Search Results - (( code classification mining algorithm ) OR ( parallel optimization means algorithm ))
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1
Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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2
Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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3
Comparative analysis for topic classification in juz Al-Baqarah
Published 2018“…The SVM performance is then compared against other classification algorithms such as Naive Bayes, J48 Decision Tree and K-Nearest Neighbours. …”
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4
Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.…”
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5
Classification of metamorphic virus using n-grams signatures
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…No EEG studies in Malaysia has been done on school children to study their emotional behaviour while learning. Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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7
Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization
Published 2022“…Based on the optimization results, the MFO outperformed other comparison algorithms for the mean fitness and also the best fitness. …”
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8
An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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9
Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.
Published 2022“…Best Hammerstein parallel NN polynomial based model and series-parallel NN polynomial model are 88.75% and 93.9% respectively, for best Hammerstein parallel NN sigmoid based model and series-parallel NN sigmoid based model 78.26% and 95.95% respectively, and for best Hammerstein parallel NN hyperbolic tangent based model and series-parallel NN hyperbolic tangent based model 70.7% and 96.4% respectively. …”
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10
Dengue outbreak prediction: hybrid meta-heuristic model
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11
Optimization of Workload Allocation Problem in a Network of Heterogeneous Computer Systems
Published 2005“…Other service distributional models such as exponential, Erlang-k and Gamma have also been used to expand the work applicability. A new algorithm of workload allocation scheme using First Come First Serve discipline in conjunction with optimization of GE queueing systems is proposed for minimizing mean queue length and mean response time in a network of computer systems. …”
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Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living
Published 2024“…In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. …”
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Investigation of QAM based on mean square error (MSE) channel estimation (CE) for MIMO-OFDM pilot based system / Mohd Ariff Ibrahim
Published 2013“…Fast Fourier Transform (FFT) and Inverse Fast Fourier Transform (IFFT) are the main optimizer as it convert input signal or output signal from frequency domain to time domain or vice versa either on serial or parallel block. …”
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15
Communication and computation rate-cheating problems in divisible load scheduling: revisited
Published 2015“…In the real applications, the processors may cheat the algorithm which means that the processors might not report their true computation or communication rates. …”
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16
Mitigation of atmospheric turbulences using mode division multiplexing based on decision feedback equalizer for free space optics
Published 2017“…This paper investigates the mitigation of atmospheric turbulences of FSO using MDM and decision feedback equalizer (DFE) with minimum mean square error (MMSE) algorithm. The implementation of the MMSE algorithm is used to optimize both the feedforward and the feedback filter coefficients of DFE. …”
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An enhanced android botnet detection approach using feature refinement
Published 2019“…The experimental and statistical tests show that 97.28% accuracy achieved by Random Forest machine classifier, it performs well as compared to other classification algorithms. Based on the test results, various open research issues which need to be addressed in future studies are highlighted.…”
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18
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Therefore, the core classifier in the hyper-heuristic approach of Intrusion Detection System (IDS) is developed to the parallel structure NN. This enables more controllability of reaching optimal learning without falling into sub-optimality because of over-fitting or under-fitting. …”
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19
System Identification And Control Of Automatic Car Pedal Pressing System For Low-Speed Driving In A Road Traffic Delay
Published 2022“…The controller gains were tuned using metaheuristic algorithm which is Particle Swarm Algorithm (PSO) for optimal values of fuzzy controller parameters. …”
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Undergraduates Project Papers -
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Multi-criteria divisible load scheduling in binary tree network
Published 2016“…The traditional divisible load scheduling assumes that the processors report their true computation and communication rates, i.e., they do not cheat the algorithm. In the real applications, the processors may cheat the algorithm, which means, the processors might not report their true computation or communication rates. …”
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