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  1. 1
    Development of committee machine models for multiple response optimization problems

    Development of committee machine models for multiple response optimization problems by Golestaneh, Seyed Jafar

    Published 2014
    “…Four methodologies are to make four different CM models to solve MRO problems. The fifth methodology proposes the final algorithm which uses four CM models together to solve MRO problems. …”
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  2. 2
    The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

    The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applicatio... by Shehadeh, Hisham A., Idris, Mohd Yamani Idna, Ahmedy, Ismail, Ramli, Roziana, Noor, Noorzaily Mohamed

    Published 2018
    “…Our proposed method, named Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP), along with other three state-of-The-Art multi-objective optimization algorithms known as OMOPSO, NSGA-II and SPEA2, are utilized in this study. …”
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  3. 3
    A comparison of watermarking image quality based on dual intermediate significant bit with genetic algorithm

    A comparison of watermarking image quality based on dual intermediate significant bit with genetic algorithm by Yasin, Azman, M. Zeki, Akram, Mohammed, Ghassan N.

    Published 2013
    “…The quality of the watermarked images is considered as one of the most important requirements of any watermarking system.In most applications, the watermarking algorithm embeds the watermark without affecting the quality of the host media.In this study, a comparison of watermarking image quality was performed between two existing methods: Dual Intermediate Significant Bit (DISB) an d Genetic Algorithm (GA).The first method focuses on the high quality of the watermarked image based on DISB model and this method requires embedding two bits into every pixel of the original image, while the other six bits are modified so as to immediately assimilate the original pixel. …”
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  4. 4
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  5. 5
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  6. 6
    High image quality watermarking model by using genetic algorithm

    High image quality watermarking model by using genetic algorithm by Mohammed, Ghassan N., Yasin, Azman, Zeki, Akram M.

    Published 2012
    “…Many studies try to enhance the quality by using different techniques and methods. In this study, Genetic Algorithm (GA) method is used to embed two bits of watermarking data within every pixel of original image and to find the optimal value based on the existing Dual Intermediate Significant Bit (DISB). …”
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  7. 7
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…These steps have conducted using the MEMPHA model and ROA algorithm to optimize three metrics: execution time, total communication volume, and imbalance ratio (load balancing). …”
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  8. 8
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  9. 9
    High image quality watermarking model by using genetic algorithm

    High image quality watermarking model by using genetic algorithm by Mohammed, Ghassan N., Yasin, Azman, Zeki, Akram M.

    Published 2012
    “…Many studies try to enhance the quality by using different techniques and methods.In this study, Genetic Algorithm (GA) method is used to embed two bits of watermarking data within every pixel of original image and to find the optimal value based on the existing Dual Intermediate Significant Bit (DISB).However, if the two embedded bits is equal to the original bits then this means the watermarked image is still the same as the original one without any changing, while in the other case GA is used getting the minimum fitness value in which the fitness is the absolute value between the pixel and chromosome and the value of chromosome between 0-255.The results show that the new method improves the image quality and get the optimal value for the two embedded bits.…”
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  10. 10
    An inclusive multiple model for predicting total sediment transport rate in the presence of coastal vegetation cover based on optimized kernel extreme learning models

    An inclusive multiple model for predicting total sediment transport rate in the presence of coastal vegetation cover based on optimized kernel extreme learning models by Jalil-Masir H., Fattahi R., Ghanbari-Adivi E., Asadi Aghbolaghi M., Ehteram M., Ahmed A.N., El-Shafie A.

    Published 2023
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  11. 11
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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  12. 12
    Enhancement of Single and Composite Images Based on Contourlet Transform Approach

    Enhancement of Single and Composite Images Based on Contourlet Transform Approach by Melkamu, Hunegnaw Asmare

    Published 2009
    “…The objective evaluation steps show that the new method of enhancement not only superior to the commonly used transformation method (e.g. wavelet transform) but also to various spatial models (e.g. …”
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  13. 13
    Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure

    Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure by Md Fahmi, Abd Samad

    Published 2016
    “…Two methods of model structure selection are closely looked into and these are deterministic mutation algorithm (DMA) and forward selection procedure (FSP). …”
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  14. 14
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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  15. 15
    A Harris hawks optimization based single- and multi objective optimal power flow considering environmental emission

    A Harris hawks optimization based single- and multi objective optimal power flow considering environmental emission by Islam, Mohammad Zohrul, Abdul Wahab, Noor Izzri, Veerasamy, Veerapandiyan, Hizam, Hashim, Mailah, Nashiren Farzilah, Guerrero, Josep M., Mohd Nasir, Mohamad Nasrun

    Published 2020
    “…The obtained results are compared with the other Artificial Intelligence (AI) techniques such as the Whale Optimization Algorithm (WOA), the Salp Swarm Algorithm (SSA), Moth Flame (MF) and Glow Warm Optimization (GWO). …”
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  16. 16
    Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin

    Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

    Published 2011
    “…A Lipschitz method and Leven berg Marquardt algorithm is used to determine the model order number and train the network respectively. …”
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  17. 17
    Color image enhancement of acute leukemia cells in blood microscopic image for leukemia detection sample

    Color image enhancement of acute leukemia cells in blood microscopic image for leukemia detection sample by Harun, Nor Hazlyna, Abu Bakar, Juhaida, Abd Wahab, Zulkifli, Osman, Muhammad Khusairi, Harun, Hazaruddin

    Published 2020
    “…The segmentation algorithm uses saturation S-component based on Hue, Saturation, Intensity (HSI) color model. …”
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  18. 18
    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…To classify image noise type, the CNN trained with Backpropagation (BP) algorithm and Stochastic Gradient Descent (SGD) optimization technique are implemented. …”
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  19. 19
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  20. 20
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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