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JournalISSN: 1064-1246

Journal of Intelligent and Fuzzy Systems 

IOS Press
About: Journal of Intelligent and Fuzzy Systems is an academic journal published by IOS Press. The journal publishes majorly in the area(s): Fuzzy logic & Computer science. It has an ISSN identifier of 1064-1246. Over the lifetime, 10368 publications have been published receiving 85185 citations. The journal is also known as: Journal of intelligent and fuzzy systems.


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Journal ArticleDOI
TL;DR: An efficient method for estimating cluster centers of numerical data that can be used to determine the number of clusters and their initial values for initializing iterative optimization-based clustering algorithms such as fuzzy C-means is presented.
Abstract: We present an efficient method for estimating cluster centers of numerical data. This method can be used to determine the number of clusters and their initial values for initializing iterative optimization-based clustering algorithms such as fuzzy C-means. Here we use the cluster estimation method as the basis of a fast and robust algorithm for identifying fuzzy models. A benchmark problem involving the prediction of a chaotic time series shows this model identification method compares favorably with other, more computationally intensive methods. We also illustrate an application of this method in modeling the relationship between automobile trips and demographic factors.

2,815 citations

Journal ArticleDOI
TL;DR: This work develops, based upon the mountain clustering method, a procedure for learning fuzzy systems models from data, and uses a back propagation algorithm to tune the model.
Abstract: We develop, based upon the mountain clustering method, a procedure for learning fuzzy systems models from data. First we discuss the mountain clustering method. We then show how it could be used to obtain the structure of fuzzy systems models. The initial estimates of this model are obtained from the cluster centers. We then use a back propagation algorithm to tune the model.

670 citations

Journal ArticleDOI
Jun Ye1
TL;DR: A multicriteria decision-making method is established in which the evaluation values of alternatives with respective to criteria are represented by the form of SNSs, and the ranking order of alternatives is performed through the cosine similarity measure between an alternative and the idealAlternative and the best ones can be determined.
Abstract: The paper introduces the concept of simplified neutrosophic sets SNSs, which are a subclass of neutrosophic sets, and defines the operational laws of SNSs. Then, we propose some aggregation operators, including a simplified neutrosophic weighted arithmetic average operator and a simplified neutrosophic weighted geometric average operator. Based on the two aggregation operators and cosine similarity measure for SNSs, a multicriteria decision-making method is established in which the evaluation values of alternatives with respective to criteria are represented by the form of SNSs. The ranking order of alternatives is performed through the cosine similarity measure between an alternative and the ideal alternative and the best ones can be determined as well. Finally, a numerical example shows the application of the proposed method.

649 citations

Journal ArticleDOI
Jun Ye1
TL;DR: The Hamming and Euclidean distances between interval neutrosophic sets INSs are defined and the similarity measures are proposed based on the relationship between similarity measures and distances, and a multicriteria decision-making method is established.
Abstract: An interval neutrosophic set is an instance of a neutrosophic set, which can be used in real scientific and engineering applications. In the paper, the Hamming and Euclidean distances between interval neutrosophic sets INSs are defined and the similarity measures between INSs are proposed based on the relationship between similarity measures and distances. In the applications of the similarity measures, a multicriteria decision-making method is established in interval neutrosophic setting, in which criterion values with respect to alternatives are evaluated by the form of interval neutrosophic values INVs and the criterion weights are known information. We utilize the similarity measures between each alternative and the ideal alternative to rank the alternatives and to determine the best one. Finally, an illustrative example demonstrates the applications of the proposed decision-making method.

447 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
2023701
20221,188
20211,931
20201,374
20191,240
2018916