An improvement of fast curvature based interpolation in image super resolution is proposed by using genetic algorithm optimization. The fast curvature based image super resolution requires low computation time, and it is suitable for real time video superresolution. This paper furthermore optimizes the parameters of FCBI based on genetic algorithm. Through the android device implementation, we ...

Particle Swarm Optimization (PSO) is an innovative and competitive optimization technique for numerical optimization with real-parameter representation. This paper examines the working mechanism of PSO in a principled manner with forma analysis and investigates the applicability of PSO on the Quadratic Assignment Problem (QAP). Particularly, the derived PSO operator for QAP is empirically studi...

We present a real-coded genetic algorithm that efficiently estimates parameters of a formant trajectory model. The genetic algorithm uses roulette-wheel selection and elitism to minimize the root mean square error between the observed formant trajectory and the model trajectory. Parameters, including vowel and consonant target values and coarticulation parameters, are estimated for a corpus of ...

In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition...

We apply evolutionary computations to Hop eld model of associative memory. Although there have been a lot of researches which apply evolutionary techniques to layered neural networks, their applications to Hop eld neural networks remain few so far. Previously we reported that a genetic algorithm using discrete encoding chromosomes evolves the Hebb-rule associative memory to enhance its storage ...

According to the characteristics that fatigue study cannot reveal fatigue mechanism and nonlinear influence factors of vehicle driving closed-loop system defects, this paper proposes a driver model inversion method for studying the driver's fatigue diagnosis. Furthermore, the new methods is divided into two steps: 1. using the forecast looks neural network model to build the driver vehicle road...

this paper describes an optimal design for multivariable pi controller with a high gain structure for an irregular system by genetic algorithm. pi controllers with a high gain structure leads to the asymptotic decomposition of the fast and slow modes in the closed loop system that have unique characteristics. the slow modes are asymptotically uncontrollable and unobservable; therefore, they hav...

In the real-world production planning problems there are many constraints that need to be considered. Usually, these constraints and interdependent and the optimization algorithms has to efficiently solve that. This paper presents the hybrid parameter-less evolutionary algorithm used for construction of an optimal production plan. The algorithm is based on genetic algorithm, but is modified to ...

Genetic algorithms (GAs) are vital members within the family biologically inspired algorithms. It has been proven that the performance of GAs is largely affected by the type of encoding schemes used to encode optimization problems. Binary and real encoding schemes are the most popular ones. However, it is still controversial to decide the superiority of one of them for GAs performance. Therefor...

In this study, the performance of an irreversible regenerative Brayton cycle is sought through power maximizations using finite-time thermodynamic concept in finite-size components. Optimizations are performed using a genetic algorithm. In order to take into account the finite-time and finite-size concepts in the current problem, a dimensionless mass-flow rate parameter is used to deploy ti...