A Neuro-Fuzzy (NF) system is a combination of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS) in such a way that ANN learning algorithms are used to determine the parameters of FIS. Potential interactions between connectionist learning systems and evolutionary search procedures have attracted lots of research work recently. There is no guarantee that the learning algorithm conv...

This paper describes the optimization of an integration block within the proposed navigation control system for a mobile robot. The control blocks that the integrator will combine are two Fuzzy Inference Systems (FIS) in charge of tracking and reaction control, respectively. The integrator block is called a Weighted Fuzzy Inference System (WFIS) and assigns weigh...

Despite of the popularity of the fuzzy Failure Mode and Effects Analysis (FMEA) methodology, there are several limitations in combining the Fuzzy Inference System (FIS) and the Risk Priority Number (RPN) model. Two main limitations are: (1) it is difficult and impractical to form a complete fuzzy rule base when the number of required rules is large; and (2) fulfillment of the monotonicity prope...

This report takes advantage of Neural Networks (NN) and Fuzzy Inference Systems (FIS) in order to design a system suited to predict time series. We choose the solution of the Mackey{Glass time delay diierential equation in the chaotic domain as a sample problem. Fuzzy rules are generated from the sample data. The system performance is improved by means of Evolution Strategy (ES). The rules of t...

ABSTRACT-This paper proposed a control scheme based on fuzzy logic for a methanol water system of bubble cap distillation column. Fuzzy rule base and Inference System of fuzzy (FIS) is planned to regulate the reflux ratio (manipulated variable) to obtain the preferred product composition (methanol) for a distillation column. Comparisons are made with conventional controller and the results conf...

The present paper aimed at developing an approach based on Fuzzy Inference System (FIS) for measuring of knowledge sharing in the organization. In recent years there has been increasing interest in the knowledge sharing by experts and managers in the world, according to increasing importance of knowledge as the key source of competitive advantage, organizations have made serious effort to find ...

The need and importance of automatically recognizing emotions from human speech has grown with the increasing role of human-computer interaction applications. This paper explores the detection of domain-specific emotions using a fuzzy inference system to detect two emotion categories, negative and nonnegative emotions. The input features are a combination of segmental and suprasegmental acousti...

Fuzzy expert systems are one of the most practical intelligent models with the high potential for managing uncertainty associated to the medical diagnosis. In this paper, a fuzzy inference system (FIS) for diagnosing of acute lymphocytic leukemia in children has been introduced. The fuzzy expert system applies Mamdani reasoning model that has high interpretability to explain system results to e...

Fusion of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) have attracted the growing interest of researchers in various scientific and engineering areas due to the growing need of adaptive intelligent systems to solve the real world problems. ANN learns from scratch by adjusting the interconnections between layers. FIS is a popular computing framework based on the concept of ...