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  1. 1
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  2. 2
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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    Final Year Project
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  3. 3
    Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall

    Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall by Mustafa, M.R., Rezaur, R.B., Saiedi, Saied, Rahardjo, H., Isa, M.H.

    Published 2013
    “…The performance of four artificial neural network (ANN) training algorithms was evaluated to identify the training algorithm appropriate for modeling the dynamics of soil pore-water pressure responses to rainfall patterns using multilayer perceptron (MLP) ANN. …”
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    Citation Index Journal
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  4. 4
    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application

    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

    Published 2020
    “…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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  5. 5
    Prime-based method for interactive mining of frequent patterns

    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Since rerunning the mining algorithms from scratch can be very time consuming, researchers have introduced interactive mining to find proper patterns by using the current mining model with various minsup. …”
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  6. 6
    Formulating new enhanced pattern classification algorithms based on ACO-SVM

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  7. 7
    Hand blood vessels pattern recognition

    Hand blood vessels pattern recognition by Tan, Xuan Qing

    Published 2023
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    Final Year Project / Dissertation / Thesis
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  8. 8
    Java based expert system for selection of natural fibre composite materials

    Java based expert system for selection of natural fibre composite materials by Ahmed Ali, Basheer A., Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed

    Published 2013
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  9. 9
    Implementation of (AES) Advanced Encryption Standard algorithm in communication application

    Implementation of (AES) Advanced Encryption Standard algorithm in communication application by Moh, Heng Huong

    Published 2014
    “…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
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    Undergraduates Project Papers
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  10. 10
    Artificial neural network-salp-swarm algorithm for stock price prediction

    Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

    Published 2024
    “…The effectiveness of the SSA-ANN model is evaluated using the Yahoo stock price dataset. …”
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  11. 11
    Machine learning predictions of stock market pattern using Econophysics approach

    Machine learning predictions of stock market pattern using Econophysics approach by Roslan, Nur Nadia Hani, Abdullah, Shahino Mah

    Published 2025
    “…This research outlines the study of stock market patterns using the Econophysics approach. There are various techniques for identifying and observing the stock market patterns, one of the techniques is to use Python programming to evaluate and possibly forecast stock market behaviour through predictive modelling, combining both machine learning and Econophysics insights. …”
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    Book Section
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  12. 12
    Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari

    Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

    Published 2017
    “…To evaluate the hybrid algorithm, optimization of hydro-power energy of Karun dams were considered. …”
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  13. 13
    Classification System for Heart Disease Using Bayesian Classifier

    Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

    Published 2007
    “…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
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  14. 14
    Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite

    Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite by Suali, Anjila J., Nuraminah Ramli, Rozmie Razif Othman, Hasneeza Liza Zakaria, Iszaidy Ismail, Nor Shahida Mohd Jamail, Rimuljo Hendradi, Nurol Husna Che Rose

    Published 2025
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  15. 15
    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification

    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

    Published 2009
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    Monograph
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  16. 16
    A Model for Evaluation of Cryptography Algorithm on UUM Portal

    A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

    Published 2004
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  17. 17
    Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search

    Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search by Wahab, Musa

    Published 2014
    “…The actual electricity demand data of Turkey and Indonesia were used in the experiments to evaluate the performance of the proposed model. Results of the proposed model were compared to the hybrid GA and Nelder-Mead local search, Real Code Genetic Algorithm and Particle Swarm Optimisation. …”
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  18. 18
    Modeling of vehicle trajectory using K-means and fuzzy C-means clustering

    Modeling of vehicle trajectory using K-means and fuzzy C-means clustering by Choong, Mei Yeen, Lorita Angeline, Chin, Renee Ka Yin, Yeo, Kiam Beng, Teo, Kenneth Tze Kin

    Published 2019
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    Proceedings
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  19. 19
    Modern fuzzy min max neural networks for pattern classification

    Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

    Published 2019
    “…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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  20. 20
    Hybrid optimization approach to estimate random demand

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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