scholarly journals The Development of a Tourism Attraction Model by Using Fuzzy Theory

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Jieh-Ren Chang ◽  
Betty Chang
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Fuzzy Theory ◽  
Limited Resources ◽  
Analysis Method ◽  
Tourism Destination ◽  
Tourist Destinations ◽  
Attraction Model ◽  
Tourism Destinations

The purpose of this study is to develop a model to investigate the tourists’ preference. Ten attributes of tourist destinations were used in this study. Fuzzy set theory was adopted as the main analysis method to find the tourists’ preference. In this study, 248 pieces of data were used. Besides the evaluations for the factors, the overall evaluations (namely, satisfied, neutral, and dissatisfied) for every tourism destination were also inquired. After screening, 201 pieces of these data could be used. In these 201 pieces of data, 141 were classified into “satisfied” with the tourism destination, accounting for 70.15%, and 49 were “neutral,” accounting for 24.38%, while 11 were “dissatisfied,” accounting for 5.47%. Eight rules were obtained with the method of fuzzy preprocess. Regarding the condition attributes, three of the original ten attributes were found influential, namely, level of prices, living costs, information and tourist services, and tourist safety of the tourism destinations. From the results of this study, it is shown that top management of tourism destinations should put resources in these fields first, in order to allow limited resources to perform to maximum effectiveness.

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.”

Fuzzy Judgments and Fuzzy Sets

2010 ◽  
Vol 1 (1) ◽  
pp. 23-40 ◽  
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.”

Importance Analysis Method of Fuzzy Fault Tree Based on T-S Modle and Application in Hydraulic System

2013 ◽  
Vol 470 ◽  
pp. 707-711 ◽  
Author(s):  
Lu Lu Zhang ◽  
Rui Jun Zhang ◽  
Xin Xin Si
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Hydraulic System ◽  
Fault Tree ◽  
Analysis Method ◽  
Fuzzy Information ◽  
Logical Relationship ◽  
Importance Analysis ◽  
Fuzzy Subsets

In order to overcome the shortage of dealing with fuzzy information and uncertainty of fault logical relationship in traditional importance measures, the fuzzy set theory is presented to fault tree, using fuzzy number to describe the fault states of system and components, and using fuzzy subsets to denote the fault rates, a fuzzy fault tree of T-S modle was established. And a model of fuzzy fault tree was established and a T-S fuzzy importance analysis method was presented on the basis of T-S analysis method. The method is applied in the importance analysis of hydraulic system, and proving that the algorithms are feasible.

Estimating construction waste generation in residential buildings: A fuzzy set theory approach in the Brazilian Amazon

2020 ◽  
Vol 265 ◽  
pp. 121779 ◽  
Author(s):  
Luiz Maurício Furtado Maués ◽  
Brisa do Mar Oliveira do Nascimento ◽  
Weisheng Lu ◽  
Fan Xue
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Residential Buildings ◽  
Brazilian Amazon ◽  
Theory Approach ◽  
Waste Generation ◽  
Construction Waste
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