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RISS 인기검색어
- 검색키워드
- 저자 : 양옥진 (검색결과 4 건)
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Current GSIS(Geo-Spatial Information System) is mostly dependent on the method of spatial overlay using vector or raster map for analysis of land suitability. This conventional method of map making modelling, however, couldn't indicate the reasonable solution for classifying the data and deciding relative weight, so, it was inevitable that the result was determined by knowledge or intention of subjective view of analyst. There are few possibility to improve these situation in some day. As following the rule made by subjective decision of analyst, most analysis part couldn't be supported by firmly theoretical basis. This study is tried to organic combination in implementing the suitability analysis of urban landuse between GSIS and ANN(Artificial Neural Network). ANN has merits that can decide rationally connectivity weights among neural network nodes through procedure of learning. It is possible to replace the weight among factors by the connectivity weights of neural network. Therefore, as this point of view it is to enough the possibility of ANN application in a GSIS. This study is composed of two kinds of neural networks to be executed. First neural network was used in the suitability analysis of landuse and second one was oriented to analyze of optimum landuse pattern. These neural networks were learned with back-propagation algorithm using the steepest gradient and genetic algorithm which are coded by ^(++). Also, These neural networks used sigmoid function as a active function. The results are given on chapter 4. Analysis results show landuse suitability map and optimum landuse pattern of Naju city consisted of residential, commercial, industrial and green zone in present zoning system. Each result map was written by the grid format of Arc/Info. Also, suitability area presented in the suitability map and optimum landuse pattern show distribution pattern consistent with theoretical concept of urban landuse plan in aspect of location and space structure.
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