Applications of Artificial Neural Network to Hydrology and Water Resources
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摘要: 人工神经网络理论被广泛地应用于水文水资源领域中各种问题的研究,依问题性质不同将其划分为4大类:(1)分类和识别问题;(2)预测预报问题;(3)优化计算问题;(4)基于神经网络的专家系统研制与开发问题,对人工神经网络在水文水资源中的应用现状作了较全面的介绍。还指出了目前应用中存在的主要问题以及今后的研究方向。Abstract: Many application researches of artificial neural networks (ANN)have been made in hydrology and water resources. The state-of-the-art of ANN as applied to hydrology and water resources has been examined and evaluated through four classified problems,those are(1)pattern recognition,(2) prediction,(3) optimization,and (4)ANN-based expert system. The major problems and directions for the future studies are presented in this paper.
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Key words:
- Artificial neural network /
- hydrology /
- water resources
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[1] 吴晓.人工神经网络在暴雨预报中的应用.智能控制与智能自动化.北京:科学出版社,1993.817-822 [2] 蔡煌东,许伟杰.自组织人工神经网络在都阳湖年最高水位长期预报中的应用.水文科技情报.1993,10 (2):27-29 [3] 胡铁松,丁晶.径流分级预报的人工神经网络方法研究,全国首届水文水资源与水环境科学不确定性研究新理论新方法学术讨论会论文集.成都:成都科技大学出版社,1994. 150-156 [4] S Ranjithan,J W Eheart and J H Garrett Jr. Neural networtk-based screeing for ground water reclamation under uncertainty. Water Resources Research. 1993,29 (3):563-574 [5] Hsiang-Te Kung, L Yulin,S Malawi. Precipitation pattern study using artificial neural networks. Proceedings of international symposium,on impact of climatic change global warming on hydrology and water resources,China,1993. 72-82 [6] MLZhu,M Fujita,and N. Hashimoto. Application of neural networks to runoff prediction. International conference on stochastic and statisticial methods in hydrology and enviromental engineering. Ontario. Canada. 1993,205-216 [7] S P Zhang, H Watanabe and R Yamada. Prediction of daily water demands by neural networks. International conference on stochastic and statisticial methods in hydrology and enviromental engineering. Ontario. Canada. 1993, 217-227 [8] G L Macher and J D Fuller. Backpropagation in hydrological time series forecasting. International conference on stochastic and statisiticial methods in hydrology and enviromental engineering. Ontario. Canada. 1993, 229-242 [9] A S Weigend, D E Rumelhart and B A Huberman. Predicting of the future:a connectionist approach. International Journal of Neural Systems, 1990, 1 (3):193-290 [10] K Y Lee. Y T Cha and J H Park. Short-term load forecasting using an artificial neural networks. IEEE Transactions on Power System, 1992, 7 (1):124-132 [11] 韦柳涛,梁年生,虞锦江.神经网络理论在梯级水电厂短期优化调度中的应用.水电能源科学,1992, 10 (3):145-151 [12] Palmer R N and K J Holems. Operational guidance during droughts:expert system. Journal of Water Resources Planning and Management. 1988, 114 (6):647-665 [13] Y Y Yin and X M Xu,Applying neural networks technology for multiobjective land use planning. Journal of Enviromental Management. 1991,32: 349-356 [14] Tiesong Hu etc. Multireservoir operations using an artificial neural network. International sympoisum on medium and small sized hydropower stations. China,1993. 114-117 [15] Hirose Y, K Yamashite and S Hijiya. Back-propagation algorithm which varies the number of hidden units. Neural Networks. 1991,4 (1):61-66 [16] Karnina. E. D. A simple procedure for pruning back-propagation trained neural networks.IEEE Transactions on Neural Networks. 1990, 1 (2):239-242 -

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