scholarly journals Risk Identification and Assessment during the Excavation of the Deep Foundation Pit

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Guowang Meng ◽  
Xiang Li ◽  
Hao Liu ◽  
Bo Wu ◽  
Yi Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Assessment Model ◽  
Risk Level ◽  
Fuzzy Decision Making ◽  
Entropy Weight ◽  
Deep Foundation ◽  
Foundation Pit ◽  
Entropy Weight Method ◽  
Weight Method

This study presents a new model for identifying and evaluating high-risk factors in foundation pit excavation. The model combines the fuzzy decision-making trial and the evaluation laboratory (FDEMATEL), the entropy weight method, and the multiattributive border approximation area comparison (MABAC) method. Firstly, the risk factors such as geology, surrounding environment, monitoring, construction, and management are studied in detail. Secondly, the subjective weight is calculated by the fuzzy DEMATEL method, and the objective weight is calculated by the entropy weight method. Then, the MABAC method is introduced to identify the key risk factors of the foundation pit and the risk level of foundation pit construction. Finally, Jinan Rail Transit R2 Line Kaiyuan Road Station is used as a case study for analysis based on the risk assessment model. The results show that the model can identify key risk factors in different construction stages of foundation pits, which can provide guidance for risk management decision-making.

scholarly journals Decision-Making of Irrigation Scheme for Soybeans in the Huaibei Plain Based on Grey Entropy Weight and Grey Relation–Projection Pursuit

Entropy ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 877 ◽  
Author(s):  
Yi Cui ◽  
Shangming Jiang ◽  
Juliang Jin ◽  
Ping Feng ◽  
Shaowei Ning
Keyword(s):  
Decision Making ◽  
Water Consumption ◽  
Projection Pursuit ◽  
Crop Water ◽  
Irrigation Scheme ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Projection Pursuit Model ◽  
Grey Relation

To provide a scientific reference for formulating an effective soybean irrigation schedule in the Huaibei Plain, potted water deficit experiments with nine alternative irrigation schemes during the 2015 and 2016 seasons were conducted. An irrigation scheme decision-making index system was established from the aspects of crop water consumption, crop growth process and crop water use efficiency. Moreover, a grey entropy weight method and a grey relation–projection pursuit model were proposed to calculate the weight of each decision-making index. Then, nine alternative schemes were sorted according to the comprehensive grey relation degree of each scheme in the two seasons. The results showed that, when using the entropy weight method or projection pursuit model to determine index weight, it was more direct and effective to obtain the corresponding entropy value or projection eigenvalue according to the sequence of the actual study object. The decision-making results from the perspective of actual soybean growth responses at each stage for various irrigation schemes were mostly consistent in 2015 and 2016. Specifically, for an integrated target of lower water consumption and stable biomass yields, the scheme with moderate-deficit irrigation at the soybean branching stage or seedling stage and adequate irrigation at the flowering-podding and seed filling stages is relatively optimal.

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 Integrated energy service demand evaluation based on AHP and entropy weight method

2020 ◽  
Vol 185 ◽  
pp. 01046
Author(s):  
Xianjun Qi ◽  
Mucong Zhou
Keyword(s):  
Clustering Algorithm ◽  
Rapid Development ◽  
Assessment Model ◽  
Entropy Weight ◽  
Analytic Hierarchy ◽  
Energy Services ◽  
Energy Service Demand ◽  
Entropy Weight Method ◽  
Energy Service ◽  
Weight Method

In the context of the energy revolution, integrated energy services have ushered in a period of opportunities for rapid development. To assess the demand of users of integrated energy services, we establish indexes of demand of integrated energy service users. We got the assessment model based on the analytic hierarchy process (AHP) and entropy weight method. The proposed assessment model is tested on 50 users, and K-means clustering algorithm is used to cluster users. The characteristics of the service requirements of each type are analysed.

scholarly journals A Method of Determining Multi-Attribute Weights Based on Single-Valued Neutrosophic Numbers and Its Application in TODIM

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 506 ◽  
Author(s):  
Dongsheng Xu ◽  
Yanran Hong ◽  
Kaili Xiang
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Entropy Weight ◽  
Attribute Weights ◽  
Attribute Weight ◽  
Decision Making Problem ◽  
Entropy Weight Method ◽  
Todim Method ◽  
Multi Attribute Decision Making ◽  
Weight Method

In this paper, the TODIM method is used to solve the multi-attribute decision-making problem with unknown attribute weight in venture capital, and the decision information is given in the form of single-valued neutrosophic numbers. In order to consider the objectivity and subjectivity of decision-making problems reasonably, the optimal weight is obtained by combining subjective weights and objective weights. Subjective weights are given directly by decision makers. Objective weights are obtained by establishing a weight optimization model with known decision information, then this method will compare with entropy weight method. These simulation results also validate the effectiveness and reasonableness of this proposed method.

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.

scholarly journals Investment Risk Assessment of Dispersed Wind Power in Low Wind Speed Area Using a Hybrid Multi-Criteria Decision-Making Approach Based on Hesitant Fuzzy Linguistic Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Lingyun Liu ◽  
Jianli Zhou ◽  
Haoxin Dong ◽  
Yao Tao ◽  
Yunna Wu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Decision Making ◽  
Wind Speed ◽  
Risk Analysis ◽  
Wind Power ◽  
Assessment Model ◽  
Risk Level ◽  
Low Wind Speed ◽  
Fuzzy Linguistic

Reducing the phenomenon of wind curtailment is essential to improve the level of wind power consumption. Wind power development in China has shifted to southeast region and dispersed wind power has developed rapidly and gradually become the new main force. However, various obstacles limit the smooth progress of dispersed wind power in low wind speed area. An important point is the absence of targeted risk analysis and evaluation methods. Therefore, the principal contribution of this paper is to find out the critical risk factors of such projects and propose the risk assessment model. First, 18 critical risk factors are identified using the constructed five-dimensional risk analysis model. Second, the hesitant fuzzy linguistic term set with credibility is utilized to collect evaluation information on one hand and to improve the multicriteria decision-making methods involved on the other hand. Third, the risk evaluation and ranking for 10 provinces that mainly develop dispersed wind power is carried out. The evaluation results indicate that the risk level of dispersed wind power projects is “Relatively Low” in most study provinces and the risk levels of Guangdong and Fujian are higher. It is worth noting that the consistency between the evaluation results and the distribution of wind resources can be used to guide the formulation of stimulus policies. Besides, the ranking results show some preference for investment choice. Finally, dual sensitivity analysis tests the stability of the model and shows the ranking results under different decision preferences. Scenario analysis gives the possible risk scenarios and evaluation results in the future. This study can provide insightful inspiration to wind power investors, risk management practitioners, and policymakers.

scholarly journals New Uncertainty Measure of Rough Fuzzy Sets and Entropy Weight Method for Fuzzy-Target Decision-Making Tables

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Huani Qin ◽  
Darong Luo
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Theoretical Studies ◽  
Uncertainty Measure ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Rough Fuzzy Set ◽  
Fuzzy Target

In the rough fuzzy set theory, the rough degree is used to characterize the uncertainty of a fuzzy set, and the rough entropy of a knowledge is used to depict the roughness of a rough classification. Both of them are effective, but they are not accurate enough. In this paper, we propose a new rough entropy of a rough fuzzy set combining the rough degree with the rough entropy of a knowledge. Theoretical studies and examples show that the new rough entropy of a rough fuzzy set is suitable. As an application, we introduce it into a fuzzy-target decision-making table and establish a new method for evaluating the entropy weight of attributes.

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