scholarly journals Some Topological and Algebraic Properties of α-level Subsets’ Topology of a Fuzzy Subset

2018 ◽  
Vol 26 (3) ◽  
pp. 213-228 ◽  
Author(s):  
B. O. Onasanya ◽  
S. Hoskova-Mayerova
Keyword(s):  
Fuzzy Set ◽  
Operations Research ◽  
Fuzzy Theory ◽  
Possibility Theory ◽  
Fuzzy Cluster ◽  
Approximate Reasoning ◽  
Credibility Theory ◽  
Fuzzy Subset ◽  
Wide Range ◽  
Α Level

AbstractThe theory of fuzzy sets, since its foundation, has advanced in a wide range of means and in many fields. One of the areas to which fuzzy set theory has been applied extensively is mathematical programming. Nevertheless, the applications of fuzzy theory can be found in e.g. logic, decision theory, artificial intelligence, computer science, control engineering, expert systems, management science, operations research, robotics, and others. Theoretical improvements have been made in many directions. Nowadays it has a lot of applications also on possibility theory, actuarial credibility theory, fuzzy logic and approximate reasoning, fuzzy control, fuzzy data analysis, fuzzy set models in operations research, etc. The aim of this paper is to investigate some topological properties of a set X when the topology defined on it is the collection of all the α-level subsets of a fuzzy subset A of X.We have been able to establish some results regarding fuzzy cluster level subsets, convergence of level subsets and quasicompactness among others.

Research on the Credibility of Fuzzy Reliability

2011 ◽  
Vol 48-49 ◽  
pp. 984-988 ◽  
Author(s):  
Ling Ling Li ◽  
Fen Fen Zhu ◽  
Chun Wen Yang ◽  
Zhi Gang Li
Keyword(s):  
Distribution Function ◽  
Engineering Design ◽  
Distribution Curve ◽  
Fuzzy Theory ◽  
Possibility Theory ◽  
Credibility Theory ◽  
Fuzzy Information ◽  
Reliability Engineering ◽  
Possibility Distribution ◽  
Fuzzy Reliability

According to the situation of randomness and fuzziness existing in the actual project, this paper proposed a reliability-credibility model based on fuzzy theory, possibility theory and credibility theory. At firstly, a reliability-possibility distribution curve was constructed by the traditional stress-strength interference model, then, a reliability distribution function was established based on this. This model built a bridge between credibility and reliability in handling randomness and fuzziness. The research results show that the model can hand the situation of random information and fuzzy information coexistence well, and the acceptable level of reliability and the most credible reliability value can be reflected directly in the reliability-credibility distribution curve. Compared with other methods, it obtains more reliability information, accords with the actual engineering situation and guides reliability engineering design much better.

scholarly journals Integration of image segmentation and fuzzy theory to improve the accuracy of damage detection areas in traffic accidents

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Majid Amirfakhrian ◽  
Mahboub Parhizkar
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Machine Vision ◽  
Traffic Accidents ◽  
Fuzzy Theory ◽  
Machine Learning Techniques ◽  
Industrial Setting ◽  
Technological Advances ◽  
Learning Techniques ◽  
Wide Range

AbstractIn the next decade, machine vision technology will have an enormous impact on industrial works because of the latest technological advances in this field. These advances are so significant that the use of this technology is now essential. Machine vision is the process of using a wide range of technologies and methods in providing automated inspections in an industrial setting based on imaging, process control, and robot guidance. One of the applications of machine vision is to diagnose traffic accidents. Moreover, car vision is utilized for detecting the amount of damage to vehicles during traffic accidents. In this article, using image processing and machine learning techniques, a new method is presented to improve the accuracy of detecting damaged areas in traffic accidents. Evaluating the proposed method and comparing it with previous works showed that the proposed method is more accurate in identifying damaged areas and it has a shorter execution time.

scholarly journals Application of Fuzzy DEMATEL in Risks Evaluation of Knowledge-Based Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
M. Abbasi ◽  
R. Hosnavi ◽  
B. Tabrizi
Keyword(s):  
Risk Factors ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
New Products ◽  
Linguistic Variables ◽  
Fuzzy Dematel ◽  
Knowledge Based ◽  
Wide Range ◽  
Do So

