Search Results - (( evolution classification learning algorithm ) OR ( parallel visualization system algorithm ))

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  1. 1
    High performance visualization of human tumor growth software

    High performance visualization of human tumor growth software by Alias, Norma, Mohd. Said, Norfarizan, Khalid, Siti Nur Hidayah, Sin, Dolly Tien Ching, Phang, Tau Ing

    Published 2008
    “…The implementation of parallel algorithm based on parallel computing system is used to visualize the growth of human tumour. …”
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  2. 2
    The visualization of three dimensional brain tumors' growth on distributed parallel computer systems

    The visualization of three dimensional brain tumors' growth on distributed parallel computer systems by Alias, Norma, Masseri, Mohd. Ikhwan Safa, Islam, Md. Rajibul, Khalid, Siti Nurhidayah

    Published 2009
    “…The main objective of this study is to visualize the brain tumors’ growth in three-dimensional and implement the algorithm on distributed parallel computer systems. …”
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  3. 3
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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  4. 4
    Discretization of crack propagation on parallel computing : complexity and parallel algorithms with source code

    Discretization of crack propagation on parallel computing : complexity and parallel algorithms with source code by Alias, Norma, Islam, Md. Rajibul

    Published 2010
    “…Parallel algorithm is used by Parallel Virtual Machine (PVM) software tool to capture the visualization of the overall extension and the stress distribution in a linearly tapered bar of circular section with an end load. …”
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  5. 5
    Discretization of crack propagation on parallel computing: complexity and parallel algorithms with source code

    Discretization of crack propagation on parallel computing: complexity and parallel algorithms with source code by Alias, Norma, Islam, Md. Rajibul

    Published 2010
    “…Parallel algorithm is used by Parallel Virtual Machine (PVM) software tool to capture the visualization of the overall extension and the stress distribution in a linearly tapered bar of circular section with an end load. …”
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  6. 6
    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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  7. 7
    Email spam classification based on deep learning methods: A review

    Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

    Published 2025
    “…Email spam is a significant issue confronting both email consumers and providers. The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. …”
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  8. 8
    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…Individual emotional states are highly variable and are subject to evolution from personal experiences. For this reason, the above system is designed to be able to perform learning and classification in real-time to account for inter-individual and intra-individual emotional drift over time. …”
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  9. 9
    Artificial fish swarm optimization for multilayer network learning in classification problems

    Artificial fish swarm optimization for multilayer network learning in classification problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam

    Published 2012
    “…Nature-Inspired Computing (NIC) has always been a promising tool to enhance neural network learning. Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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  10. 10
    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems

    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2012
    “…In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems. …”
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  11. 11
    Parallel system for abnormal cell growth prediction based on fast numerical simulation

    Parallel system for abnormal cell growth prediction based on fast numerical simulation by Alias, Norma, Islam, Md. Rajibul, Shahir, Rosdiana, Hamzah, Norhafizah, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Ludin, Eliana, Azami, Masrin

    Published 2010
    “…The development of the prediction system is the combinations of the parallel algorithms, open source software on Linux environment and distributed multiprocessor system. …”
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  12. 12
    Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE)

    Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE) by Alias, Norma, Islam, Md. Rajibul

    Published 2010
    “…This study focuses on the implementation of parallel algorithm for the simulation of tumor growth using two dimensional Helmholtz’s wave equation on a distributed parallel computing system. …”
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  13. 13
    Image based autonomous indoor parallel parking assist on omni-directional vehicle (ODV)

    Image based autonomous indoor parallel parking assist on omni-directional vehicle (ODV) by Edwind, Liaw Yee Kang

    Published 2016
    “…In this research, the implementation of image processing techniques on vehicle’s control has been proposed to develop autonomous indoor parallel parking assist on ODV. The image processing algorithm is first developed using Visual Studio C++ and OpenCV. …”
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  14. 14
    Parallel visualization approach of a 3D heart model

    Parallel visualization approach of a 3D heart model by Malekpour, A., Ling, T.C., Lim, W.C.

    Published 2008
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  15. 15
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…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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  16. 16
    A New Quadratic Binary Harris Hawk Optimization For Feature Selection

    A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

    Published 2019
    “…A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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  17. 17
    Grid portal technology for web based education of parallel computing courses, applications and researches

    Grid portal technology for web based education of parallel computing courses, applications and researches by Alias, Norma, Islam, Md. Rajibul, Mydin, Suhaimi, Hamzah, Norhafiza, Safiza Abd. Ghaffar, Zarith, Satam, Noriza, Darwis, Roziha

    Published 2009
    “…These courses will actively engage the students in exploring the concepts of the development the parallel algorithm in visualizing the grand challenge applications of mathematical problems. …”
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  18. 18
    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution

    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

    Published 2017
    “…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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  19. 19
    The feature parallelism model of visual recognition

    The feature parallelism model of visual recognition by Hassan, Marwa Yousif, Shuriye, Abdi Omar, Hassan Abdalla Hashim, Aisha, Salami, Momoh Jimoh Eyiomika, Khalifa, Othman Omran

    Published 2017
    “…In this work, the Feature Parallelism Model of visual recognition, which addresses the parallel nature of the human brain compared to the hierarchal (serial) brain model, was studied. …”
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  20. 20
    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis

    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

    Published 2019
    “…To verify our proposed approach, four Arabic benchmark datasets for sentiment analysis are used since there are only a few studies in sentiment analysis conducted for Arabic language as compared to English. The proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. …”
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