Search Results - evolution ((((mining techniques) OR (learning techniques))) OR (optimization techniques))

Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…Many statistical and data mining techniques have been used to predict time series stock market. …”
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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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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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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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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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Global trends of educational data mining in online learning by Nie Hui Ling, Chwen Jen Chen, Chee Siong Teh, Dexter Sigan John, Looi Chin Ch’ng, Yoon Fah Lay

“…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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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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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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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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Accelerator-based human activity recognition using voting technique with NBTree and MLP classifiers by Azmi M.S.M., Sulaiman M.N.

“…In this study, an accelerator-based activity recognition model using voting technique was proposed. Two machine learning classifiers, Naive Bayes Tree (NBTree) and Multilayer Perceptron (MLP), were used as ensemble classifiers in the voting technique. …”

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). …”

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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Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. The evolution of authoritative immunofingerprint mining technology is exerting a growing influence on comprehensive cancer diagnosis biology. …”
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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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Reinforcement Learning Model Selection for Resource Allocation and Subcarrier Spacing Optimization in 5G Sliced Spectrum Networks by Samidi F.S., Radzi N.A.M., Aripin N.M.

“…The evolution of 5G technology presents unique challenges and opportunities for optimizing network performance through advanced techniques such as Reinforcement Learning (RL). …”

A study on biomolecular sequence alignment using machine learning techniques by Othman, Muhamad Razib, Salim, Naomie, Abdul Jalil, Rozita, Deris, Safaai, Mat Yatim, Safie, Md. Illias, Rosli

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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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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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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…To show the effectiveness of EMA-DL, comparison studies were conducted among other metaheuristic optimizers that were also used to optimize the DL parameters viz, Particles Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE) as well as the Adaptive Moment Estimation (ADAM). …”
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