Search Results - (evolution OR solution) ((optimization technique) OR (learning techniques))

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. …”
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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. …”
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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.

“…ECHT is considered to be a flagship ensemble technique till date for constrained optimization problems, whereas SRDE employs a parent selection mechanism for constrained optimization. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

“…The performance of proposed method is compared with several feature selection techniques in order to prove their superiority using ten datasets obtained from UCI machine learning repository.…”
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Critical review of object detection techniques for traffic light detection in intelligent transportation systems by Muhammad Adhwa, Mohd Salemi, Muhammad Arif, Mohamad

“…This study provides a critical review of object detection techniques specifically for traffic light detection, evaluating the evolution of machine learning frameworks, deep learning architectures, and hybrid optimization models. …”
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Modeling of Remora Optimization with Deep Learning Enabled Heavy Metal Sorption Efficiency Prediction onto Biochar by Almalawi, A., Khan, A.I., Alqurashi, F., Abushark, Y.B., Alam, M.M., Qaiyum, S.

“…Besides, deep belief network (DBN) model was employed for prediction and the efficiency of the DBN model is optimally adjusted with utilize of RO technique. The experimental validation of the RODL-HMSEP technique ensured the promising performance of the RODL-HMSEP technique on the prediction of sorption efficiency onto biochar over other methods The experimental validation of the RODL-HMSEP technique ensured the promising performance of the RODL-HMSEP technique on the prediction of sorption efficiency onto biochar over other methods. …”
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Modeling of Remora Optimization with Deep Learning Enabled Heavy Metal Sorption Efficiency Prediction onto Biochar by Almalawi, A., Khan, A.I., Alqurashi, F., Abushark, Y.B., Alam, M.M., Qaiyum, S.

“…Besides, deep belief network (DBN) model was employed for prediction and the efficiency of the DBN model is optimally adjusted with utilize of RO technique. The experimental validation of the RODL-HMSEP technique ensured the promising performance of the RODL-HMSEP technique on the prediction of sorption efficiency onto biochar over other methods The experimental validation of the RODL-HMSEP technique ensured the promising performance of the RODL-HMSEP technique on the prediction of sorption efficiency onto biochar over other methods. …”
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Optimizing railway safety by analyzing human reliability techniques - A review by M. E., M. Aliza, Ahmad Fitri, Yusop, Mohd Adnin, Hamidi, Muhammad Azri, Muhammed Nor

“…This review provides a comprehensive analysis of the evolution of HRA, from the first-generation techniques to the third-generation approaches currently in use. …”
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Optimization and design of machine learning computational technique for prediction of physical separation process by Haiqing Li, Chairun Nasirin, Azher M. Abed, Dmitry Olegovich Bokov, Lakshmi Thangavelu, Haydar Abdulameer Marhoon, Md Lutfor Rahman

“…Indeed, this work indicates application of machine learning technique for a real physical system and optimization of process parameters to achieve the target. …”
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Review of firewall optimization techniques by Shakirah, Saidin, Mohamad Fadli, Zolkipli

“…As a result, this paper will be useful for researchers who are interested in learning more about firewall optimization techniques.…”
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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

“…The proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. …”
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Neural Network Preference Learning Approaches For Improving Agent-Based Meeting Scheduling Problems by Tang, En Lai

“…This strategy was extended with “preference estimation” technique to optimize the user preference level of negotiation outcome. …”
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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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Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development by Salehmin M.N.I., Tiong S.K., Mohamed H., Umar D.A., Yu K.L., Ong H.C., Nomanbhay S., Lim S.S.

“…This review uniquely focuses on harnessing the synergy between ML and computational modeling (CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction (HER) catalysts and various hydrogen production processes (HPPs). …”

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

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A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operato... by Alsa’Di, Kawthar, Nik Long, Nik Mohd Asri

“…Moreover, a new hybrid technique which is the combination of deep learning artificial neural network and finite difference method (FDL-ANN) is developed to approximate the solution of higher order VFIDEs. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman by Isman, Muhammad Iskandar

“…ACO algorithm is the best solution because it included the optimization technique to optimized the result based on the data criteria needs. …”
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Malware detection through machine learning techniques by Amer, Ahmed, Abdul Aziz, Normaziah

“…We conclude that Machine Learning techniques are practical to be applied as anti-malware solutions including for Zero-day attacks.…”
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An enhanced metaheuristic approach to solve quadratic assignment problem using hybrid technique by Hameed, Asaad Shakir

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