Water Saving Irrigation Decision-Making Method based on Big Data Fusion

doi:10.23940/ijpe.19.11.p10.29162926

Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (11): 2916-2926.doi: 10.23940/ijpe.19.11.p10.29162926

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Water Saving Irrigation Decision-Making Method based on Big Data Fusion

Xiaojuan Zhang^*, Feng Zhang, Yongheng Zhang, and Xiaoyan Ai

School of Energy Engineering, Yulin University, Yulin, 719000, China

Submitted on ; Revised on ; Accepted on
Contact: * E-mail address: 718679225@qq.com
About author:Xiaojuan Zhang received her M.S. degree in computer science from Beijing Normal University in 2007. She is currently a lecturer at Yulin University. Her research interests include management systems and decision support, large data analysis, and data modeling and mining.Feng Zhang received his M.S. degree in computer science from Xidian University and his Ph.D. from Northwestern Polytechnical University. He is currently a professor at Yulin University. His research interests include cloud integrated manufacturing technology, modeling of complex systems, and Internet of things applications.Yongheng Zhang received his M.S. degree in computer science from Xidian University in 2010. He is currently a professor at Yulin University. His research interests include data mining technology and mass data processing technology.Xiaoyan Ai received his M.S. degree in computer science from Xidian University in 2010. He is currently a professor at Yulin University. His research interests include modeling of complex systems and Internet of things applications.

Abstract

Abstract: In order to realize the intelligence of irrigation management and the wisdom of irrigation decision-making, improve the efficiency of water resource utilization, and introduce information fusion technology into the field of farmland irrigation, an irrigation decision-making method based on multi-source information fusion is proposed. Firstly, according to the actual situation and specific needs of the study area, the multi-objective irrigation water quantity optimization configuration model is constructed, and the multi-objective intelligent algorithm is used to solve the model. Then, using the adaptive weighted average fusion algorithm, the weight coefficient of soil moisture of millet in different growth stages and different soil layers is constructed, and the fusion of soil moisture in the data layer is realized. Finally, in order to meet different irrigation requirements, the multi-objective particle algorithm is used to solve the multi-object canal optimal water allocation model based on the optimized configuration of irrigation water volume. The experimental results show that the fusion results obtained by the multi-source large data adaptive weighted fusion algorithm are more reasonable, the uncertainty of irrigation decision-making is greatly reduced, the reliability of irrigation decision-making is improved, and the water consumption can be saved by 25.61% by using the multi-objective optimal allocation model.

Key words: decision-making, big data fusion, irrigation water resources, optimized configuration, multi-source information fusion

Xiaojuan Zhang, Feng Zhang, Yongheng Zhang, and Xiaoyan Ai. Water Saving Irrigation Decision-Making Method based on Big Data Fusion [J]. Int J Performability Eng, 2019, 15(11): 2916-2926.

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Water Saving Irrigation Decision-Making Method based on Big Data Fusion

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