Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/61415
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dc.titleStudy on optimization of agent initial positions in land combat simulation
dc.contributor.authorWu, C.
dc.contributor.authorLiang, Y.
dc.contributor.authorLee, H.P.
dc.contributor.authorLu, C.
dc.contributor.authorYang, X.
dc.date.accessioned2014-06-17T06:34:52Z
dc.date.available2014-06-17T06:34:52Z
dc.date.issued2004-03
dc.identifier.citationWu, C.,Liang, Y.,Lee, H.P.,Lu, C.,Yang, X. (2004-03). Study on optimization of agent initial positions in land combat simulation. Progress in Natural Science 14 (3) : 257-261. ScholarBank@NUS Repository.
dc.identifier.issn10020071
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/61415
dc.description.abstractThe use of computational-intelligence-based techniques in the optimization of agent initial positions in land combat simulations is studied. A method for the reduction of support vectors in the support vector machine (SVM) is presented. The optimization on the width of the Gaussian kernel function and the combination of the SVM with the radial basis function neural network are performed in the proposed method. Simulation results show that the proposed method can improve the running efficiency drastically compared with that of using the traditional SVM with the same precision. We also summarize and present some experiences and trends on the optimization problem in land combat simulation.
dc.sourceScopus
dc.subjectGenetic algorithm
dc.subjectMulti-agent
dc.subjectRadial basis function
dc.subjectRegression
dc.subjectSupport vector machine
dc.typeArticle
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.sourcetitleProgress in Natural Science
dc.description.volume14
dc.description.issue3
dc.description.page257-261
dc.description.codenPNASE
dc.identifier.isiutNOT_IN_WOS
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