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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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A new parallel model for starter sets generation via exchanging two elements by Karim, Sharmila, Omar, Zurni, Ibrahim, Haslinda

“…In this study, a technique of parallelization across the method was employed to develop new parallel algorithm for finding all permutations under exchanged restrictions. …”
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Parallel Optical Window Algorithm Applied to Optical Multistage Interconnection Network by Othman, Mohamed, Abdullah, Monir, Johari, Rozita

“…In this paper, a new parallel algorithm of the window method is developed called the Balanced Parallel Window Method (BPWM) algorithm. …”
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Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network by Abduh Kaid, Monir Abdullah

“…This routing problem is an NPhard problem. Many algorithms are designed by many researchers to perform this routing such as window method, sequential algorithm, degree-descending algorithm, simulated annealing algorithm, genetic algorithm and ant colony algorithm.This thesis explores two approaches, sequential and parallel approaches. …”
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New Sequential and Parallel Division Free Methods for Determinant of Matrices by Sharmila, Karim

“…The computation times in the newly developed sequential methods were dominated by generating starter sets. Therefore, two parallel strategies were developed to parallelise this algorithm so as to reduce the computation times. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

“…These fine-tuning techniques continue to be the object of ongoing research. …”
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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

“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

Finding an effective classification technique to develop a software team composition model by Gilal, Abdul Rehman, Jaafar, Jafreezal, Capretz, Luiz Fernando, Omar, Mazni, Basri, Shuib, Abdul Aziz, Izzatdin

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Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

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Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

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Bitwise-based Routing Algorithms in Optical Multistage Interconnection Network by Abed, Farzaneh

“…Under the constraint of avoiding crosstalk, the interests of these algorithms are to find a permutation that uses a minimum number of passes and minimum execution time. …”
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Zero Algorithms for Avoiding Crosstalk in Optical Multistage Interconnection Network by Ali Al-Shabi, Mohammed Abdulhameed

“…In Zero algorithms, there are three types of algorithms namely; The Zero X, Zero Y and zeroXY algorithms. …”
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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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Analysis on target detection and classification in LTE based passive forward scattering radar by Raja Abdullah, Raja Syamsul Azmir, Abdul Aziz, Noor Hafizah, Abdul Rashid, Nur Emileen, Salah, Asem Ahmad, Hashim, Fazirulhisyam

“…By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. …”
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Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Draman @ Muda, Noor Azilah

“…Unlike a conventional PSOIACO algorithm, this hybrid algorithm shows improvement of the classification accuracy in its generated rough reducts to solve NP-Hard problem. …”
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Greedyzero-based scheduling algorithm to route in optical low stage interconnection networks by Moudi, Mehrnaz

“…Under the constraint of avoiding crosstalk, what we have been interested is how to realize a permutation that will use the minimum number of passes, the minimum execution time and the maximum bandwidth to route the input request to output without crosstalk. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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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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