| 优化进化神经网络的空气质量预测研究 |
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| 引用本文： | 张齐,罗国亮,李佳,赵坤荣. 优化进化神经网络的空气质量预测研究[J]. 计算机工程与应用, 2009, 45(28): 211-214. DOI: 10.3778/j.issn.1002-8331.2009.28.064 |
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| 作者姓名： | 张齐 罗国亮 李佳 赵坤荣 |
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| 作者单位： | 华南理工大学,计算机科学与工程学院,广州,510006;环境保护部,华南环境科学研究所,广州,510655 |
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| 基金项目： | 广东省科技计划项目，广州市科技攻关计划项目 |
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| 摘 要： | 进化神经网络模型与问题内部机制无关，避免了神经网络收敛到局部，但模型存在参数多而过于复杂的问题。对影响基本进化神经网络模型性能的个体编码方式和适应度函数进行优化，并自适应性定义种群交叉率、变异率。以大气中主要污染物SO2为例，考虑气温、相对湿度、风速等影响因子，实验仿真结果表明优化后的进化神经网络较传统的基本进化神经网络模型进化过程收敛更快，预测效果更佳，为环境保护部门提供可靠的决策依据。
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| 关 键 词： | 进化神经网络 污染源 预测 |
| 收稿时间： | 2009-03-30 |
| 修稿时间： | 2009-5-20 |
Research of forecasting of air quality based on optimization of Evolutionary Neural Network |
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| ZHANG Qi,LUO Guo-liang,LI Jia,ZHAO Kun-rong. Research of forecasting of air quality based on optimization of Evolutionary Neural Network[J]. Computer Engineering and Applications, 2009, 45(28): 211-214. DOI: 10.3778/j.issn.1002-8331.2009.28.064 |
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| Authors: | ZHANG Qi LUO Guo-liang LI Jia ZHAO Kun-rong |
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| Affiliation: | 1.College of Computer Science and Engineering，South China University of Technology，Guangzhou 510006，China 2.South China Institute of Environment Science，National Bureau of Environmental Protection，Guangzhou 510655，China |
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| Abstract: | Evolutionary Neural Network（ENN） does not concern problems’ internal mechanism，avoids the convergence to local brought by neural network model，but the ENN model is complicated because of too many parameters.This paper optimizes the Simple ENN（SENN） with individual encoding，fitness function，and develops self-adaptive crossing rate and mutation rate of the species，which are main factors that influence the performance of the ENN.Simulation of the concentration that SO2 contained in the air with its impact factors and the historical data shows that Optimized ENN（OENN） converges faster in the evolution process than the SENN，and performs better in the forecasting.The OENN model can be capable to supply valuable prediction data for environmental protection. |
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| Keywords: | Evolutionary Neural Network（ENN） pollution sources prediction |
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