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Prediction Model of Water Resources in Mine Area Based on Phase Space Reconstruction and Chaos Neural Network

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Advances in Computation and Intelligence (ISICA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5370))

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Abstract

In the process of social economic development, water resource is increasingly scarce because of unreasonable exploitation of groundwater resources. It has seriously hampered the economic and social development speed in mine area, and even caused a series of negative effects of serious environmental and ecological problems. In this paper, chaos theory is used to study the water resource system in mine area. By analyzing the phenomena of chaotic characteristics in water resource system, regional mine water resources safety model was constructed based on the phase space reconstruction coupled with the neural network. Through the application of the model to forecast future water resources consumption in Gejiu mine area, the predicted results not only verified the validity of the model, but also found a new approach to study water resources in mine area.

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Author information

Authors and Affiliations

  1. School of Resources and Safety Engineering, Central South University, 410083, Changsha, China

    Keping Zhou, Ge Gao & Feng Gao

  2. Yunnan Tin Industry Group Company, 661000, Gejiu, China

    Wenxiang Gao

Authors
  1. Keping Zhou
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  2. Ge Gao
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  3. Feng Gao
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  4. Wenxiang Gao
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Editor information

Editors and Affiliations

  1. Computation Center, Wuhan University, 430072, Wuhan, China

    Lishan Kang

  2. Faculty of Computer Science, China University of Geosciences, 430074, Wuhan, Hubei, P.R. China

    Zhihua Cai

  3. School of Computer Science, China University of Geosciences, Wu-Han, 430074, China Research Center for Space Science and Technology, China University of Geosciences, 430074, Wu-Han, China

    Xuesong Yan

  4. The University of Aizu, Tsuruga, Ikki-machi, 965-8580, Aizu-Wakamatsu City Fukushima, Japan

    Yong Liu

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© 2008 Springer-Verlag Berlin Heidelberg

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Zhou, K., Gao, G., Gao, F., Gao, W. (2008). Prediction Model of Water Resources in Mine Area Based on Phase Space Reconstruction and Chaos Neural Network. In: Kang, L., Cai, Z., Yan, X., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2008. Lecture Notes in Computer Science, vol 5370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92137-0_36

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  • DOI: https://doi.org/10.1007/978-3-540-92137-0_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92136-3

  • Online ISBN: 978-3-540-92137-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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