This paper focusses on the application of intelligent control techniques (neural networks, fuzzy logic and genetic algorithms) and their hybrid forms (neuro-fuzzy networks, neuro-genetic and fuzzy-genetic algorithms) in the area of humanoid robotic systems. Overall, this survey covers a broad selection of examples that will serve to demonstrate the advantages and disadvantages of the applicatio...

In this study, we propose the method creating fuzzy control rules based on experiential knowledge. With the advent of data mining techniques, a new way is provided to create fuzzy control rules. With the introduction of incremental data mining techniques, fuzzy control rules can be updated dynamically in time on the condition that massive new data is producing.

As customers are the main asset of any organization, customer churn management is becoming a major task for organizations to retain their valuable customers. In the previous studies, the applicability and efficiency of hierarchical data mining techniques for churn prediction by combining two or more techniques have been proved to provide better performances than many single techniques over a nu...

data envelopment analysis (dea) is a technique used to compare efficiency in various sectors such as hospitals, chain stores, and dealerships. it represents a set of linear programming techniques and uses deter-ministic data (inputs and outputs), in stable conditions. the dea technique cannot be used when there is data with indeterministic nature, or when there is an environment with dynamic co...

The aim of image enhancement is to improve the interpretability or perception of information in images for human viewers, or to provide 'better' input for other automated image processing techniques. Fuzzy techniques can manage the vagueness and ambiguity efficiently (an image can be represented as fuzzy set). Fuzzy logic is a powerful tool to represent and process human knowledge in form of fu...

Frequently SASε programmers must merge files where the values of the key variables are only approximately the same. Merging on names with approximately the same spelling, or merging on times that are within three minutes of each other are examples of these kinds of merges. These merges are often called fuzzy merges. This tutorial examines the realm of fuzzy merges. It looks at relevant techniqu...

This book contains the successful invited submissions [1–21] to a Special Issue of Symmetry on the subject area of “Fuzzy Techniques for Decision Making”. We invited contributions addressing novel techniques and tools for decision making (e.g., group or multi-criteria decision making), with notions that overcome the problem of finding the membership degree of each element in Zadeh’s original mo...

Disaster mitigation and management is one of the most challenging examples of decision making under uncertain, missing, and sketchy, information. Even in the extreme cases where the nature of the disaster is known, preparedness plans are in place, and analysis, evaluation, and simulations of the disaster management procedures have been performed, the amount and magnitude of “surprises” that acc...

Ranking of fuzzy numbers plays a very important role in linguistic decision making and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce nonintuitive results in certain cases. In this paper, some new approaches for ranking of trapezoidal fuzzy numbers are introduced. Keywords— Magnitude of...