Set pair analysis and BP neural network coupling model for optimal selection of flood control operation

2010 ◽  
Author(s):  
Chengguo Wu ◽  
Yimin Wang ◽  
Juliang Jin ◽  
Yiming Wei ◽  
Qiang Huang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Flood Control ◽  
Coupling Model ◽  
Optimal Selection ◽  
Set Pair Analysis ◽  
Control Operation ◽  
Flood Control Operation ◽  
Pair Analysis ◽  
Selection Of

scholarly journals Selection of criteria for multi-criteria decision making of reservoir flood control operation

2017 ◽  
Vol 19 (4) ◽  
pp. 558-571 ◽  
Author(s):  
Feilin Zhu ◽  
Ping-an Zhong ◽  
Yimeng Sun ◽  
Bin Xu
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Flood Control ◽  
Relative Importance ◽  
Contribution Ratio ◽  
Control Operation ◽  
Relative Contribution ◽  
Flood Control Operation ◽  
Reservoir Flood Control Operation ◽  
Selection Of

In reservoir flood control operation, selection of criteria is an important part of the multi-criteria decision making (MCDM) procedure. This paper proposes a method to select criteria for MCDM of reservoir flood control operation based on the back-propagation (BP) neural network. According to the concept of ideal and anti-ideal points, we propose a method to generate training samples of the BP neural network via stochastic simulation. The topological structure of a three-layer BP neural network used for criteria selection is established. The relative importance of criteria is derived via the learned connection weights of a trained BP neural network, and its calculation method is proposed. The sensitivity curve method is employed to conduct sensitivity analysis, and the relative contribution ratio is defined to quantify the relative sensitivity strength of each criterion. We present the principle and threshold value of criteria selection based on the comprehensive discrimination index defined by the combination of the relative importance and relative contribution ratio. The Pubugou reservoir is selected as the case study. The results show that the proposed method can provide an effective tool for decision makers to select criteria before MCDM modeling of reservoir flood control operation.

Forewarning of sustainable utilization of regional water resources: a model based on BP neural network and set pair analysis

2011 ◽  
Vol 62 (1) ◽  
pp. 115-127 ◽  
Author(s):  
Ju-Liang Jin ◽  
Yi-Ming Wei ◽  
Le-Le Zou ◽  
Li Liu ◽  
Wei-wei Zhang ◽  
...  
Keyword(s):  
Neural Network ◽  
Water Resources ◽  
Bp Neural Network ◽  
Sustainable Utilization ◽  
Set Pair Analysis ◽  
Model Based ◽  
Pair Analysis ◽  
Regional Water

An evaluating model for smart growth plan based on BP neural network and set pair analysis

2019 ◽  
Vol 226 ◽  
pp. 928-939 ◽  
Author(s):  
Rui Zhang ◽  
Yan Wang ◽  
Kaibo Wang ◽  
Huiyang Zhao ◽  
Shuo Xu ◽  
...  
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Smart Growth ◽  
Set Pair Analysis ◽  
Pair Analysis

scholarly journals Research and Development of Flood Control Operation System of Beijing City, China

10.29007/k3d3 ◽  
2018 ◽  
Author(s):  
Chai Fuxin ◽  
Liu Shu ◽  
Hu Changwei ◽  
Zhang Hongping
Keyword(s):  
Flood Control ◽  
Coupling Model ◽  
Beijing City ◽  
Operation System ◽  
Control Operation ◽  
Open Design ◽  
Database Technology ◽  
Hydrodynamic Method ◽  
Flood Control Operation ◽  
Real Time Information

Assembling all the data of weather, rainfall, hydrology, engineering, water logging and other real-time information and basic information of the Beijing, the flood forecasting coupling model with hydrological and hydrodynamic method and the operation model of gate and dam are constructed. Obeying object-oriented open design concept, Beijing flood control operation system based on B/S framework is developed, using Java language and database technology, which has achieved these functions that the analysis of flood control situation, flood forecast, flood control operation, flood simulation, evaluation of regulation results and scheduling management etc. At the same time, the mobile application client is developed by using html5 technology, with the functions of flood information query, mobile patrol and dangerous case report etc. All these can provide the decision-making basis for the integrated flood control management of Beijing city.

scholarly journals Risk Assessment and Decision-Making Based on Mean-CVaR-Entropy for Flood Control Operation of Large Scale Reservoirs

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 649 ◽  
Author(s):  
Quansen Wang ◽  
Jianzhong Zhou ◽  
Kangdi Huang ◽  
Ling Dai ◽  
Gang Zha ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Flood Control ◽  
Large Scale ◽  
Yangtze River Basin ◽  
Mean Value ◽  
Operation System ◽  
Control Operation ◽  
Flood Control Operation ◽  
Reservoir Flood Control Operation

The risk inevitably exists in the process of flood control operation and decision-making of reservoir group, due to the hydrologic and hydraulic uncertain factors. In this study different stochastic simulation methods were applied to simulate these uncertainties in multi-reservoir flood control operation, and the risk caused by different uncertainties was evaluated from the mean value, extreme value and discrete degree of reservoir occupied storage capacity under uncertain conditions. In order to solve the conflict between risk assessment indexes and evaluate the comprehensive risk of different reservoirs in flood control operation schemes, the subjective weight and objective weight were used to construct the comprehensive risk assessment index, and the improved Mahalanobis distance TOPSIS method was used to select the optimal flood control operation scheme. The proposed method was applied to the flood control operation system in the mainstream and its tributaries of upper reaches of the Yangtze River basin, and 14 cascade reservoirs were selected as a case study. The results indicate that proposed method can evaluate the risk of multi-reservoir flood control operation from all perspectives and provide a new method for multi-criteria decision-making of reservoir flood control operation, and it breaks the limitation of the traditional risk analysis method which only evaluated by risk rate and cannot evaluate the risk of the multi-reservoir flood control operation system.

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