Search Results - (( using two optimization algorithm ) OR ( evolution optimization means algorithm ))

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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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

“…Algorithms; Evolutionary algorithms; Mean square error; Optimization; Parameter estimation; Photovoltaic cells; Coefficient of determination; DEAM; Five parameters; Hybrid differential evolution; Improved differential evolutions; IV characteristics; Photovoltaic modules; Root mean square errors; Iterative methods; algorithm; artificial intelligence; electromagnetic method; error analysis; experimental study; photovoltaic system…”

Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

“…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”

Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach by Lai, V., Ahmed, Ali Najah, Malek, Marlinda Abdul, El-Shafie, Ahmed, El-Shafie, Amr

“…GP is a meta-heuristic search and optimization technique based on natural evolution. The control and optimization parameters in this study are tuned. …”
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Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

“…Roadways and telephone systems are the examples of them. Genetic Algorithms (GA), pioneered by John Holland, applies the principle of evolution found in nature to the problem of finding an optimal solution. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review by Diandra Chika Fransisca, Sukono, Diah Chaerani, Nurfadhlina Abdul Halim

Optimizing crystal size distribution based on different cooling strategies in batch crystallization process by Siti Zubaidah, Adnan, Noor Asma Fazli, Abdul Samad

“…The crystallization process was developed and simulated in Matlab software using a potash alum in the water system. Four optimization algorithms were proposed with different objective functions, such as maximizing mean crystal size (I), minimizing coefficient of variation (II), minimizing nucleus-grown crystals (III), and maximizing CSD (IV). …”
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Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach by Lai V., Ahmed A.N., Malek M.A., El-Shafie A., El-Shafie A.

“…GP is a meta-heuristic search and optimization technique based on natural evolution. The control and optimization parameters in this study are tuned. …”

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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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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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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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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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…This study is primarily aimed at investigating two issues in genetic algorithm (GA) and one issue in conformational search (CS) problems. …”
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