Developing new products has received much attention within the last decades. This issue can be highlighted for strategic innovations, in particular. Recently, knowledge-based networks have been introduced in order to facilitate the affair of transforming knowledge into commercial products which can be regarded as a set of research centers, universities, knowledge intermediaries, customers, and so forth. However, there is a wide range of risk factors that are liable to affect the chain performance. Hence, this paper aims to consider the most influencing criteria that can play a more significant role in achievements of such networks. To do so, DEMATEL has been applied to take the relationships between the risk factors into account. Moreover, fuzzy set theory has been utilized in order to deal with the linguistic variables. Finally, the most important factors are identified and their relations are determined.

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.

scholarly journals A Review on the Development of Fuzzy Classifiers with Improved Interpretability and Accuracy Parameters

2021 ◽  
Vol 2 (2) ◽  
pp. 1-9
Author(s):  
Farheen Azad ◽  
Keyword(s):  
Fuzzy Set ◽  
Fuzzy System ◽  
Probabilistic Reasoning ◽  
Fuzzy Theory ◽  
Physical World ◽  
Fundamental Aspect ◽  
Fuzzy Classifiers ◽  
Human Thinking ◽  
Interval Type

This review paper of fuzzy classifiers with improved interpretability and accuracy parameter discussed the most fundamental aspect of very effective and powerful tools in form of probabilistic reasoning, The fuzzy logic concept allows the effective realization of ap-proximate, vague, uncertain, dynamic, and more realistic conditions, which is closer to the actual physical world and human thinking. The fuzzy theory has the competency to catch the lack of preciseness of linguistic terms in a speech of natural language. The fuzzy theory provides a more significant competency to model humans like com-mon-sense reasoning and conclusion making to fuzzy set and rules as good membership function. Also, this paper reviews discussed the evaluation of the fuzzy set, type-1, type-2, and interval type-2 fuzzy system from traditional Boolean crisp set logic along with interpretability and accuracy issues in the fuzzy system.

Complex bipolar fuzzy sets: An application in a transport’s company

2020 ◽  
pp. 1-17
Author(s):  
Muhammad Gulistan ◽  
Naveed Yaqoob ◽  
Ahmed Elmoasry ◽  
Jawdat Alebraheem
Keyword(s):  
Fuzzy Sets ◽  
Membership Function ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Cartesian Product ◽  
Real Numbers ◽  
Wide Range ◽  
Fuzzy Aggregation ◽  
Bipolar Fuzzy Sets ◽  
Range Of Values

Zadeh’s fuzzy sets are very useful tool to handle imprecision and uncertainty, but they are unable to characterize the negative characteristics in a certain problem. This problem was solved by Zhang et al. as they introduced the concept of bipolar fuzzy sets. Thus, fuzzy set generalizes the classical set and bipolar fuzzy set generalize the fuzzy set. These theories are based on the set of real numbers. On the other hand, the set of complex numbers is the generalization of the set of real numbers so, complex fuzzy sets generalize the fuzzy sets, with wide range of values to handle the imprecision and uncertainty. So, in this article, we study complex bipolar fuzzy sets which is the generalization of bipolar fuzzy set and complex fuzzy set with wide range of values by adding positive membership function and negative membership function to unit circle in the complex plane, where one can handle vagueness in a much better way as compared to bipolar fuzzy sets. Thus this paper leads us towards a new direction of research, which has many applications in different directions. We develop the notions of union, intersection, complement, Cartesian product and De-Morgan’s Laws of complex bipolar fuzzy sets. Furthermore, we develop the complex bipolar fuzzy relations, fundamental operations on complex bipolar fuzzy matrices and some operators of complex bipolar fuzzy matrices. We also discuss the distance measure on complex bipolar fuzzy sets and complex bipolar fuzzy aggregation operators. Finally, we apply the developed approach to a numerical problem with the algorithm.

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