| 基于粒子群优化BP神经网络的养肠胃菜谱判定 |
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| 引用本文： | 张璐,雷雪梅.基于粒子群优化BP神经网络的养肠胃菜谱判定[J].计算机科学,2016,43(Z11):63-66, 72. |
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| 作者姓名： | 张璐 雷雪梅 |
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| 作者单位： | 北京科技大学计算机与通信工程学院 北京100083,北京科技大学计算机与通信工程学院 北京100083 |
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| 摘 要： | 提出了一种基于粒子群优化BP神经网络的养肠胃菜谱判定的方法。粒子群算法通过自身良好的搜寻能力,对BP神经网络的权值和阈值进行了优化,弥补了BP神经网络中收敛性慢、存在多个局部极值点的缺陷。并分别通过误差曲线图、线性回归图等,对BP神经网络模型与PSO-BP神经网络模型进行比较分析。实验结果表明,PSO-BP模型判定较准确,在调养肠胃的饮食食谱选择中起到了指导作用。
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| 关 键 词： | PSO-BP神经网络模型 粒子群优化算法 调养肠胃菜谱 |
Optimized Approach on Stomach Nourishing Decision Based on PSO-BP Neural Network |
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| ZHANG Lu and LEI Xue-mei.Optimized Approach on Stomach Nourishing Decision Based on PSO-BP Neural Network[J].Computer Science,2016,43(Z11):63-66, 72. |
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| Authors: | ZHANG Lu and LEI Xue-mei |
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| Affiliation: | School of Computer and Communication Engineering,University of Science and Technology Beijing,Beijing 100083,China and School of Computer and Communication Engineering,University of Science and Technology Beijing,Beijing 100083,China |
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| Abstract: | The conventional BP neural network has the problems of slow convergence and multi-local extreme value.An optimized approach on stomach nourishing decision based on PSO-BP neural network was proposed.The robust sear-ching ability of particle swarm optimization enables the weight and threshold of BP neural network to optimize.By the error curve and linear regression,we compared PSO-BP and BP method.The results show that the proposed approach can get a more accurate decision on stomach nourishing and provide better guidance on food selection. |
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| Keywords: | PSO-BP neural network Particle swarm optimization Stomach nourishing recipe |
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