Fuzzy C-Mean (FCM) is an unsupervised clustering algorithm based on fuzzy set theory that allows an element to belong to more than one cluster. Where fuzzy means “unclear” or “not defined” and c denotes “clustering”. In FCM the number of cluster are randomly selected. [15] FCM is the advanced version of K-means clustering algorithm and doing more work than K-means. K-Means just needs to do a di...

Methods of solving the identified environmental problems, considering mathematical rigorous alternative assessment of environmental component process using fuzzy logic and approximate reasoning, are described by various researchers. To illustrate how such a computational intelligence approach would work in performing an assessment, various artificial techniques have been described. Fuzzy system...

In this work, we conduct a preliminary study considering a fuzzy rule-based multiclassification system design framework based on Fuzzy Unordered Rule Induction Algorithm (FURIA). This advanced method serves as the fuzzy classification rule learning algorithm to derive the component classifiers considering bagging combined with feature selection. We develop a study on the use of both bagging and...

The control of turbulence at tokamaks is very complex problem.The idea is to apply the fuzzy Markovian processes and fuzzy Brownian motions as good approximation of general robust drift kinetic equation. It is obtained by using the artificial neural networks for solving of appropriate advanced control problem. The proof of the appropriate theorem is shown.

Fuzzy set theory which is a powerful tool for handling vague situations has advanced in a variety of ways and in many disciplines. Applications of this theory can be found in artificial intelligence, computer science, control engineering, decision theory, expert systems, logic, management science, operations research, pattern recognition and robotics. There have been a variety of fuzzy measures...

The teaching of fuzzy and advanced control strategies at bachelor level is correlated with the usually heuristic means of fuzzy control, incorporating human skills, the drawback being in the lack of general-purpose development methods. A major problem, which follows from the study of advanced control strategies is the understanding of its background the basic development methods and some applic...

The modeling of the behavior of human process operators using fuzzy methods is well established in technical applications. We investigate whether these fuzzy strategies can also be successfully applied for modeling the manner in which a musician interprets a piece of music. For L. v. Beethoven’s composition “Für Elise” we set up a base of 150 fuzzy rules that relate to features laid down explic...

The contemporary manufacturing organisations are forced to adopt advanced manufacturing paradigms for sustaining in the global markets. Supply chain management is an essential ingredient of advanced manufacturing systems since outsourcing gains vital importance. Supplier selection is a vital issue concerned in the process of managing global supply chains. A conceptual model for supplier selecti...

This paper presents an advanced intelligent control for cardiac pacemaker systems using fuzzy proportional-integral derivative (FPID) controller. Under three different body states (rest, walking, and exercising), it offers good adaptation of the heart rate to the physiological needs of the patient. Based on dual-sensors, the combination of fuzzy logic and conventional PID control approaches is ...

The paper presents an advanced control strategy that uses the neural network predictive controller and the fuzzy controller in the complex control structure with an auxiliary control variable. The controlled tubular heat exchanger was used for pre-heating of petroleum by hot water. The heat exchanger was modelled as a nonlinear system with interval parametric uncertainty. The set point tracking...