Search Results - (( motion optimization model algorithm ) OR ( evolution optimization based algorithm ))

The impact of executive function and aerobic exercise recognition in obese children under deep learning by JING, XIN, ABDULLAH, BORHANNUDIN, ABU SAAD, HAZIZI, YANG, XIANGKUN

“…Initially, a motion recognition model based on STN and Lucas–Kanade optical flow algorithm optimization was constructed. …”
Get full text
Get full text

Multilevel optimization for dense motion estimation by Saaban, Azizan, Kalmoun, El Mostafa, Ibrahim, Haslinda, Ramli, Razamin, Omar, Zurni

“…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
Get full text
Get full text
Get full text

Reliably optimal PMU placement using disparity evolution-based genetic algorithm by Matsukawa, Yoshiaki, Othman, Mohammad Lutfi, Watanabe, Masayuki, Mitani, Yasunori

“…In this paper, Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied. …”
Get full text
Get full text
Get full text

A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

“…DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimization. …”
Get full text
Get full text
Get full text

A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

“…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
Get full text
Get full text

Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

“…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
Get full text
Get full text

Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
Get full text
Get full text

Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

Get full text
Get full text

MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION by SAINI, SANJA Y

Get full text
Get full text

Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

“…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
Get full text
Get full text
Get full text

SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

“…This study presents the identification of slow drift motions of floating structures from model test data. …”
Get full text
Get full text

Multiobjective differential evolution algorithm-based sizing of a standalone photovoltaic water pumping system by Muhsen D.H., Ghazali A.B., Khatib T.

Minimizing machining airtime motion with an ant colony algorithm by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

Get full text
Get full text

Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses by Tarajo, Buba Ahmed, Lee, Lai Soon

“…This paper proposes a hybrid differential evolution with particle swarm optimization (DE-PSO) algorithm to solve the UTNDP, aiming to simultaneously optimize route configuration and service frequency with specific objectives in minimizing both the passengers’ and operators’ costs. …”
Get full text
Get full text
Get full text

Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

“…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
Get full text
Get full text
Get full text

A review on particle swarm optimization algorithm and its variants to human motion tracking by Saini, S., Rambli, D.R.B.A., Zakaria, M.N.B., Sulaiman, S.B.

“…Several approaches have been proposed in the literature using different techniques.However, conventional approaches such as stochastic particle filtering have shortcomings in computational cost, slowness of convergence, suffers from the curse of dimensionality and demand a high number of evaluations to achieve accurate results. Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space.This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. …”
Get full text
Get full text

Robust multi-user detection based on hybrid grey wolf optimization by Ji, Yuanfa, Fan, Z ., Sun, X., Wang, S., Yan, S., Wu, S., Fu, Q., Kamarul Hawari, Ghazali

“…The simulation results show that the iteration times of the multi-user detector based on the proposed algorithm is less than that of genetic algorithm, differential evolution algorithm and Grey wolf optimization algorithm, and has the lower BER.…”
Get full text
Get full text
Get full text
Get full text
Get full text

Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica... by Stonier, A.A., Chinnaraj, G., Kannan, R., Mani, G.

“…Purpose: This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms. Design/methodology/approach: The optimal modulation index along with the switching angles are calculated for an 11 level inverter. …”
Get full text
Get full text

Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
Get full text
Get full text
Get full text