Search Results - (( evolution solution learning algorithm ) OR ( program implementation matching algorithm ))

Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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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. …”
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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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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

Needleman wunsch implementation for SPAM/UCE inline filter by Tamil E.M., Idris M.Y.I., Thong C.M., Jali M.Z., Madihah Mohd Saudi

PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Unlike existing OBL-based techniques, the PMT generates more than one candidate in multiple solution-space directions. To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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Evaluation of the effectiveness and efficiency of Wagner and Fischer algorithm in retrieving Hadith translated documents / Kamarul Arifin Muhamad by Muhamad, Kamarul Arifin

“…First experiment uses exact match, which is no method, is apply. Second experiment uses dynamic programmings apply with Wagner and Fischer algorithm.…”
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Dual optimization approach in discrete Hopfield neural network by Guo, Yueling, Zamri, Nur Ezlin, Mohd Kasihmuddin, Mohd Shareduwan, Alway, Alyaa, Mansor, Mohd. Asyraf, Li, Jia, Zhang, Qianhong

“…To evaluate the effectiveness of the Hybrid Differential Evolution Algorithm and Swarm Mutation in the learning and retrieval phases, several performance metrics are employed in terms of synaptic weight management, learning errors, testing errors, energy profiles, solution variations, and similarity for 10 different cases. …”
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Selection of prospective workers using profile matching algorithm on crowdsourcing platform by Cucus, Ahmad, Aji, Luhur Bayu, Al Fahim, Mubarak Ali, Aminuddin, Afrig, Farida, Lilis Dwi

“…These criteria become variables that are used in the profile matching algorithm to find workers who best match the profiles offered. …”
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Implementing case-based reasoning approach to framework documentation by Hajar M.J., Lee S.P.

Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

“…On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. …”
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Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin by Shamsudin, Farah Syadiyah

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PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

“…Unlike existing OBL-based techniques, the PMT generates more than one candidate in multiple solution-space directions. To evaluate the PMT's performance and adaptability, the PMT has been applied to four contemporary meta-heuristic algorithms, differential evolution (DE), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), to solve 15 well-known benchmark functions. …”
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

Can recognition using LABVIEW / Jamilah Othman by Othman, Jamilah

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An integrated algorithm of analytical network process with case-based reasoning to support the selection of an ideal football team formation and players by Mohammad Zukuwwan, Zainol Abidin

“…The system can provide the team formation and players, and calculate the strength of the KFA team to justify its winning and loss of 2019 FA Cup and Malaysia Cup final matches respectively. This system can help coaches to solve problem regarding the strong team development with available players and motivate the use of decision technologies in sports able to match the results from the real world implementation.…”
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Crossover and mutation operators of genetic algorithms by Lim, Siew Mooi, Md. Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mustapha, Aida, Leong, Kuan Yew

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Crossover and mutation operators of genetic algorithms by Siew, Mooi Lim, Md. Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mustapha, Aida, Leong, K. Y.

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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

“…To verify our proposed approach, four Arabic benchmark datasets for sentiment analysis are used since there are only a few studies in sentiment analysis conducted for Arabic language as compared to English. The proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. …”
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