Study on Stability of Rock at Reservoir Banks Slop Based on AHP

2012 ◽  
Vol 204-208 ◽  
pp. 2309-2317 ◽  
Author(s):  
Zhi Jun Zhou ◽  
Han Liang ◽  
Xiao Dong Wang
Keyword(s):  
Slope Stability ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Engineering Practice ◽  
Stability Evaluation ◽  
Analytic Hierarchy ◽  
Evaluation Indexes ◽  
Comprehensive Evaluations ◽  
Research On Application

The paper aims to present the authors’ research on application of engineering fuzzy set theory analysis to reservoir ranks rock slop stability evaluation by using analytic hierarchy processing (AHP). Many methods, which used to analysis highway slope stability, are compared in the paper. On the basis of research on the general slope stability evaluation methods, lots of fuzzy factors of stability evaluation for highway slope are researched and fuzzy comparison matrix model is established. Correspondence relationship between mood operator and fuzzy value are determined. Evaluation indexes and grading standards are identified on the basis of engineering practice. The weight of every index is obtained by using analytic hierarchy processing and the method of Ridge-type distribution, which the method of combining with the bigger the more excellent and the smaller the more excellent. Engineering fuzzy set theory is used to make a comprehensive evaluations, overall evaluation of the highway slope stability is obtained according to the principle of maximum degree of subjection and the result of subjection degree vector. Slope stability evaluation of AN-SHAN Expressway is analyzed with analytical hierarchy process. Evaluation results provide a basis for the progress of the project, and the project carried out smoothly with the guidance of it. The results show that the model makes slope stability evaluation more comprehensive, scientific and rational.

Slope-stability evaluation factors and rock characteristics based on fuzzy set theory.

1992 ◽  
pp. 151-154
Author(s):  
Kunimasa NISHI ◽  
Kohei FURUKAWA ◽  
Tsuyoshi OGAWA ◽  
Koji NAKAGAWA
Keyword(s):  
Slope Stability ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Stability Evaluation

Uncertainty Analysis in Quantitative Risk Assessment

1996 ◽  
Vol 118 (1) ◽  
pp. 121-124 ◽  
Author(s):  
S. Quin ◽  
G. E. O. Widera
Keyword(s):  
Risk Assessment ◽  
Uncertainty Analysis ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Failure Modes ◽  
The Other ◽  
Quantitative Risk Assessment ◽  
Engineering Practice ◽  
Criticality Analysis

Of the quantitative approaches applied to inservice inspection, failure modes, effects,criticality analysis (FMECA) methodology is recommended. FMECA can provide a straightforward illustration of how risk can be used to prioritize components for inspection (ASME, 1991). But, at present, it has two limitations. One is that it cannot be used in the situation where components have multiple failure modes. The other is that it cannot be used in the situation where the uncertainties in the data of components have nonuniform distributions. In engineering practice, these two situations exist in many cases. In this paper, two methods based on fuzzy set theory are presented to treat these problems. The methods proposed here can be considered as a supplement to FMECA, thus extending its range of applicability.

scholarly journals Analysis of time overruns in roads and highways sector in India using AHP ranking technique

2018 ◽  
Vol 7 (3.29) ◽  
pp. 259
Author(s):  
Siddesh K. Pai ◽  
Avinash Kumar Singh ◽  
Ankur Mittal ◽  
Neeraj Anand
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Analytic Hierarchy ◽  
Severity Factor ◽  
Construction Firm ◽  
The Right ◽  
Hierarchy Process

In today’s scenario there will be a competition exists among various construction firm, so the risk management come into picture to assess the various risk related to project. Assigning the right severity factor as per the possibility of occurrence will impart the success of organization as well as success will impart the growth of nation with increase in G.D.P. In construction of road the assessment of right severity factor, will be considered as strength to lower down the delay of time over run. Tremendous amount of effort are applied in quantitative and qualitative manner for assessment of risk severity factor. However, many criteria for risk severity factor enable the decision making methods will smoothen the process of arriving at a solution and enable decision makers to make the right decisions. Decision-making problems need systematic approach to appraise the various alternatives using quantitative and non quantitative factors. Standard methods for solving problems will lack considerations of non-quantitative factors, where numeric values are difficult to assign. Different techniques like, Analytic Hierarchy Process (AHP), Fuzzy set theory Making and Multi Criteria Decision are being used in risk severity factor. These techniques consider factors with concrete values or vague values. This research will provide solution to a risk severity factor for budget allocation problem, for allocating funds to competing and deserving organizations by using ranking analysis technique. Fuzzy set theory and AHP is used to calculate the Weights .Fuzzy set considers subjective values like preferred, strongly preferred etc. and Analytic Hierarchy Process (AHP) technique evaluates relative importance of factors by making pair wise comparison matrix. The evaluation technique will facilitate in ranking of various severity factors according to their possibility of occurrence after assigning weights to decision making factor.   

Fuzzy Judgments and Fuzzy Sets

2012 ◽  
pp. 100-116 ◽  
Author(s):  
Thomas L. Saaty ◽  
Liem T. Tran
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Fuzzy Theory ◽  
Value Theory ◽  
Outcome Data ◽  
Analytic Hierarchy ◽  
The Many ◽  
The Right

Using fuzzy set theory has become attractive to many people. However, the many references cited here and in other works, little thought is given to why numbers should be made fuzzy before plunging into the necessary simulations to crank out numbers without giving reason or proof that it works to one’s advantage. In fact it does not often do that, certainly not in decision making. Regrettably, many published papers that use fuzzy set theory presumably to get better answers were not judged thoroughly by reviewers knowledgeable in both fuzzy theory and decision making. Buede and Maxwell (1995), who had done experiments on different ways of making decisions, found that fuzzy does the poorest job of obtaining the right decision as compared with other ways. “These experiments demonstrated that the MAVT (Multiattribute Value Theory) and AHP (Analytic Hierarchy Process) techniques, when provided with the same decision outcome data, very often identify the same alternatives as ‘best’. The other techniques are noticeably less consistent with the Fuzzy algorithm being the least consistent.”

