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ganmin银虫 (正式写手)
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帮忙看一下这几句英文摘要有无问题【有效期至2009年02月27日】
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A hybrid optimization algorithm adapted to radial basis function (RBF) networks and an RBF nets-based state-dependent AR(X) model parameter estimation is presented. The proposed method (EA-SNPOM) merges an evolutionary algorithm (EA) with a gradient-based search strategy—the structured nonlinear parameter optimization method (SNPOM). It provides a global search with the EA and a local search via the SNPOM. The effectiveness of the resulting combination is demonstrated by several examples. [ Last edited by telomerase on 2009-2-18 at 09:55 ] |
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wshbinzhang
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ganmin(金币+2,VIP+0):谢谢！还有问题请你回答，回答有分，谢谢 2-18 09:49
ganmin(金币+2,VIP+0):谢谢！还有问题请你回答，回答有分，谢谢 2-18 09:49
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1. A hybrid optimization algorithm based on radial basis function (RBF) networks and an RBF nets-based state-dependent AR(X) model parameter estimation has been presented. 2. The proposed method (EA-SNPOM) combines the evolutionary algorithm (EA) and the structured nonlinear parameter optimization method (SNPOM, a gradient-based search strategy). 3. A global search with EA and a local search via SNPOM can be achieved. |
2楼2009-02-18 00:57:30
ganmin
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4楼2009-02-18 09:56:39
ganmin
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6楼2009-02-20 20:32:30
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7楼2009-02-25 10:52:06
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ganmin(金币+6,VIP+0):谢谢阿！ 2-27 15:48
ganmin(金币+6,VIP+0):谢谢阿！ 2-27 15:48
| A hybrid optimization algorithm for radial basis function (RBF) networks and RBF nets-based state-dependent AR(X) models parameter estimation is presented. This algorithm (EA-SNPOM) effectively combines an evolutionary algorithm (EA) with a gradient-based search strategy via the structured nonlinear parameter optimization method (SNPOM). The hybrid approach provides a global search with the EA and a local search via the SNPOM. The effectiveness of the resulting combination is demonstrated by several examples. |
8楼2009-02-26 20:49:43
