This paper provides an in-depth review of the optimal design of type-1 and type-2 fuzzy
inference systems (FIS) using five well known computational frameworks: genetic-fuzzy …

Abstract Evolutionary Fuzzy Systems are a successful hybridization between fuzzy systems
and Evolutionary Algorithms. They integrate both the management of imprecision …

Abstract The k-Nearest Neighbor algorithm (kNN) is an algorithm that is very simple to
understand for classification or regression. It is also a lazy algorithm that does not use the …

The world continues to generate quintillion bytes of data daily, leading to the pressing needs
for new efforts in dealing with the grand challenges brought by Big Data. Today, there is a …

Classification techniques are becoming essential in the financial world for reducing risks
and possible disasters. Managers are interested in not only high accuracy, but in …

The local set is the largest hypersphere centered on an instance such that it does not
contain instances from any other class. Due to its geometrical nature, this structure can be …

Data selection, which includes feature and instance selection, is often an important step in
building prediction systems. Genetic algorithms (GA) frequently allow finding better solutions …

In the last years, rule-based systems have been widely employed in several different
application domains. The performance of these systems is strongly affected by the process …

An anti-lock brake system based on fuzzy logic has been developed and optimized to cope
with changes in adherence road conditions. Conventional control systems have to be tuned …

Abstract “Fuzzy Theoretic Approach to Signals and Systems” assumes all system variables
and parameters as uncertain (ie being characterized by membership functions), develops a …