Multi-Attribute Decision Making Using Interval Type-2 Fuzzy AHP and Its Application on Borsa Istanbul (BIST)

2021 ◽  
pp. 30-56
Author(s):  
Beyza Ahlatcioglu Ozkok ◽  
Hale Gonce Kocken
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Fuzzy Ahp ◽  
Short Review ◽  
Analytic Hierarchy ◽  
Multi Attribute Decision Making ◽  
Interval Type

Analytic hierarchy process (AHP) is a widely used multi-attribute decision-making (MADM) approach. Due to the complexity and uncertainty involved in real world problems, decision makers might be prefer to make fuzzy judgments instead of crisp ones. Furthermore, even when people use the same words, individual judgments of events are invariably subjective, and the interpretations that they attach to the same words may differ. This is why fuzzy numbers has been introduced to characterize linguistic variables. Fuzzy AHP methods have recently been extended by using type-2 fuzzy sets. Type-2 fuzzy set theory incorporates the uncertainty of membership functions into the fuzzy set theory. In this chapter, the authors firstly provide a short review on applications of interval type-2 fuzzy AHP on MADM problems. Then, they present a very efficient MADM technique, interval type-2 fuzzy AHP, to solve the portfolio selection problem that is to decide which stocks are to be chosen for investment and in what proportions they will be bought. And finally, they provided a case study on BIST.

Evaluation Model of Conceptual Design Scheme Based on Engineering Fuzzy Set Theory

2012 ◽  
Vol 479-481 ◽  
pp. 1741-1744
Author(s):  
Hong Bin Miao
Keyword(s):  
Conceptual Design ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Evaluation Model ◽  
Objective Evaluation ◽  
Evaluation Indexes ◽  
Model Based ◽  
Mechanical Products ◽  
Fuzzy Pattern

The evaluation of conceptual design schemes of mechanical products is an essential problem in the process of its conceptual design. At the stage of conceptual design, whether a correct and objective evaluation can be made on these design schemes will ultimately decide a good or bad performance, even its success or failure. The evaluation of conceptual design is a semi-structural decision-making that includes qualitative indexes and quantitative indexes, so it is difficult to select the best design concepts from a number of schemes. Therefore, an evaluation model based on the engineering fuzzy set theory is developed in this paper. First, the paper makes a detailed hierarchy analysis of evaluation indexes system and constructs some evaluation units according to evaluation indexes system. The whole evaluation of schemes is translated into a series of evaluation of basic units or comprehensive cells. Second, a multi-pole fuzzy pattern recognition model based on the engineering fuzzy set theory is established and the relative membership degree matrix can be obtained by the model, the matrix shows the order of excellence. An example is given for demonstration of its application. It shows that the method is feasible and reasonable.

ANALYZING INFLUENCE FACTORS OF TECHNOLOGY TRANSFER USING FUZZY SET THEORY

2010 ◽  
Vol 07 (01) ◽  
pp. 71-87 ◽  
Author(s):  
WEN-HSIANG LAI ◽  
CHIEN-TZU TSAI
Keyword(s):  
Technology Transfer ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
New Technologies ◽  
New Technology ◽  
Influence Factors ◽  
Analytic Hierarchy ◽  
Support Mechanism ◽  
International Firms

In order to compete in the global environment, the ability and effectiveness of acquiring new technology are essential for firms, and most new technologies need and depend on the Technology Transfer (TT) from international firms and research institutes. Due to the complicity of influence factors of TT, such as features of industry, technology, organization, and talent, difficulties are encountered in evaluating the effectiveness of TT. This study develops a rule-based decision support mechanism using fuzzy set theory and the method of Analytic Hierarchy Process (AHP) to evaluate the effectiveness of TT. The characteristic of adopting fuzzy set theory is to construct the membership function for those features of influence factors and differentiate the indistinct linguistic terms in order to match true conditions. Finally this study discusses the hierarchical influence factors of TT and provides suggestions for machinery firms with respect to TT effectiveness.

Identification of unbalanced bids based on grey-fuzzy evaluation method

2020 ◽  
Vol 47 (3) ◽  
pp. 272-278
Author(s):  
Limin Su ◽  
Huimin Li ◽  
Zhangmiao Li ◽  
Yongchao Cao
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Evaluation Method ◽  
Unit Price ◽  
Fuzzy Evaluation ◽  
Analytic Hierarchy ◽  
Identification Method ◽  
Score Vector ◽  
Grey Relational

To provide theoretical reference for owners to identify unbalanced bids, this paper aims to construct an identification method based on grey relational and fuzzy set theory. Firstly, to measure the closeness degree between bidding unit price from engineering’s estimated price, grey relational analysis theory is used to express the relationship between them. Secondly, a combined weight method determining all line items is calculated through integrating analytic hierarchy model and maximizing deviation method. Thirdly, based on fuzzy set theory, the membership degree and the fuzzy relation matrix are constructed, and then a fuzzy comprehensive identification method is established to identify unbalanced bidding. Fourthly, on the basis of fuzzy comprehensive identification method, the scoring set and total score vector are designed, and the rank of unbalanced bids is obtained by total score vector. Finally, a practical construction project bidding is stated to illustrate the effectiveness and practicability of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document