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  1. 1
    Series division method based on PSO and FA to optimize Long-Term Hydro Generation Scheduling

    Series division method based on PSO and FA to optimize Long-Term Hydro Generation Scheduling by Hammid, Ali Thaeer, M. H., Sulaiman

    Published 2018
    “…To deal with this complicated problem, Series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed in this paper. …”
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  2. 2
    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement

    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement by Karami, Mahdi

    Published 2011
    “…This thesis present a genetic algorithm based method for placement of FACTS devices for voltage profile improvement. …”
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  3. 3
    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction

    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction by Tan, James Yiaw Beng

    Published 2012
    “…(Research into the field of artificial neural networks (ANN) is fast gaining interest in recent years, due to the fact that it is fast becoming a popular tool of choice in prediction of time series trends. This recent surge in its popularity can be attributed to the fact that ANN, especially a multilayer perceptron with backpropagation (BP) network that has the optimal number of neurons in its hidden layer would be able to predict with better accuracy unknown values of a time series that it is trained with, compared to other methods implemented to predict the same time series The drawback of using BP networks in time series prediction is that it is difficult and time-consuming to find the optimal number of neurons in its hidden layer to minimize the prediction error. …”
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  4. 4
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
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  5. 5
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  6. 6
    Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting

    Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting by Wei Y., Hashim H., Chong K.L., Huang Y.F., Ahmed A.N., El-Shafie A.

    Published 2024
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  7. 7
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
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    Monograph
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  8. 8
    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail

    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…In last decade, there has been increasing interest in simulating the natural evolutionary process in solving hard optimization problems. Genetic Algorithm (GA) is numerical optimization algorithm inspired by both natural selection and natural genetics. …”
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    Research Reports
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  9. 9
    Modified Harmony Search

    Modified Harmony Search by Najihah, Mohamed, Ahmad Lutfi, Amri Ramli, Ahmad, Abd Majid, Abd Rahni, Mt Piah

    Published 2017
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    Conference or Workshop Item
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  10. 10
    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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  11. 11
    New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks

    New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks by Marzia, Ahmed

    Published 2024
    “…The study demonstrates GBO's superiority over previous algorithms, including BMO and its variants, and other established methods. …”
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  12. 12
    A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega)

    A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega) by Tan, Tun Tai

    Published 2009
    “…However, it is impractical to solve MOOP by using classical methods due to its complexity. Genetic Algorithms (GAs) are a powerful stochastic search in solving optimization problems. …”
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    Final Year Project Report / IMRAD
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  13. 13
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
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  14. 14
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
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  15. 15
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
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  16. 16
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
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  17. 17
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
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  18. 18
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
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  19. 19
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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  20. 20
    Performance of Levenberg-Marquardt neural network algorithm in air quality forecasting

    Performance of Levenberg-Marquardt neural network algorithm in air quality forecasting by Cho, Kar Mun, Nur Haizum Abd Rahman, Iszuanie Syafidza Che Ilias

    Published 2022
    “…However, both algorithms have mixed conclusions in optimizing MLP in time series forecasting. …”
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