This journal is devoted to the theory, design and applications of fuzzy systems, ranging from hardware to software. Emphasis will be given to engineering applications.

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Featured Paper

Selected article from IEEE Transaction on Fuzzy Systems

Improving Supervised Learning Classification Methods Using Multigranular Linguistic Modeling and Fuzzy Entropy

We propose to apply linguistic modeling methods in order to obtain a linguistic representation. With the help of multigranular linguistic modeling, data can be transformed and expressed using different (unbalanced) linguistic label sets. Expressing the data using linguistic expressions instead of numbers increases the readability and reduces the complexity of the problem, and data recovering methods allow us to manually control the level of precision. In this paper, several datasets are transformed and utilized for classification tasks using several supervised learning algorithms. For each combination of datasets and algorithms, the data have been expressed using several linguistic label sets that have different granularity values. After carrying out the testing processes, we can conclude that, in some cases, reducing data complexity leads to better classification results. Therefore, it is found that linguistic representation of the training data with just the necessary and sufficient precision can improve the reliability of the classification process.

IEEE Transactions on Fuzzy Systems, Oct. 2017


Lotfi A. Zadeh In Memoriam


Recounts the career and achievements of Lotfi A. Zadeh, who passed away September 6, 2017.

P. P. Bonissone and E. H. Ruspini, "Lotfi A. Zadeh In Memoriam," in IEEE Transactions on Fuzzy Systems, vol. 25, no. 5, pp. 1021-1022, Oct. 2017.