Land Use Change Simulation Model Based on Support Vector Machine
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Graphical Abstract
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Abstract
We apply support vector machine to simulate the relation between arable land area and datum of driving forces of land use change of Hubei Province from 1986-2004,and compare the test values by GA-SVM with ones by BP and RBF neural networks models.Practice proves the simulation results of land use change by SVM are more effective than those from BP-ANN,and is approximate to the precision of RBF-ANN.
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