Embedding Urban Planning Objective by Integrated Artificial Immune System and Cellular Automata
Received date: 2007-10-27
Revised date: 2008-05-23
Online published: 2008-08-25
Supported by
National Outstanding Youth Foundation of NSF of China, No.40525002; National Natural Science Foundation of China, No.40471105; Hi-Tech Research and Development Program of China, No.2006AA12Z206
A rtificial Im m une System can be used in pattern recognition and self-adaptive learning for its strong com puting pow er such as im m une recognition,clonal selection,im m une learning and im m une m em ory, w hich is quite suitable for studying the com plex geographical progress.A nd C A is proved to be convenient and effective for studying com plex system . A s a result, m odel based on integrating A IS w ith CA was built to sim ulate the urban evolution and planning in this paper.A s planning objective w as em bedded into A IS algorithm , antibody w ill gradually evolve tow ards w hich by changing the evolutionary variation m echanism . Then urban developing spatial pattern based on different planning scenarios can be sim ulated,w hich w ill supply decision support for urban and land use planning.This paper designed six different scenarios for city developm ent, and used A IS-based C A m odel to sim ulate the Pearl R iver D elta's urban developm ent (1988-2002) under different planning scenarios. It also com pared the urban com pactness under different sim ulation results: "C ity C enter" and "C ity C enter- Expressw ay" m odels incline to result in a m ore com pact form of urban; O n the other hand, "Tow n C enter" and "R oad" m odels com e into being a relatively scattered and decentralized form of urban areas. Sim ulated results indicate that "C ity C enter- Expressw ay" is the best developm ent m ode for the Pearl R iver D elta.
LIU Xiaoping, LI Xia, ZHANG Xiaohu, CHEN Gangqiang, LI Shaoying, CHEN Yimin . Embedding Urban Planning Objective by Integrated Artificial Immune System and Cellular Automata[J]. Acta Geographica Sinica, 2008 , 63(8) : 882 -894 . DOI: 10.11821/xb200808009
[1] B arredo J, K asanko M , M cC orm ick N et al. M odelling dynam ic spatial processes: Sim ulation of urban future scenarios through cellular autom ata.Landscape and U rban Planning,2003,64: 145-160.
[2] Zhou C henghu, Shun Zhanli, X ie Y ichun. G eographic C ellular A utom ata Study. B eijing: Science Press, 1999.
[周成虎, 孙战利, 谢一春. 地理元胞自动机研究. 北京: 科学出版社,1999.]
[3] H e C Y , O kada N , Zhang Q F et al. M odeling urban expansion scenarios by coupling cellular autom ata m odel and system s dynam ic m odel in B eijing,C hina.A pplied G eography,2006,26: 323-345.
[4] W hite R ,Engelen G .C ellular autom ata and fractal urban form : A cellular m odelling approach to the evolution of urban land-use patterns.Environm ent and Planning A ,1993,25: 1175-1199.
[5] B atty M ,X ie Y .From cells to cities.Environm ent and Planning B ,1994,21: 531-548.
[6] C larke K C , G aydos L J, 1998. Loose-coupling a cellular autom ata m odel and G IS: Long-term urban grow th prediction for San Francisco and W ashington/B altim ore.International Journal of G eographical Inform ation Science,12(7): 699-714.
[7] Li X ,Y eh A G O .M odelling sustainable urban developm ent by the integration of constrained cellular autom ata and G IS. International Journal of G eographical Inform ation Science,2000,14(2): 131-152.
[8] W u F, W ebster C J. Sim ulation of land developm ent through the integration of cellular autom ata and m ulticriteria evaluation.Environm ent and Planning B : Planning and D esign,1998,25: 103-126.
[9] Shi W Z, M Y C Pang. D evelopm ent of V oronoi-based cellular autom ata-an integrated dynam ic m odel for G eographical Inform ation System s.International Journal of G eographical Inform ation Science,2000,14(5): 455-474.
[10] Torrens P M , O 'Sullivan D . Editorial: C ellular autom ata and urban sim ulation: W here do w e go from here? Environm ent and Planning B ,2001,28: 163-168.
[11] Tobler W .A com puter m ovie sim ulating urban grow th in the D etroit region.Econom ic G eography,1970,46: 234-240.
[12] C ouclelis H . C ellular w orlds: A fram ew ork for m odeling m icro-m acro dynam ics. Environm ent and Planning A , 1985, 17: 585-596.
[13] C ouclelis H . O f m ice and m en: W hat rodent population scan teach us about com plex spatial dynam ics. Environm ent and Planning A ,1988,20: 99-109.
[14] C ouclelis H . M acrostructure and m icrobehavior in a m etropolitan area. Environm ent and Planning B , 1989, 16: 141-154.
[15] C larke K C , H oppen S, G aydos L. A self-m odifying cellular autom aton of historical urbanization in the San Francisco B ay area.Environm ent and Planning B ,1997,24: 247-261.
[16] W u F.C alibration of stochastic cellular autom ata: The application to rural-urban land conversions.International Journal of G eographical Inform ation Science,2002,16(8): 795-818.
[17] W u F, W ebster C J. Sim ulation of land developm ent through the integration of cellular autom ata and m ulticriteria evaluation.Environm ent and Planning B : Planning and D esign,1998,25: 103-126.
