this paper presents a new strategy based on multi-stage fuzzy (msf) pid controller based on artificial bee colony (abc) for damping power system stabilizer (pss) in multi-machine environment. the recent studies in artificial intelligence demonstrated that the abc optimization is strong intelligent method in complicated stability problems. also, finding the parameters of pid controller in power ...

Guided Local Search (GLS) is an intelligent search scheme for combinatorial optimization problems. A main feature of the approach is the iterative use of local search. Information is gathered from various sources and exploited to guide local search to promising parts of the search space. The application of the method to the Travelling Salesman Problem and the Quadratic Assignment Problem is exa...

This paper provides a framework for optimization of Induction Hardening parameters by using Intelligent Techniques. Heat Treatment of Iron Alloy is carried out for improving Mechanical and Metallurgical properties like Ductility, Toughness, Hardness, and Tensile Strength etc. These properties play a important role for selection of material in Manufacturing Field. Induction Hardening on iron all...

With the fast proliferation of various computational paradigms, from Web-based to wireless and mobile computing, intelligent data processing and security have become cross-cutting features of large scale Internet-based system. On the one hand, there is data being generated everywhere, from various sources and heterogenous formats (such as document repositories, business process data, network da...

This paper presents an application of the intelligent search technique for the parameters optimization of conventional automatic generation control (AGC) systems. An efficient intelligent search technique, which is Adaptive Tabu Search (ATS), is employed to demonstrate the effectiveness of the intelligent search techniques in the tuning of the AGC parameters. A two-area non-reheat thermal syste...

When the systems under investigation are complex, the analytical solutions to these systems become impossible. Because of the complex stochastic characteristics of the systems, simulation can be used as an analysis tool to predict the performance of an existing system or a design tool to test new systems under varying circumstances. However, simulation is extremely time consuming for most probl...

Our paper focuses on the generation of optimal test sequences and test cases using Intelligent Agents for highly reliable systems. Test sequences support test case generation for these types of systems. Our system is modeled through UML state charts. Conventional test generation techniques do not worry about optimization and dynamic nature of such systems. In the case of highly reliable Softwar...

This article introduces two swarm intelligent algorithms, a group search optimizer (GSO) and an artificial fish swarm algorithm (AFSA). A single intelligent algorithm always has both merits in its specific formulation and deficiencies due to its inherent limitations. Therefore, we propose a mixture of these algorithms to create a new hybrid optimization algorithm known as the group search-artif...

For a decade swarm Intelligence is concerned with the design of intelligent systems by taking inspiration from the collective behaviors of social insects. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. This paper focuses on the procedure of most successful methods of optimization techniques inspired by Swarm Intelligence: Ant Colony Optimization (ACO) and P...

A novel intelligent neural optimizer with two objective functions is designed for electrical distribution systems. The presented method is faster than alternative optimization methods and is comparable with the most powerful and precise ones. This optimizer is much smaller than similar neural systems. In this work, two intelligent estimators are designed, a load flow program is coded, and a spe...