An optimized approach based on neural network and control theory to estimate hydro-geological parameters

Chih Yung Hung, Cheng Haw Lee

研究成果: Conference contribution

摘要

In the past, typical approaches simulating the groundwater flow are based on continuous trials to approach to the targeted measurement accuracy. In this study, we propose a new neural network based on feedback observer technique to estimate the hydro-geological structure and hydraulic parameters of a large-scale alluvial fan in Taiwan. We develop an under-ground water level observer (UGW-LO) based on feedback control theory to simulate the dynamics of groundwater levels and estimate water levels of wells in the large area. In the proposed observer system, a large-scale back-propagation neural network (BPNN) is proposed to simulate water levels dynamics of multiple wells. The simulation results are fed back as a reference for BPNN to approach to refine estimation. Based on that model, a groundwater flow is simulated correctly by software MODFLOW. Experimental results indicate that the innovative method works better than conventional regression estimations. The learning ability of BPNN also contributes to overcome the gap between legacy dynamics UGW equations and real UGW dynamics. The applicability and precision are verified in a large scale experiment that is beneficial to the management of underground waters and reduce the risk of ground-sink.

原文English
主出版物標題Modern Advances in Applied Intelligence - 27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014, Proceedings
編輯Moonis Ali, Shyi-Ming Chen, Jeng-Shyang Pan, Mong-Fong Horng
發行者Springer Verlag
頁面170-177
頁數8
ISBN(電子)9783319074542
出版狀態Published - 2014 一月 1
事件27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014 - Kaohsiung, Taiwan
持續時間: 2014 六月 32014 六月 6

出版系列

名字Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
8481
ISSN(列印)0302-9743

Conference

Conference27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014
國家Taiwan
城市Kaohsiung
期間14-06-0314-06-06

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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