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Multi-level fuzzy comprehensive evaluation of the influence of reservoir sedimentation based on improved cloud model
Author(s) -
Mingwang Zhang,
Kebin Shi
Publication year - 2021
Publication title -
water science and technology water supply
Language(s) - English
Resource type - Journals
eISSN - 1607-0798
pISSN - 1606-9749
DOI - 10.2166/ws.2021.190
Subject(s) - sedimentation , weighting , cloud computing , grasp , fuzzy logic , computer science , petroleum engineering , geology , data mining , artificial intelligence , geomorphology , sediment , medicine , radiology , programming language , operating system
The extent of reservoir sedimentation is an important index related to the functional operation of reservoirs. Therefore, it is vital to accurately conduct sedimentary assessment. In this paper, the analytic hierarchy process was used to determine subjective weights, gray correlation analysis and entropy weight method were used to determine objective weights. The combination weights obtained using optimized combination weighting method based on genetic algorithm were more suitable for the comprehensive analysis of the impact of reservoir sedimentation. This was then used to constructed a multi-level fuzzy comprehensive evaluation model based on improved cloud model. A reservoir was selected as the study object, and its sedimentation impact level was evaluated: the numerical characteristics of the stratus cloud of the comment on the impact of the reservoir sedimentation were (0.6372, 0.0664, 0.0795). The results showed that the reservoir sedimentation is considered as severe influence, and the sedimentation has become a major problem that needed to be solved urgently. The results of this paper could provide insight for reservoir research domestically and abroad. Furthermore, it could also enable managers to more accurately grasp the severity of reservoir sedimentation.

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