| ???????????RBF????????????????е???? |
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| 引用本文： | 朱玉,赵卿,梅艳.???????????RBF????????????????е????[J].大地测量与地球动力学,2012,32(5):53-57. |
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| 作者姓名： | 朱玉 赵卿 梅艳 |
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| 作者单位： | 江苏师范大学测绘学院,徐州,221116 |
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| 基金项目： | 国家自然科学基金(40774010);江苏师范大学博士学位教师科研项目(10XLR24) |
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| 摘 要： | ?????????????????????????????????????????????????RBF?????????????????????CIOA????RBF??????????????????????????????CIOA?????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????RBF???????????????????????У???Ч????????????????????
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| 关 键 词： | ????????????? RBF???? ??????μ?? ????? ??? |
PREDICTION OF DYNAMIC DEFORMATION BASED ON CHAOTIC IMMUNE OPTIMIZATION ALGORITHM BRF NEURAL NETWORK |
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| Zhu Yu,Zhao Qing and Mei Yan.PREDICTION OF DYNAMIC DEFORMATION BASED ON CHAOTIC IMMUNE OPTIMIZATION ALGORITHM BRF NEURAL NETWORK[J].Journal of Geodesy and Geodynamics,2012,32(5):53-57. |
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| Authors: | Zhu Yu Zhao Qing and Mei Yan |
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| Institution: | (School of Geodesy and Geomatics,Jiangsu Normal University,Xuzhou 221116) |
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| Abstract: | Aiming to the shortcoming of the traditional prediction model, a method for designing the RBF neural network based on chaotic immune optimization algorithm (CIOA) is proposed, which uses CIOA to the RBF network center vector and weights optimization. By applying chaos mutation operator to producing new antibody and applying immune selection operator to realizing the survival of the fittest, CIOA is able to maintain a good diversity. At the same time, CIOA has higher convergence speed and it can effectively avoid falling into local optima. The results show that chaotic immune optimization RBF neural network applied to the prediction of dynamic deformation, effectively improve the predicted speed and performance. |
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| Keywords: | chaotic immune optimization algorithm(CIOA) RBF neural network model dynamic deformation monitoring optimization model prediction |
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