Search Results - (( evolution optimization tree algorithm ) OR ( variable optimization strategy algorithm ))

Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks by Sanni, Mistura Laide, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Anwar, Farhat, Ahmed, Gharib Subhi Mahmoud

“…Thus this paper proposes a Differential Evolution based optimized mobile multicast routing algorithm for the shared tree architecture. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems by Yousefi M., Darus A.N., Yousefi M., Hooshyar D.

Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation by Bahomaid, Ameen A., Alsewari, Abdulrahman A., Zamli, Kamal Z., Alsariera, Yazan A.

“…This study presented the most recent variable interaction strength (VS) CT strategy using an enhanced variant in the greedy algorithm. …”
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Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm by Chong K.L., Lai S.H., Ahmed A.N., Wan Jaafar W.Z., El-Shafie A.

Differentially expressed wound-response-related proteins from a major agarwood-producing tree, Aquilaria malaccensis Lam. identified via 2-D electrophoresis by Lee, Shiou Yih, Samsuddin, Ahmad Syazwan, Lamasudin, Dhilia Udie, Mohamed, Rozi

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An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time by Mirhassani, S.M., Golroodbari, S.Z.M, Goiroodbari, S.M.M., Mekhilef, Saad

“…This paper presents an improved maximum power point tracking (MPPT) strategy for photovoltaic (PV) systems based on particle swarm optimization (PSO). …”
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Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems by Yousefi, M., Darus, A.N., Yousefi, M., Hooshyar, D.

“…In this paper, a new design strategy is presented where variable operating conditions, which better represent real-world problems, are considered. …”
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A swarm intelligent approach for multi-objective optimization of compact heat exchangers by Yousefi M., Yousefi M., Martins Ferreira R.P., Darus A.N.

Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

“…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm by Ng, Yeong Khang

“…To overcome the combinatorial optimization problem, Jaya algorithm is proposed to apply in this project since metaheuristic algorithm is fast in optimization and this strategy is named as CTJ. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…Improved mean fitness function values were also revealed in the TRS (11.63%) and EMPS (69.63%) assessments, surpassing the conventional algorithm. This proposed algorithm produced solutions with superior accuracy and consistency compared to various established metaheuristic strategies, including particle swarm optimizer, grey wolf optimizer, multi-verse optimizer, AOA, and a hybrid optimizer (average multi-verse optimizer-sine-cosine algorithm).…”
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Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis by Jamian, J.J., Abdullah, M.N., Mokhlis, Hazlie, Mustafa, M.W., Bakar, Ab Halim Abu

“…To overcome this problem, an efficient Global Particle Swarm Optimization (GPSO) algorithm is proposed in this paper, based on a new updated strategy of the particle position. …”
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Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines by Noroziroshan, Alireza

“…It confirms that the proposed genetic algorithm procedure is able to tackle the problem complexity and reach to optimal solutions in different production strategies. …”
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EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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Automatic control of flotation process using computer vision by Saravani, Ali Jahed

“…In addition, several algorithms were implemented to measure the other important image variables such as froth velocity,froth color and bubble collapse rate. …”
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Single and Multiple variables control using Tree Physiology Optimization by Halim, A.H., Ismail, I.

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A memory optimal BFGS neural network training algorithm by McLoone, Sean, Asirvadam , Vijanth Sagayan

“…This paper considers the implementation of a novel memory optimal neural network training algorithm which maximises performance in relation to available memory. …”
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Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system by Ghani, Muhamad Fadli

“…Due to the difficulty of concurrent hybrid design, the PSO algorithm was employed to determine the optimal control variables value. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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