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1
The division free parallel algorithm for finding determinant
Published 2013“…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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2
A new parallel model for starter sets generation via exchanging two elements
Published 2019“…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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3
Parallel Optical Window Algorithm Applied to Optical Multistage Interconnection Network
Published 2008“…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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4
Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network
Published 2005“…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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Thesis -
5
New Sequential and Parallel Division Free Methods for Determinant of Matrices
Published 2013“…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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6
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
7
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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8
Bitwise-based Routing Algorithms in Optical Multistage Interconnection Network
Published 2007“…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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9
Zero Algorithms for Avoiding Crosstalk in Optical Multistage Interconnection Network
Published 2005“…In Zero algorithms, there are three types of algorithms namely; The Zero X, Zero Y and zeroXY algorithms. …”
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10
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…So, the integration of Artificial Neural Network (ANN) with an Expert System for material classification was explored. The computational tool, Matlab was proposed for classification with Levenberg-Marquardt training algorithm, which provided faster rate of convergence for feed forward network. …”
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11
Greedyzero-based scheduling algorithm to route in optical low stage interconnection networks
Published 2012“…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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12
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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13
A multi-filter feature selection in detecting distributed denial-of-service attack
Published 2019“…In addition, the proposed M2FS method is developed through WEKA API with Java Programming language using the IDE of Eclipse Java. …”
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Conference or Workshop Item -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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15
Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
Published 2012“…The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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16
Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The study proposes the use of software metric thresholds in the classification process during the GA representation. …”
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17
A Simulated Annealing-Based Hyper-Heuristic For The Flexible Job Shop Scheduling Problem
Published 2023“…Flexible job shop scheduling problem (FJSP) is a common optimisation problem in the industry. The use of parallel machines allows an operation to be executed on a machine assigned from a set of alternative machines, raising a combination of machine assignment and job sequencing sub-problems. …”
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18
Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024Conference Paper -
19
Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…Machine Learning is one of the ways as a preventive method by applying the data collected from the clogging experiment in the vibration lab to build up a machine learning model for classification of flow blockage levels in the centrifugal pump. …”
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