Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...

The data-driven identification of fuzzy rule-based classifiers for high-dimensional problems is addressed. A binary decision-tree-based initialization of fuzzy classifiers is proposed for the selection of the relevant features and effective initial partitioning of the input domains of the fuzzy system. Fuzzy classifiers have more flexible decision boundaries than decision trees (DTs) and can th...

This paper focuses on the data-driven generation of fuzzy IF...THEN rules. The resulted fuzzy rule base can be applied to build a classifier, a model used for prediction, or it can be applied to form a decision support system. Among the wide range of possible approaches, the decision tree and the association rule based algorithms are overviewed, and two new approaches are presented based on the...

The main objective of this research work is to construct a Fuzzy Temporal Rule Based Classifier that uses fuzzy rough set and temporal logic in order to mine temporal patterns in medical databases. The lower approximation concepts and fuzzy decision table with the fuzzy features are used to obtain fuzzy decision classes for building the classifier. The goals are pre-processing for feature selec...

designing an effective criterion for selecting the best rule is a major problem in theprocess of implementing fuzzy learning classifier (flc) systems. conventionally confidenceand support or combined measures of these are used as criteria for fuzzy rule evaluation. in thispaper new entities namely precision and recall from the field of information retrieval (ir)systems is adapted as alternative...

When designing any type of fuzzy rule based system, considerable effort is placed in identifying the correct number of fuzzy sets and the fine tuning of the corresponding membership functions. Once a rule base has been formulated a fuzzy inference strategy must be applied in order to combine grades of membership. Considerable time and effort is spent trying to determine the number of fuzzy sets...

Designing an effective criterion for selecting the best rule is a major problem in theprocess of implementing Fuzzy Learning Classifier (FLC) systems. Conventionally confidenceand support or combined measures of these are used as criteria for fuzzy rule evaluation. In thispaper new entities namely precision and recall from the field of Information Retrieval (IR)systems is adapted as alternative...