scholarly journals The Risk Assessment of Debris Flow Hazards in Banshanmen Gully Based on the Entropy Weight-Normal Cloud Method

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
X. B. Gu ◽  
S. T. Wu ◽  
X. J. Ji ◽  
Y. H. Zhu
Keyword(s):  
Risk Assessment ◽  
Debris Flow ◽  
Cloud Model ◽  
Risk Estimation ◽  
Assessment Method ◽  
Risk Level ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Index Weight

The debris flow is one of the geological hazards; its occurrence is complex, fuzzy, and random. And it is affected by many indices; a new multi-index assessment method is proposed to analyze the risk level of debris flow based on the entropy weight-normal cloud model in Banshanmen gully. The index weight is calculated by using the entropy weight method. Then, the certainty degree of each index belonging to the corresponding cloud is obtained by using the cloud model. The final risk level of debris flow is determined according to the synthetic certainty degree. The conclusions are drawn that the method is feasible and accurate rate of risk estimation for debris flow is very high, so a new method and thoughts for the risk assessment of debris flow can be provided in the future.

scholarly journals Risk assessment of floodwater resources utilization in water transfer projects based on an improved cloud model

2019 ◽  
Vol 19 (8) ◽  
pp. 2517-2532 ◽  
Author(s):  
Xianfeng Huang ◽  
Wanyu Li ◽  
Yingqin Chen ◽  
Guohua Fang ◽  
Wei Yan
Keyword(s):  
Risk Assessment ◽  
Cloud Model ◽  
Projection Pursuit ◽  
Assessment Method ◽  
Water Transfer ◽  
Water Diversion ◽  
Low Flow ◽  
Risk Level ◽  
Membership Degree ◽  
Entropy Weight

Abstract The utilization of floodwater resources will produce benefits, but it will also pose risks; therefore, it is necessary to strengthen knowledge regarding risk assessment to minimize negative effects. In the present study, the risk factors for the utilization of floodwater resources in water diversion projects were identified, the index system was constructed, and the fuzziness and randomness of the risk were considered. Assessment was performed with respect to the following three projects: water storage, water conveyance, and water pumping. The specific methods to improve the cloud model are as follows: analytic hierarchy process (AHP) is used to calculate subjective weights, entropy weight method and projection pursuit method are used to calculate objective weights, X-conditional cloud is used to calculate index membership degree, and finally combination weight and membership degree are combined to obtain the risk level of flood resource utilization. The above methodology was applied to the risk assessment of floodwater resources utilization in the Jiangsu Province of the East Route of the South-to-North Water Transfer Project. The risk of floodwater resources utilization in high-flow, normal-flow, and low-flow years was evaluated, and the validity and applicability of the assessment method were verified.

Synthetic Risk Assessment of Catastrophic Failures in Power System Based on Entropy Weight Method

2012 ◽  
Vol 446-449 ◽  
pp. 3015-3018 ◽  
Author(s):  
Jing Feng ◽  
Ying Wang ◽  
Xian Yong Xiao
Keyword(s):  
Risk Assessment ◽  
Power System ◽  
Severity Index ◽  
Assessment Method ◽  
Entropy Weight ◽  
Event Sequences ◽  
Risk Assessment Method ◽  
Catastrophic Failures ◽  
Entropy Weight Method ◽  
Weight Method

The synthetic risk assessment method incorporating the severity and the possibility is used to identify the catastrophic event sequences in power system. The weight setting of each severity index is determined by the proposed entropy weight method. Comparing with traditional methods, the entropy weight method can determine the weight coefficients objectively. The simulation results for the WSCC-9 buses system have proved the validity of the proposed method. This method can be used in the practice power system.

scholarly journals Assessment of the Ecological Niche of Photovoltaic Agriculture in China

2019 ◽  
Vol 11 (8) ◽  
pp. 2268 ◽  
Author(s):  
Wang ◽  
Wang ◽  
Chen
Keyword(s):  
Ecological Niche ◽  
Cloud Model ◽  
Development Trend ◽  
Evaluation Index System ◽  
Entropy Weight ◽  
Interval Numbers ◽  
Good State ◽  
Entropy Weight Method ◽  
Weight Method ◽  
The Development Trend

To evaluate the ecological niche of photovoltaic agriculture in China, an evaluation index system was constructed. Based on the presentation form of interval numbers, we used the interval entropy weight method and interval cloud model to measure the niche state value and niche role value of photovoltaic agriculture. In this way, we determined the development trend of the ecological niche of photovoltaic agriculture. The results show that Chinese photovoltaic agriculture is in a good state and plays a good, but weak, role. The ecological niche of China’s photovoltaic agriculture will undergo a four-stage evolution process: positioning, integration, leap, and symbiosis. China has completed the positioning stage and entered the integration stage. Hence, it is important to constantly improve the level of industrial integration technology and to form a new photovoltaic agriculture recycling economic ecosystem.

scholarly journals Application of TOPSIS Method Based on Entropy Weight -Delphi in the Evaluation of Teachers’ “double-qualified” Ability

2020 ◽  
Vol 165 ◽  
pp. 06050
Author(s):  
Weixia Wang ◽  
He Jun
Keyword(s):  
Evaluation System ◽  
Evaluation Model ◽  
Topsis Method ◽  
Entropy Weight ◽  
Chinese Library Classification ◽  
Evaluation Indexes ◽  
Energy Evaluation ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Index Weight

In order to improve the rationality and fairness of Teachers’ “Double-qualified” Ability, the article establishes an evaluation model based on 14 evaluation indexes of teachers’ “double-qualified” ability. it adopts Delphi - entropy weight method to weight the evaluation index, and then combines TOPSIS method to evaluate the evaluation object. In the evaluation of TOPSIS method, the traditional TOPSIS weight method was improved, and the entropy weight-delphi method was used to determine the index weight, which was a combination of subjective and objective, making the evaluation system more objective, scientific and reasonable.It not only avoids the subjectivity of decision makers and limitations, but also eliminates the phenomenon of indexes in common impact assessment results and finally applies it to a university teacher “Double division and triple energy” evaluation system, to provide theoretical basis and feasibility analysis for the “double type” teachers team construction. Chinese library classification number: O224 Document identification code: A

scholarly journals Effectiveness of Entropy Weight Method in Decision-Making

2020 ◽  
Vol 2020 ◽  
pp. 1-5 ◽  
Author(s):  
Yuxin Zhu ◽  
Dazuo Tian ◽  
Feng Yan
Keyword(s):  
Decision Making ◽  
Water Source ◽  
Entropy Weight ◽  
Weighting Method ◽  
Numerical Discrimination ◽  
Differentiation Degree ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Degree Of Differentiation ◽  
Index Weight

Entropy weight method (EWM) is a commonly used weighting method that measures value dispersion in decision-making. The greater the degree of dispersion, the greater the degree of differentiation, and more information can be derived. Meanwhile, higher weight should be given to the index, and vice versa. This study shows that the rationality of the EWM in decision-making is questionable. One example is water source site selection, which is generated by Monte Carlo Simulation. First, too many zero values result in the standardization result of the EWM being prone to distortion. Subsequently, this outcome will lead to immense index weight with low actual differentiation degree. Second, in multi-index decision-making involving classification, the classification degree can accurately reflect the information amount of the index. However, the EWM only considers the numerical discrimination degree of the index and ignores rank discrimination. These two shortcomings indicate that the EWM cannot correctly reflect the importance of the index weight, thus resulting in distorted decision-making results.

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