Search Results - (( based optimisation based algorithm ) OR ( evolution optimization using algorithmic ))

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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B-spline curve fitting with different parameterization methods by Kheng, Jia Shen

“…Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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A self‐configured link adaptation for green LTE downlink transmission by Salman, Mustafa Ismael, Ng, Chee Kyun, Noordin, Nor Kamariah, Mohd Ali, Borhanuddin, Sali, Aduwati

“…Then, a self‐configured link adaptation (SCLA) algorithm is developed to ensure that the priority weights related to EE and SE are adapted according to network load with the use of real‐time cross‐layer optimization. …”
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A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

“…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

“…The first level searches for the appropriate model order while the second level computes the optimal/sub-optimal corresponding parameters. The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm by Salami, Momoh Jimoh Eyiomika, Tijani, Ismaila, Isqeel , Abdullateef Ayodele, Aibinu, Abiodun Musa

“…A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). …”
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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. …”
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Reliably optimal PMU placement using disparity evolution-based genetic algorithm by Matsukawa, Yoshiaki, Othman, Mohammad Lutfi, Watanabe, Masayuki, Mitani, Yasunori

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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.

“…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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Performance comparison of differential evolution and particle swarm optimization in constrained optimization by Iwan, Mahmud, Akmeliawati, Rini, Faisal, Tarig, Al-Assadi, Hayder M.A.A.

“…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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A New Bats Echolocation-based Algorithm for Single Objective Optimisation by N. M., Yahya, Tokhi, M. Osman, Kasdirin, Hyreil Anuar

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Optimal HE-PWM inverter switching patterns using differential evolution algorithm by Muhammad Ikram, Mohd Rashid, Hiendro, Ayong, Anwari, Makbul

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A Modified Bats Echolocation-Based Algorithm for Solving Constrained Optimisation Problems by N. M., Yahya, Tokhi, M. O.

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Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

“…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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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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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

“…Global optimisation method includes differential evolution algorithm, which will be used in this research. …”
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