Search Results - evolution learning technique

Modeling 2D appearance evolution for 3D object categorization by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal

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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). …”

Methods of learning and writing jawi scripts within the Malay community: Past and present experiences by Fadzli, Adam, Daud, Ismail, Asyraf, Ab Rahman, Abdul Manan, Ali

“…This paper discusses some methods of learning and writing Jawi scripts within the Malay community and how the script writing system has gone through a systematic evolution through times due to requirements set by relevant authorities. …”
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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.

“…The median convergence traces have been compared with two different algorithms based on differential evolution, i:e: Ensemble of Constraint Handling Techniques (ECHT) and Stochastic Ranking Differential Evolution (SRDE). …”
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A New Hybrid K-Means Evolving Spiking Neural Network Model Based on Differential Evolution by Abdulrazak Yahya, Saleh, Haza Nuzly, Abdull Hamed, Siti Mariyam, Shamsuddin, Ashraf, Osman Ibrahim

“…Clustering is one of the essential unsupervised learning techniques in Data Mining. In this paper, a new hybrid (K-DESNN) approach to combine differential evolution and K-means evolving spiking neural network model (K-means ESNN) for clustering problems has been proposed. …”
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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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Assistive Technology For Disabilities: A Case Study Of Autism In Teaching And Learning Outcomes by Omar, Sarah, Bidin, Azman, Koo, Ah Choo

“…A number of studies have highlighted new teaching techniques. There has been a trend in moving towards e-learning technologies in (Agarwal, 2012) and (Kemp, 2015), where those strategies were part of pedagogy techniques in teaching children with special needs. …”
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Evolution, design, and future trajectories on bipedal wheel-legged robot: A comprehensive review by Zulkifli, Mansor, Irawan, Addie, Mohammad Fadhil, Abas

“…The analysis encompasses optimization techniques, sensor integration, machine learning, and adaptive control methods, evaluating their impact on robot capabilities. …”
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Concept Drift Evolution In Machine Learning Approaches: A Systematic Literature Review by Hashmani, M.A., Jameel, S.M., Rehman, M., Inoue, A.

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

“…Addressing these issues, this research proposes a new general opposition-based learning (OBL) technique inspired by a natural phenomenon of parallel mirrors systems called the parallel mirrors technique (PMT). …”
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Statistics in finance, operation research and forecasting

“…Readers will learn and appreciate the application of such techniques in their respective fields.…”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Addressing these OBL limitations, this research proposes a new general OBL technique inspired by a natural phenomenon of parallel mirrors systems called the Parallel Mirrors Technique (PMT). …”
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Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

“…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
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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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Comparison of detection model using machine learning on android malware / Muhammad Ikmal Ihsan by Ihsan, Muhammad Ikmal

“…The result of the comparison using the machine learning techniques for Android malware dataset discovered that SVM machine learning get the highest percentage with accuracy of 0.93. …”
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Global Trends of Educational Data Mining in Online Learning by Chen, Chwen Jen, Teh, Chee Siong, Dexter Sigan, John

“…Educational data mining (EDM) in online learning involves data mining techniques to analyze data from online environments to gain insights into student behavior, performance, and engagement. …”
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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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Lattice Imperfections in Intermetallic Ti-Al alloys: an X-Ray Diffraction study of the microstructure by the Rietveld method by Lee Liu Mei

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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

“…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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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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