[18] Liu Y an, Stuart R P. M odelling urban developm ent w ith cellular autom ata incorporating fuzzy-set approaches. C om puters,Environm ent and U rban System s,2003,27: 637-658.
[19] Li X ia, Y eh A G O . Principal com ponent analysis of stacked m ulti-tem poral im ages for m onitoring of rapid urban expansion in the Pearl R iver D elta.International Journal of R em ote Sensing,1998,19(8): 1501-1518.
[20] Li X , Y eh A G O . N eural-netw ork-based cellular autom ata for sim ulating m ultiple land use changes using G IS. International Journal of G eographical Inform ation Science,2002,16(4): 323-343.
[21] Liu X iaoping, Li X ia. R etrieving C A nonlinear transition rule from high-dim ensional feature space. A cta G eographica Sinica, 2006, 61(6): 663-672.
[ 刘小平, 黎夏. 从高维特征空间中获取元胞自动机的非线性转换规则. 地理学报, 2006,61(6): 663-672.]
[22] Li X iaoping, Li X ia, Y eh A G O et al. D iscovery of transition rules for geographical cellular autom ata by using ant colony optim ization.Science in C hina (Series D ),2007,37(6): 824-834.
[刘小平, 黎夏, 叶嘉安等. 利用蚁群智能挖 掘地理元胞自动机的转换规则. 中国科学(D 辑),2007,37(6): 824-834.]
[23] Li X ia, Y eh A G O . M odelling sustainable urban developm ent by the integration of constrained cellular autom ata and G IS.International Journal of G eographical Inform ation Science,2000,14(2): 131-152.
[24] Li X ia, Y eh A G O . C onstrained cellular au tom ata for m odelling sustainable urban form s. A cta G eographic Sinica, 1999, 54(4): 289-298.
[黎夏, 叶嘉安. 约束性单元自动演化C A 模型及可持续城市发展形态的模拟. 地理学报, 1999,54 (4): 289-298.]
[25] W ard D P, M urray A T. A n optim ized cellular autom ata approach for sustainable urban developm ent in rapidly urbanizing regions.International Journal of G eographical Inform ation Science,1999,7(5): 235-250.
[26] Y eh A G O ,Li X .Sim ulation of developm ent alternatives using neural netw orks, cellular autom ata, and G IS for urban planning.Photogram m etric Engineering & R em ote Sensing,2003,69(9): 1043-1052.
[27] H e C hunyang, Shi Peijun, C hen Jin et al. D eveloping land use scenario dynam ics m odel by the integration of system dynam ics m odel and cellular autom ata m odel.Science in C hina (Series D ),2005,35(5): 464-473.
[何春阳, 史培军, 陈 晋等. 基于系统动力学模型和元胞自动机模型的土地利用情景模型研究. 中国科学(D 辑),2005,35(5): 464-473.]
[28] K im J, B entley P. The artificial im m une m odel for netw ork intrusion detection. Proc 7th European C onference on Intelligent Techniques and Soft C om puting,A achen,G erm any,1999.
[29] Jerne N K .The im m une system .Scientific A m erican,1973,229(1): 52-60.
[30] C hun JS, K im M K , Jung H K , et al. Shape O ptim ization of Electrom agnetic D evices U sing Im m une A lgorithm . IEEE Trans on M agnetics,1997,33(2): 1876-1879.
[31] Tang Z, Y am aguchi T, Tashim a K , Ishizuk O , M ultiple T K . A m ultiple valued im m une netw ork and its applications. IEIC E Trans.Fundam entals,1999,E82-A (6): 1102-1108.
[32] Tim m is J. O n Param eter A djustm ent of Im m une Inspired M achine Learning A lgorithm A IN E. C anterbury: U niversity K ent,2000.
[33] K um ark K ,N eidhoefer J.Im m unized neurocontrol.Experts System s w ith A pplication,1997,13(3): 201-214.
[34] Tim m is J,N eal M A .R esource lim ited artificial im m une system for data analysis.K now ledge B ased System s,2001,14 (3/4): 121-130.
[35] D asgupta D , Forrest S. Tool breakage detection in m illing operations using a negative-selection algorithm . Technical R eport C S95-5,D epartm ent of C om puter Science,U niversity of N ew M exico,1995.
[36] Jenks M ,B urton E,W illiam s K .C om pact cities and sustainability: A n introduction.In: Jenks M ,B urton E,W illiam s K (eds.).The C om pact C ity: A Sustainable U rban Form ? London: SPO N Press,1996,11-12.
[37] B anister D , W atson S, W ood C . Sustainable cities: transport, energy, urban form . Environm ent and Planning B , 1997, 24: 125-143.
[38] Li X ia, Y eh A G O . A nalyzing spatial restructuring of land use patterns in a fast grow ing region using rem ote sensing and G IS.Landscape and U rban Planning,2004,69(4): 335-354.
[39] X ue Ling. U rban space evolution sim ulation based on subjective m ulti-agent. D octoral D issertation of Peking U niversity,2002.
[薛领. 基于主体(m ulti-agent) 的城市空间演化模拟研究. 北京大学博士论文,2002.]
[40] M cG arigal K , M arks B . Fragstats: Spatial pattern analysis program for quantifying landscape structure. U SD A Forest Service-G eneral Technical R eport PN W -G TR -351,1995.
/
| 〈 |
|
〉 |