Search Results - (( using evolution a algorithm ) OR ( based optimization modified algorithm ))

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). …”
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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. …”
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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. …”
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The PID controller parameter tuning based on a modified differential evolutionary optimization algorithm for the intelligent active vibration control of a combined single link robotics flexible manipulator by Moloody, Abbas, As’arry, Azizan, Hong, Tang Sai, Raja Kamil, ., Zolfagharian, Ali

“…In this strategy, a Strictly Bearish Distributed Exponential Function (SBDEF) has been used as the main target and the criteria and indicators for evaluating and measuring the optimal performance of differential evolution are the Integral Absolute Error (IAE) rate and the PID controller parameter values. …”
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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

“…The aim of the algorithm is to improve a controller performance (minimize the overshoot, settling time, IAE/ITAE and achieving zero steady state error) when used for a DC servomotor application. …”
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A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Chuah, Joon Huang, Dhanapal, Saroja, Kendall, Graham

“…M-MOPSO is compared with four other algorithms namely, MOPSO, Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm based on Decompositions (MOEA/D) and Multi-Objective Differential Evolution (MODE). …”
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Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq

“…The unified RBF model is then used for autotuning the PID controller using the DE algorithm. …”
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Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq, Yaakub, Mohd Fauzi

“…The unified RBF model is then used for autotuning the PID controller using the DE algorithm. …”
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Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems by Salman, Mustafa Ismael

“…To achieve this objective, an iterative approach based on swarm intelligence is used to find the optimal CQI threshold at which the competing criteria are optimized. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…In order to train Ridgelet probabilistic neural network, a modified differential evolution algorithm with new mutation phase, crossover process, and selection mechanism is introduced. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

“…The evaluation process employs the Hypervolume (HV) indicator and Inverted Generational Distance (IGD) to scrutinize solution efficacy and coverage. The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
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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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Quality of service and scheduling performance optimization in LTE networks / Abubakar Auwal Idris by Abubakar Auwal , Idris

“…This research proposed an optimal downlink scheduling algorithm called Video Real-Time Scheduling Algorithm (VRTSA) to support real-time traffic of video in LTE network. …”
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Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin by Ong, Chung Sin

“…Metaheuristic is one of the “approximation methods” that is able to find practically acceptable solutions especially for large-scale problems within a limited amount of time. Genetic Algorithms (GA) which is based on biological evolution is one of the metaheuristics that has been successfully applied to JSSP. …”
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Accurate numerical treatment on a stochastic SIR epidemic model with optimal control strategy by Ghosh, Indranil, Rashid, Muhammad Mahbubur, Ghosh, Pallabi, Mawa, Shukranul, Roy, Rupal, Ahsan, Md Manjurul, Gupta, Kishor Datta

“…In this paper, a numerical study has been undertaken on the susceptible-infectedrecovered (SIR) epidemic model that encompasses the mechanisms of the evolution of disease transmission; a prophylactic vaccination strategy in the susceptible populations, depending on the infective individuals. …”
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Development of a robust intelligent controller for a semi-active car suspension system by Abas, Hesham Ahmed Abdul Mutleba

“…Commonly, the Fuzzy rules are optimized using offline optimization methods such as Differential Evolutionary (DE), Particle Swarms Optimization (PSO), or Artificial Neural Network (ANN) algorithms. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…In addition, two novel Jaya-based methods namely, the modified Jaya (MJaya) algorithm and quasi-oppositional modified Jaya (QOMJaya) algorithm are proposed to solve different MOOPF problems. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

“…This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. …”
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Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…Besides, some real data sets were examined to validate the proposed algorithm. Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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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. …”
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