The Evaluation of Drought Degree in Irrigation District Based on Variable Fuzzy Evaluation Method

2012 ◽  
Vol 212-213 ◽  
pp. 731-738
Author(s):  
Dan Liu ◽  
Ben De Wang
Keyword(s):  
Fuzzy Sets ◽  
Evaluation Method ◽  
Entropy Method ◽  
Irrigation District ◽  
Fuzzy Evaluation ◽  
Discrimination Information ◽  
The One ◽  
Sets Theory ◽  
Minimum Discrimination Information ◽  
Variable Fuzzy Sets

In view of the disadvantages of drought evaluation methods in irrigation district, the variable fuzzy sets theory has been adopted in this paper to establish the variable fuzzy sets drought evaluation method in irrigation district. At the same time, the improved entropy method has been employed to determine the objective weights and the minimum discrimination information principle has been used to combine the subjective weights with the objective weights, which have eliminated the one-sidedness of the application of a single weighting preferred program.

A New Improved Entropy Method and its Application in Power Quality Evaluation

2013 ◽  
Vol 706-708 ◽  
pp. 1726-1733 ◽  
Author(s):  
Sen Ouyang ◽  
Zi Wen Liu ◽  
Qing Li ◽  
Yi Li Shi
Keyword(s):  
Power Quality ◽  
Evaluation Method ◽  
Rank Correlation ◽  
Calculation Model ◽  
Entropy Method ◽  
Entropy Weight ◽  
Bp Network ◽  
Efficient Performance ◽  
Entropy Weight Method ◽  
The One

This paper puts forward a new improved entropy method, which fixes the problem of traditional entropy weight method that entropy weights present the wrong message of entropy when all the entropy values are close to 1. The proposed method achieved efficient performance by designing calculation model of BP network. Firstly, the synthesis weights of power quality indexes were calculated by rank correlation analysis and the improved entropy method, which avoids the one-sidedness of subjective or objective. And the quantitative values of multi-index were obtained. Then a calculation model of BP network to realize this evaluation method is designed in this paper, making it more efficient and more practical. Finally, the evaluation of a power supply bureau has verified the effectiveness of the proposed method.

Research on Reliability Allocation Method for NC Grinding Machine

2014 ◽  
Vol 599-601 ◽  
pp. 1244-1248
Author(s):  
Hang Hong He
Keyword(s):  
Entropy Method ◽  
Analysis Method ◽  
Reliability Allocation ◽  
Interval Analysis Method ◽  
Multiple Factors ◽  
Allocation Method ◽  
Discrimination Information ◽  
Grinding Machine ◽  
Nc Grinding ◽  
Minimum Discrimination Information

Reliability allocation is a collection problem of engineering decision, multiple factors comprehensive balance and process optimization. Considering that both the factors that influenced the reliability allocation and their weights have the characteristics of uncertainty, which always be ignored .Therefore a subjective and objective combined weights method that combined the entropy method and Interval analysis method was proposed. Taking NC grinding machine as an example, firstly, establish the reliability objective function based on the minimum discrimination information principle, and employ the Lagrange multiplier to get the combined weights of the 6 factors. Then use the fuzzy comprehensive allocation method to obtain the reliability allocation results, which was compared with the actual accumulated data, so that the feasibility and effectiveness of this method was verified.

scholarly journals Fuzzy evaluation method using fuzzy rule approach in multicriteria analysis

2008 ◽  
Vol 18 (1) ◽  
pp. 95-107 ◽  
Author(s):  
Mahmod Othman ◽  
Ruhana Ku-Mahamud ◽  
Abu Bakar
Keyword(s):  
Fuzzy Sets ◽  
Evaluation Method ◽  
Multicriteria Analysis ◽  
Fuzzy Rule ◽  
Experimental Results ◽  
Approximate Reasoning ◽  
Fuzzy Evaluation ◽  
Quality Of Teaching ◽  
Rule Approach

A multicriteria analysis in ranking the quality of teaching using fuzzy rule is proposed. The proposed method uses the application of fuzzy sets and approximate reasoning in deciding the ranking of the quality of teaching in several courses. The proposed method introduces normalizing data which dampen the extreme value that exists in the data. The use of the model is suitable in evaluating situations that involve subjectivity, vagueness and imprecise information. Experimental results are comparable and the method performs better in some domains. .

scholarly journals An Improved Model of Variable Fuzzy Sets with Normal Membership Function for Crane Safety Evaluation

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Aihua Li ◽  
Zhangyan Zhao
Keyword(s):  
Fuzzy Sets ◽  
Membership Function ◽  
Safety Assessment ◽  
Evaluation Method ◽  
Evaluation Criteria ◽  
Safety Evaluation ◽  
Economic Losses ◽  
Interval Numbers ◽  
Improved Model ◽  
Variable Fuzzy Sets

Crane safety evaluation is significant for reducing the casualties and economic losses. Various evaluation methods have been applied to evaluate crane safety. However, when index standard with respect to every level is described in terms of intervals, existing crane safety evaluation models are not ideal. Although variable fuzzy sets (VFS) method has successfully solved similar problems, its evaluation processes are rather complex complicated and tedious. In this paper, we provided an improved VFS evaluation method with normal membership function for solving crane safety problem, in which the evaluation criteria are described in terms of intervals. To demonstrate our presented method, the improved variable fuzzy sets (IVFS) method was applied to two numerical cases including an application to crane safety assessment. It is shown that our proposed method possesses the merit to simplify assessment processes of traditional VFS and can be applied to assess crane safety when criteria values are defined as interval numbers.

scholarly journals Safety Prediction of Deep Foundation Pit Based on Neural Network and Entropy Fuzzy Evaluation

2021 ◽  
Vol 233 ◽  
pp. 03001
Author(s):  
Xie Xiudong ◽  
Pan Caizhen
Keyword(s):  
Neural Network ◽  
Evaluation Method ◽  
Fuzzy Comprehensive Evaluation ◽  
Development Trend ◽  
Entropy Method ◽  
Monitoring Data ◽  
Fuzzy Evaluation ◽  
Deep Foundation ◽  
Foundation Pit ◽  
Deep Foundation Pit

The monitoring data can effectively reflect the safety status of the project during the construction of deep foundation pit, and the risks existing in the project can be discovered in time and the development trend can be reasonably predicted through the processing and analysis of the existing monitoring data. In this paper, a deep foundation pit in compound soil area of a coastal city was taken as an example, the BP neural network was taken to predict the monitoring data in the next stage, the entropy method was utilized to determine the weight of the evaluation index according to the predicted value, and the fuzzy comprehensive evaluation method was used to quantitatively describe the future safety status, so as to formulate targeted countermeasures and improve the construction safety.

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