This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting.
Some engineering optimization methods, including operational-pattern optimization, satisfactory optimization with soft constraints adjustment, multi-objective intelligent optimization methods, and a comprehensive optimal control technique for a large-scale zinc electrolysis process are illustrated.
By calculating theoretical unbalance responses and measuring original unbalance vibrations, a new type of intelligent optimization technique, genetic algorithm, is applied to optimize the correction masses to minimize residual vibrations at selected measurement locations and balancing speeds.
Taking into consideration this new frame, intelligent optimization techniques emerge as the only suitable way to optimally design this smart grid.
The particle swarm optimization (PSO) algorithm which is one of the most important intelligent optimization algorithms and is classified in the swarm intelligence field has been used to solve the problem (Kaveh 2014 and Olsson 2011).
Two intelligent optimization tools of GA and PSO have been used to find a near optimal forest road profile, connecting specified endpoints considering restrictions associated with forest road profile design with cost evaluation.
In this paper, we propose a multi-variable intelligent matching pursuit algorithm (MIMP), which can solve l0 minimization problem essentially by taking the advantage of the intelligent optimization algorithm in solving combinatorial optimization problems and searching for the global optimal solution to improve the performance of image reconstruction.
Intelligent optimization techniques for transcoding. .
This is part of an intelligent optimization system for multiobjective performance optimization of power distribution operations.
The immune algorithm is a kind of intelligent optimization algorithm based on features of biological immune systems [20, 21, 22].
Therefore lens system design provides ideal problems for intelligent optimization algorithms.
