W ilensky , U., 1998, NetLogo Ants model. Center for Connected Learning and Computer‐Based Modeling, Northwestern University, Evanston, IL. Available online at: http://ccl.northwestern.edu/netlogo/models/Ants .
- Worboys , M. 2005 . Event‐oriented approaches to geographic phenomena. . International Journal of Geographical Information Science , 19 (1) : 1 – 28 .
- Yuan , M. and McIntosh , J. 2003 . GIS representation for visualizing and mining geographic dynamics. . Transactions in GIS , 3 (2) : 3 – 10 .
- Zhang , W. and Hunter , G. J. 2000 . Temporal interpolation of spatially dynamic objects. . GeoInformatica , 4 (4) : 403 – 418 .