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There is a number of frameworks for the general task of classification available for free usage on the Internet. However, software to generate fuzzy classification systems using the genetic approach is scarce. In this work, we present the FCABASED RULE GENERATOR framework to automatically generate fuzzy classification systems based on a genetic rule selection process. Such rules are extracted from...
Procedural content generation (PCG) is concerned with automatically generating game content, such as levels, rules, textures and items. But could the content generator itself be seen as content, and thus generated automatically? This would be very useful if one wanted to avoid writing a content generator for a new game, or if one wanted to create a content generator that generates an arbitrary amount...
In this paper, a self-adaptive differential evolution algorithm (SaDEA) is proposed for solving conventional economic dispatch (ED) problem with transmission losses consideration. The purpose of ED problem is to minimize the total fuel cost of thermal power plants associated with the technical operation and economical constraints. The software development has been performed within the mathematical...
Optimal Power Flow (OPF) is one of the most vital tools for power system operation analysis, which requires a complex mathematical formulation to find the best solution. Conventional methods such as Linear Programming, Newton-Raphson and Non-linear Programming were previously offered to tackle the complexity of the OPF. However, with the emergence of artificial intelligence, many novel techniques...
Dynamic optimization is one of the important research area in the intelligence computation field. For a decade, various dynamic benchmark test functions have been put forward. Generally speaking, though these functions help to improve a lot on the dynamic algorithms design, the fact that the whole landscape might affects the algorithm's performance rather than that of the way it changes is ignored...
This paper presents robust tuning of Proportional Integral Derivative Power System Stabilizers (PID-PSS) using artificial intelligence (AI) techniques. Tow heuristic methods, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used to PID-PSS parameters tuning minimizing an objective function and results are compared with each other which Eigen value analysis is used for comparison. The...
This paper proposes a hybrid evolutionary algorithm to solve the maintenance-scheduling problem for thermal generating units. The proposed approach uses a hybrid Fuzzy-Genetic Algorithm that implements Fuzzy Knowledge Based System to emulate the power plant personnel's experience, and uncertainties in the constraints, while a Genetic Algorithm optimizes the total generating cost and the maintenance...
The Optimal sizing and placement of distributed generators has received considerable attention from researchers recently. This paper presents an extensive review of the different solution methods found in the literature and is intended as a guide for those interested in the problem or intending to do additional research in the area. The assumptions made and a brief description of the solution methods...
A comparative analysis using different intelligent techniques has been carried out for the economic load dispatch (ELD) problem considering line flow constraints for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of this paper is to minimize the total production cost of the thermal power generation. Economic load dispatch (ELD) has been applied...
As the traditional negative selection, clonal selection algorithms predefine one part of antigens to be self (the training set) in intrusion detection applications, but in practice the self is difficult to define and can change over time. With the change of the self, error detection rate increases sharply. A recently developed hypothesis in immunology, the Danger Theory, states that our immune system...
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