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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

“…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Dynamic Economic Dispatch For Large Scale Power Systems: A Lagrangian Relaxation Approach by Ab Ghani, Mohd Ruddin, Hindi, K. S.

“…Otherwise, Dantzig-Wolfe decomposition is invoked, using almost all the information generated during subgradient optimization to ensure a speedy conclusion. The computational efficiency of the algorithm renders it suitable for on-line dispatch.…”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…The pandemic has resulted in unpredictable customers’ purchasing patterns post-pandemic has rendered heuristic-based forecasting large forecast errors, which leads to poor decision-making. …”
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Predictive analysis of dengue outbreak based on an improved salp swarm algorithm by Zuriani, Mustaffa, M. H., Sulaiman, Khairunnisa Amalina, Mohd Rosli, Mohamad Farhan, Mohamad Mohsin, Yuhanis, Yusof

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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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Integration of simulation for ergonomics assessment in operation control centre (railway industries) / Adib Zulfadhli Mohd Alias by Adib Zulfadhli, Mohd Alias

“…This study will focus on the translation of the CAD/Revit model into simulation software, either directly or through the intermediate stage of rendering package. Complete CAD/Revit model can be used to generate simulation model by straight forward translation of the whole model or with the algorithms for optimization. …”
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WHALE OPTIMIZATION NEURAL NETWORK FOR DAILY WATER LEVEL FORECASTING CONSIDERING THE CHANGING CLIMATE by Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman, Teng, Yeow Haur

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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems by Umar D.A., Alkawsi G., Jailani N.L.M., Alomari M.A., Baashar Y., Alkahtani A.A., Capretz L.F., Tiong S.K.

“…Furtherly, Artificial Intelligence (AI)-based MPPT algorithms were proposed for the WEHS as either standalone or integrated with the traditional MPPT methods. …”

Development of intelligent evaluation system for product end-of-life selection strategy by Zakri, Ghazalli

“…This study integrates the travelling salesman problem with genetic algorithm (TSP-GA) for finding the optimal disassembly sequence and disassembling the EOL product. …”
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Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots by Shojaei, Taha Roodbar, Mohd Salleh, Mohamad Amran, Mobli, Hossein, Aghbashlo, Mortaza, Tabatabaei, Meisam

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Augmented Reality Framework For Symbian Mobile Devices by Oui, Wei Wei

“…Open source libraries such as OpenGL and OpenCV are used to develop mobile AR framework. Optimized algorithms are used to ensure that AR application running smooth. …”
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Intelligent traffic lights using Q-learning by Mohd Yusop, Muhammad Aminuddin, Mansor, Hasmah, Gunawan, Teddy Surya, Nasir, Haidawati,

“…Q-learning derives benefits from past experiences and determines the optimal course of action based on them. The performance of the proposed system has been measured against that of the traditional system, which is a fixed time cycle system. …”
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Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units by Peddakapu, K., M. R., Mohamed, M. H., Sulaiman, Srinivasarao, P., Kishore, D. J. K., P. K., Leung

“…Different types of metaheuristic optimisation methods like teaching–learning-based optimisation (TLBO) and cuckoo search algorithms are suggested to acquire the optimal gain values of the proposed controllers. …”
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Automated fault detection and extraction under gas chimneys using hybrid discontinuity attributes by Imran, Q.S., Siddiqui, N.A., Latiff, A.H.A., Bashir, Y., Khan, M., Qureshi, K., Al-Masgari, A.A.-S., Ahmed, N., Jamil, M.

“…3D-seismic data have increasingly shifted seismic interpretation work from a horizons-based to a volume-based focus over the past decade. …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

“…The idea of hybridizing the newly developed biogeography based optimization algorithm (BBO) with variable neighborhood structure (VNS) is proposed in order to produce a high performance initial schedule in terms of minimum completion time, tardiness and flow time within reasonable amount of time. …”
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