This paper discussed the implementation of Particle Swarm Optimization (PSO) to optimize a Fuzzy Model Reference Learning Controller (FMRLC) for tanker ship. FMRLC is developed by synthesizing several basic ideas from fuzzy set and control theory. It can achieve the heading regulation of tanker ship exposed to plant changes and disturbances by adjusting the rules in a direct fuzzy controller so...

In this chapter we focus on three bio-inspired algorithms and their combinations with fuzzy rule based systems. Rule Based systems are widely being used in decision making, control systems and forecasting. In the real world, much of the knowledge is imprecise and ambiguous but fuzzy logic provides for systems better presentations of the knowledge, which is often expressed in terms of the natura...

We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on the MSSA and information granulation (IG). The MSSA is a multi-objective optimization algorithm whose search method is associated with the analysis of the solution space. The multi-objective mechanism of MSSA is realized using a non-dominated sorting-based multi-object...

In this study, we introduce an advanced architecture of genetically optimized Hybrid Fuzzy Neural Networks (gHFNN) and develop a comprehensive design methodology supporting their construction. A series of numeric experiments is included to illustrate the performance of the networks. The construction of gHFNN exploits fundamental technologies of Computational Intelligence (CI), namely fuzzy sets...

This paper presents some results related to the optimal tuning of fuzzy models of magnetic levitation systems as widely used nonlinear processes. A modeling approach is given. The Takagi-Sugeno fuzzy models of the process (which is first stabilized) are obtained by the modal equivalence principle, where the rule consequents contain the state-space models of the stabilized process linearized at ...

Type-2 (T2) fuzzy variable is an extension of an ordinary fuzzy variable. In fuzzy possibility theory, T2 fuzzy variable is defined as a measurable map from the universe to the set of real numbers, and the possibility of a T2 fuzzy variable takes on a real number is a regular fuzzy variable (RFV). T2 fuzziness, which is usually used to handle linguistic uncertainties, can be described as T2 fuz...

E-learning model is examined of three major dimensions. And each dimension has a range of indicators that is effective in optimization and modeling, in many optimization problems in the modeling, target function or constraints may change over time that as a result optimization of these problems can also be changed. If any of these undetermined events be considered in the optimization process, t...

We present a fuzzy optimization problem in business and economics. In this problem, a fuzzy price is determined by using a linear two degree demand functions. The objective is to find the optimal fuzzy revenue, which is derived from the fuzzy price. We use level (λ, 1) interval-valued fuzzy numbers to consider the fuzzy price and the fuzzy revenue. Using signed distance to defuzzify, we can obt...

The concept of duality plays an important role in optimization theory .In this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear programming problems using breaking point and duality theory. By using the proposed method the fuzzy optimal solution of fully fuzzy linear programming problem with inequality constraints has been obtained. To illustrate the prop...