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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
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  2. 2
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Also, the proposed models for learning in data sets generated the classification rules faster than other methods. …”
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  3. 3
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  4. 4
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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  5. 5
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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  6. 6
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
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  7. 7
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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  8. 8
    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS

    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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  9. 9
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
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    Monograph
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  10. 10
    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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  11. 11
    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules

    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

    Published 2013
    “…Benchmark data sets from various fields were used to test the proposed algorithms. …”
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  12. 12
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
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  13. 13
    A low dispersion probabilistic roadmaps (LD-PRM) algorithm for fast and efficient sampling-based motion planning

    A low dispersion probabilistic roadmaps (LD-PRM) algorithm for fast and efficient sampling-based motion planning by Khaksar W., Hong T.S., Khaksar M., Motlagh O.

    Published 2023
    “…In this paper, we propose a new learning strategy for a probabilistic roadmap (PRM) algorithm. …”
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  14. 14
    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT

    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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  15. 15
    The new efficient and accurate attribute-oriented clustering algorithms for categorical data

    The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

    Published 2012
    “…Four real-life data sets obtained from University of California Irvine (UCI) machine learning repository and ten synthetically generated data sets are used to evaluate MGR and IG-ANMI algorithms, and other four algorithms are used to compare with these two algorithms. …”
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  16. 16
    A new technique for improving the dispersion of a set of samples. Application in multi-query motion planning

    A new technique for improving the dispersion of a set of samples. Application in multi-query motion planning by Khaksar W., Hong T.S., Sahari K.S.B.M., Khaksar M.

    Published 2023
    “…For measuring the uniformity of the generated samples, a new algorithm was created to measure the dispersion of a set of samples based on any desired resolution. …”
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  17. 17
    Tap Settings Optimization in Power Systems: Economic Efficiency Enhancement Through Cuckoo Search Algorithm While Ensuring Voltage Stability

    Tap Settings Optimization in Power Systems: Economic Efficiency Enhancement Through Cuckoo Search Algorithm While Ensuring Voltage Stability by Raizal N.I., Mansor M.H., Musirin I., Shaaya S.A., Ismail S.A., Ismail N.L.

    Published 2024
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  18. 18
    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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  19. 19
    Short-Term forecasting of floating photovoltaic power generation using machine learning models

    Short-Term forecasting of floating photovoltaic power generation using machine learning models by Mohd Herwan, Sulaiman, Mohd Shawal, Jadin, Zuriani, Mustaffa, Mohd Nurulakla, Mohd Azlan, Hamdan, Daniyal

    Published 2024
    “…The dataset was divided into a training set (first five days) and a testing set (remaining two days), and five machine learning models—Neural Networks (NN), Random Forest (RF), Extreme Learning Machine (ELM), Support Vector Regression (SVR), and Long Short-Term Memory (LSTM)—were employed. …”
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  20. 20
    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots

    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

    Published 2006
    “…A simulated Khepera robot is evolved by a Pareto-frontier Differential Evolution (POE) algorithm, and learned through a 3-layer feed-forward artificial neural network, attempting to simultaneously fulfill two conflicting objectives of maximizing robot phototaxis behavior while minimizing the neural network's hidden neurons by generating a Pareto optimal set of controllers. …”
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