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  1. 1
    Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis

    Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis by Ashraf Osman, Ibrahim, Siti Mariyam, Shamsuddin, Abdulrazak, Yahya Saleh, Ahmed, Ali, Mohd Arfian, Ismail, Shahreen, Kasim

    Published 2019
    “…However, the performance of such methods is based on the algorithms or technique. In this paper, we develop an intelligent technique using multiobjective evolutionary method hybrid with a local search approach to enhance the backpropagation neural network. …”
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  2. 2
    Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee

    Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

    Published 2023
    “…RBFN-DDA performs incremental learning wherein its structure expands by adding new hidden units to include new information. As such, its training can reach stability in a shorter time compared to the gradient-descent based methods. …”
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  3. 3
    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems

    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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  4. 4
    Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems

    Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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  5. 5
    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
    “…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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  6. 6
    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification

    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

    Published 2017
    “…For example, Binary Particle Search Optimization Common Spatial Pattern (BPSO-CSP) was proposed to choose multiple possible best bands to be used in processing the data. …”
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  7. 7
    Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification

    Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification by Ahmad, Fadzil

    Published 2017
    “…The proposed technique avoids the destruction of nearly optimal information contained in the gene segment and allows offspring to inherit highly important information among multiple parents. …”
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  8. 8
    Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach

    Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach by Nur'atiah Zaini

    Published 2025
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  9. 9
    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. …”
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  10. 10
    Efficient Entropy-Based Decoding Algorithms For Higher-Order Hidden Markov Model

    Efficient Entropy-Based Decoding Algorithms For Higher-Order Hidden Markov Model by Chan, Chin Tiong

    Published 2019
    “…The extended entropy-based Viterbi algorithm is proposed for decoding HHMM. …”
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  11. 11
    Vehicular traffic noise prediction and propagation modelling using artificial neural network

    Vehicular traffic noise prediction and propagation modelling using artificial neural network by Ahmed, Ahmed Abdulkareem

    Published 2018
    “…The neural network and its hyperparameters were optimized through a systematic optimization procedure based on a grid search approach. …”
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  12. 12
    A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming

    A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming by Darzi S., Sieh Kiong T., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

    Published 2023
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  13. 13
    A Multi-State Gravitational Search Algorithm for Combinatorial Optimization Problems

    A Multi-State Gravitational Search Algorithm for Combinatorial Optimization Problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2015
    “…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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  14. 14
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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  15. 15
    An experimental study of modified black hole algorithms

    An experimental study of modified black hole algorithms by Mohammed, Suad Khairi

    Published 2018
    “…Those algorithms are Black Hole White Hole Algorithm, Gravitational Black Hole Algorithm, Gravitational Black Hole White Hole Algorithm, Black Hole Local Search Algorithm, Black Hole White Hole Local Search Algorithm, Gravitational Black Hole Local Search Algorithm, and Gravitational Black Hole White Hole Local Search Algorithm. …”
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  16. 16
    Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system

    Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system by Nasir, Ahmad Nor Kasruddin, Abdul Razak, Ahmad Azwan

    Published 2022
    “…Spiral Dynamic Algorithm (SDA) is a group-based optimization algorithm formulated based on the concept of a natural spiral phenomenon on earth. …”
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  17. 17
    An improved method using fuzzy system based on hybrid boahs for phishing attack detection

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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  18. 18
    Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization

    Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization by Zuwairie, Ibrahim, Mohamad Nizam, Aliman, Fardila, Naim, Sophan Wahyudi, Nawawi, Shahdan, Sudin

    Published 2015
    “…Particle Swarm Optimization (PSO) and Gravitational Search Algorithm are a well known population-based heuristic optimization techniques. …”
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  19. 19
    A novel multi-state gravitational search algorithm for discrete optimization problems

    A novel multi-state gravitational search algorithm for discrete optimization problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2015
    “…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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  20. 20
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and finds the best sub-search space, and then the CS selects the best nest by traversing the sub-search space. …”
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