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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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The division free parallel algorithm for finding determinant by Karim, Sharmila, Omar, Zurni, Ibrahim, Haslinda

“…A cross multiplication method for determinant was generalized for any size of square matrices using a new permutation strategy.The permutation is generated based on starter sets.However, via permutation, the time execution of sequential algorithm became longer.Thus, in order to reduce the computation time, a parallel strategy was developed which is suited for master and slave paradigm of the high performance computer.A parallel algorithm is integrated with message passing interface.The numerical results showed that the parallel methods computed the determinants faster than the sequential counterparts particularly when the tasks were equally allocated.…”
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Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli by Rosli, Muhammad Helmi

“…Each experiment highlight the advantages and disadvantages of the experimental architecture.The disadvantages from each experiment prompts the design of dynamic parallel partitioning and allocating framework. The case study use for this experiment is Sobel edge detection algorithm. …”
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Development of a heuristic procedure for balancing mixed-model parallel assembly line type II by Esmaeilian, Gholamreza

“…To solve these problems, two heuristic algorithms were developed and coded in MATLAB®. The first one allocates each model to only one parallel assembly line and achieves the initial arrangement of tasks with the minimum number of workstations for each line. …”
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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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WCDMA teletraffic performance improvement via power resource optimization using distributed parallel genetic algorithm by Prajindra S.K., Tiong S.K., Johnny Koh S.P., Yap D.F.W.

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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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

“…Hence using the proposed mathematical model for large size problem was time consuming and inefficient as so many job allocation values should be checked. …”
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Parallel guided image processing model for ficus deltoidea (Jack) moraceae varietal recognition by Abdul Rahman, Prof. Dr. Mohd Nordin

“…From the results, the sequential complex image processing model and computational flow design are significantly improved when executed through parallel model under multi-cores computer system. As the number of cores increases, the computational time taken by the parallel algorithm becomes less. © 2018, Springer Nature Singapore Pte Ltd.…”
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Optimization of Workload Allocation Problem in a Network of Heterogeneous Computer Systems by Rahela, Abdul Rahim

“…Multiple Queue Multiple Server Queueing models are used to model workload allocation problems in a network of computers. …”
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New Sequential and Parallel Division Free Methods for Determinant of Matrices by Sharmila, Karim

“…Numerical results showed that the parallel methods were able to compute determinants faster than the sequential counterparts, particularly when the tasks were equally allocated. …”
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Image reconstruction using iterative transpose algorithm for optical tomography by Md. Yunos, Yusri, Abd. Rahim, Ruzairi, Green, R. G., Fazalul Rahiman, Mohd. Hafiz

“…This paper describes a transpose algorithm for use with an optical tomography system. …”
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Improving energy consumption in cloud computing datacenters using a combination of energy-aware resource allocation and scheduling mechanism by Khalil Abd., Sura

“…Nowadays, DNA plays a vital role in many computing applications due to the massive processing parallelism. In addition, using fuzzy theory in genetic algorithm reduces the iteration of producing the population and assigning the suitable resources to the tasks-based and task length in the node capacity. …”
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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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Parallel guided image processing model for ficus deltoidea (Jack) moraceae varietal recognition by Ahmad Fakhri, Ab. Nasir, Ahmad Shahrizan, Abdul Ghani, M. Nordin, A. Rahman

“…From the results, the sequential complex image processing model and computational flow design are significantly improved when executed through parallel model under multi-cores computer system. As the number of cores increases, the computational time taken by the parallel algorithm becomes less.…”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method by Delgoshaei, Aidin

“…Then, design of experiments is used to examine the sensitivity of the parameters of each solving algorithm using Taguchi method. …”
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Continuous media (CM) data stream in flash-based solid state disk (SSD) storage server by Abdul Rahiman, Amir Rizaan, Ab. Karim, Mohd Bazli

“…Both allocations intelligently organize the CM data using the residue class algorithm and the results from the simulation experiments shown both allocations have significant outcomes in terms of the access latency and the throughput.…”
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Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids by Abduh Kaid, Monir Abdullah

“…In many data grid applications, data can be decomposed into multiple independent sub datasets and distributed for parallel execution. This property has been successfully employed using Divisible Load Theory (DLT) , which has been proven to be a powerful tool for modeling divisible load problems in large scale data grid. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod