An evolutionary algorithm for the optimization of combined fuzzy compression and decompression of images is introduced. An image is divided into squares, and a fuzzy compression algorithm decides the color of the pixels that will replace the whole squares in the compressed image. A fuzzy decompression algorithm reconstructs the colors of pixels in the decompressed image on the basis of the pixe...

Interpretability and accuracy are two important features of fuzzy systems which are conflicting in their nature. One can be improved at the cost of the other and this situation is identified as “Interpretability-Accuracy Trade-Off”. To deal with this trade-off Multi-Objective Evolutionary Algorithms (MOEA) are frequently applied in the design of fuzzy systems. Several novel MOEA have been propo...

Background: Acute appendicitis is one of the common and urgent illnesses among children.  Children usually are unable to help the physicians completely due to weakness in describing the medical history. Moreover, acute appendicitis overlaps with conditions of other diseases in terms of Symptoms and signs in the first hours of presentation. These conditions lead to unwanted biases as well as err...

In this contribution a new supervised classification model is proposed, namely the Fuzzy Evolutionary Probabilistic Neural Network (FEPNN). The proposed model incorporates a fuzzy class membership function into the recently proposed Evolutionary Probabilistic Neural Network (EPNN). EPNN employs an evolutionary algorithm, namely the Particle Swarm Optimization (PSO), for the selection of the spr...

in this paper, a numerical method for nding minimal solution of a mn fullyfuzzy linear system of the form ax = b based on pseudo inverse calculation,is given when the central matrix of coecients is row full rank or column fullrank, and where a~ is a non-negative fuzzy mn matrix, the unknown vectorx is a vector consisting of n non-negative fuzzy numbers and the constant b isa vector consisti...

We are trying to piece together the knowledge of evolution with the help of biology, informatics and physics to create complex evolutionary algorithms with parallel and hierarchical structure. It can speed up the creation of optimization algorithms with high quality features. The adaptive significance of genetic algorithms (GAs) with diploid chromosomes and an artificial immune system has been ...

A new methodology to learn descriptive linguistic Fuzzy Rule-based System Knowledge Bases from examples based on the combination of fuzzy clustering and evolutionary simultaneous rule selection and membership functions tuning is presented in this work. Fuzzy clustering is used to achieve a preliminary description of the data, in other words to obtain information on the definition of the linguis...

This work describes the application of subgroup discovery using evolutionary algorithms to the usage data of the Moodle course management system, a case study of the University of Cordoba, Spain. The objective is to obtain rules which describe relationships between the student’s usage of the different activities and modules provided by this e-learning system and the final marks obtained in the ...

Recently Web mining has become a hot research topic, which combines two of the prominent research areas comprising of data mining and the World Wide Web (WWW). Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, business and support se...