this study focuses on the forecasting of energy demands of residential and commercial sectors using linear and exponential functions. the coefficients were obtained from genetic and particle swarm optimization (pso) algorithms. totally, 72 different scenarios with various inputs were investigated. consumption data in respect of residential and commercial sectors in iran were collected from the ...

Crack identification is a very important issue in mechanical systems, because it is a damage that if develops may cause catastrophic failure. In the first part of this research, modal analysis of a multi-cracked variable cross-section beam is done using finite element method. Then, the obtained results are validated usingthe results of experimental modal analysis tests. In the next part, a nove...

Power system must be operated in such a way that both real and reactive powers are optimized simultaneously. Reactive powers should be optimized to provide better voltage profile as well as to reduce system losses. The four objectives of minimization of fuel cost, minimization of emission, minimization of losses and increasing stability by minimizing system stability index, these are conflictin...

This work presents the definition and solution of an optimization model using techniques based on the Particle Swarm Optimization (PSO) algorithm or the Particle Swarm Optimization and Genetic Algorithms. The model corresponds to the Joint Replenishment Problem in a system operating with quantity discounts. Results are shown in problems, where their size makes it difficult or impossible to esta...

Cryptanalysis with Computational Intelligence has gained much interest in recent years. This paper presents an approach for breaking the key used in Simplified-Data Encryption Standard (S-DES) using Genetic algorithm (GA), Particle Swarm Optimization (PSO) and a novel approach called Genetic Swarm Optimization (GSO) obtained by combining the effectiveness of GA and PSO. Ciphertext-only attack i...

This paper presents an optimal design of linear phase digital high pass finite impulse response (FIR) filter using Improved Particle Swarm Optimization (IPSO). In the design process, the filter length, pass band and stop band frequencies, feasible pass band and stop band ripple sizes are specified. FIR filter design is a multi-modal optimization problem. An iterative method is introduced to fin...

This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute v...

This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute v...

Particle swarm optimization (PSO) has received increasing attention in solving multi-objective economic dispatch (ED) problems in power systems because of parallel computation, faster convergence, and easier implementation. This paper presents a detailed overview of multi-objective particle swarm optimization (MOPSO) and provides a comprehensive survey on its applications in power system econom...

A distributed variant of multi-objective particle swarm optimization called multi-objective parallel asynchronous particle swarm optimization (MOPAPSO) was used to develop a new optimization-based synthesis routine for Grashof mechanisms. By using a formal multi-objective handling scheme based on Pareto dominance criteria, the need to pre-weight competing objective functions is removed and the ...