Evolutionarily stable strategy (ESS) is a key concept in evolutionary game theory. ESS provides an evolutionary stability criterion for biological, social and economical behaviors. In this paper, we develop a new approach to evaluate ESS in symmetric two player games with fuzzy payoffs. Particularly, every strategy is assigned a fuzzy membership that describes to what degree it is an ESS in pre...

A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifies numerous temporal association rules that occur more frequently in areas of a dataset with specific quantitative values represented with fuzzy sets. The novelty of this research lies in exploring the composition of qu...

Evolution strategy (ES) is a well-known instance of evolutionary algorithms, and there have been many studies on ES. In this paper, the author proposes an extended ES for solving fuzzy-valued optimization problems. In the proposed ES, genotype values are not real numbers but fuzzy numbers. Evolutionary processes in the ES are extended so that it can handle genotype instances with fuzzy numbers....

a neuro-fuzzy modeling tool (anfis) has been used to dynamically model cross flow ultrafiltration of milk. it aims to predict permeate flux and total hydraulic resistance as a function of transmembrane pressure, ph, temperature, fat, molecular weight cut off, and processing time. dynamic modeling of ultrafiltration performance of colloidal systems (such as milk) is very important for designing ...

One of the new trends in genetic fuzzy systems (GFS) is the use of evolutionary multiobjective optimization (EMO) algorithms. This is because EMO algorithms can easily handle two conflicting objectives (i.e., accuracy maximization and complexity minimization) when we design accurate and compact fuzzy rule-based systems from numerical data. Since the main advantage of fuzzy rule-based systems co...

In multi-objective evolutionary fuzzy systems, the process of tuning the membership functions plays an important role towards optimizing the systems accuracy. Although, the shape and position of the membership functions in the partition should not change too much with relation to the original partition, so that it does not lose its integrity. This paper presents and discusses multi-objective ev...

As the planet watches in shock evolution of COVID-19 pandemic, new forms sophisticated, versatile, and extremely difficult-to-detect malware expose society especially global economy. Machine learning techniques are posing an increasingly important role field identification analysis. However, due to complexity problem, training intelligent systems proves be insufficient recognizing advanced cybe...

This work presents the use of local fuzzy prototypes as a new idea to obtain accurate local semantics-based Takagi–Sugeno–Kang ~TSK! rules. This allow us to start from prototypes considering the interaction between input and output variables and taking into account the fuzzy nature of the TSK rules. To do so, a two-stage evolutionary algorithm based on MOGUL ~a methodology to obtain Genetic Fuz...

An Intelligent Supervision Scheme for the Industrial Production is presented in this work. Such scheme is tested for gas lift (GL) oil wells. The proposal is based on the possible production assessment, the process variables (specifically, the bottom-well pressures), and the operational scenarios detection for the process (in the case of study, as an oil producing well), with the objective of o...