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Forecasting Industrial Water Demand Using Case-Based Reasoning: A Case Study in Zhangye City, China

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River Basin Management

Part of the book series: Ecohydrology ((ECOH))

Abstract

Forecasting the industrial water demand accurately is crucial for sustainable water resource management. This study investigates industrial water demand forecasting by case-based reasoning (CBR) in an arid area, with a case study of Zhangye City, China. CBR uses past experience to solve new problems. Since CBR is a methodology rather than a technique, this definition makes case-based reasoning system be an open system, which can constantly absorb new technologies and methods, and be more conducive to the development of itself. This research constructed a case base with 420 original cases of 28 cities in China, extracted six attributes of the industrial water demand, and employed a back propagation neural network (BPN) to weight each attribute, as well as the grey incidence analysis (GIA) to calculate the similarities between target case and original cases. The forecasting values were calculated by weighted similarities. The results show that the industrial water demand of Zhangye in 2030, which is the target case, will reach 11.9 million tons. There are ten original cases which have relatively high similarities to the target case. Furthermore, the case of Yinchuan, 2010, has the largest similarity, followed by Yinchuan, 2009, and Urumqi, 2009. This research also made a comparison experiment in which CBR is more accurate than the grey forecast model and back propagation neural network in water demand forecasting. It is expected that the results of this study will provide references to water resources management and planning.

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Authors and Affiliations

  1. College of Public Administration, Huazhong Agricultural University, Wuhan, China

    Bohan Yang, Weiwei Zheng & Xinli Ke

Authors
  1. Bohan Yang
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  2. Weiwei Zheng
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  3. Xinli Ke
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Corresponding author

Correspondence to Xinli Ke .

Editor information

Editors and Affiliations

  1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Xiangzheng Deng

  2. Department of Economics, Waikato Management School, The University of Waikato, Hamilton, Waikato, New Zealand

    John Gibson

Appendix

Appendix

See Table A1.

Table A1 Similarities between Original Cases and the Target Case (Industrial Water Demand of Zhangye in 2030) (Reprinted from Yang et al. (2017) with permission of Water)
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Yang, B., Zheng, W., Ke, X. (2019). Forecasting Industrial Water Demand Using Case-Based Reasoning: A Case Study in Zhangye City, China. In: Deng, X., Gibson, J. (eds) River Basin Management. Ecohydrology. Springer, Singapore. https://doi.org/10.1007/978-981-10-6949-9_10

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