Search Results - (( using selection method algorithm ) OR ( basic optimization ((bat algorithm) OR (_ algorithm)) ))

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  1. 1
    A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem

    A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem by Mohd Said, Rahaini, A Aziz, Khairul Azha, Zainal Abidin, Amar Faiz, Mat Jizat, Jessnor Arif, Mohd Khairuddin, Ismail, Widiyanto, Sigit, Abdul Waduth, Mohamed Faisal

    Published 2022
    “…Each bat in the Bat Algorithm represents a potential solution to the issue, and each dimension in the Bat Algorithm's search space represents one of the basic parameters: skew, focal length, and magnification factor. …”
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  2. 2
    A hybrid particle swarm optimization approach and its application to solving portfolio selection problems

    A hybrid particle swarm optimization approach and its application to solving portfolio selection problems by Shamshul Bahar, Yaakob, Prof. Madya, Watada, Junzo

    Published 2011
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  3. 3
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…In future, this work could be enhanced for better performances in both aspects using another variant of the PSO or other potential metaheuristic searching techniques such as Firefly Optimization, Bat Algorithm and etc.…”
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  4. 4
    System identification using Extended Kalman Filter

    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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  5. 5
    Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization

    Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization by Salih, Sinan Q., Alsewari, Abdulrahman A., Al-Khateeb, Bellal, Mohamad Fadli, Zolkipli

    Published 2019
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  6. 6
    An ensemble feature selection method to detect web spam

    An ensemble feature selection method to detect web spam by Oskouei, Mahdieh Danandeh, Razavi, Seyed Naser

    Published 2018
    “…Web spam is an illegal method to increase mendacious rank of internet pages by deceiving the algorithms of search engines, so it is essential to use an efficient method. …”
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  7. 7
    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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  8. 8
    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction

    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

    Published 2023
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  9. 9
    Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad

    Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad by Mostafa, Modiri Delshad

    Published 2016
    “…Backtracking search algorithm (BSA) as the new evolutionary technique of optimization is used for solving the problems. …”
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  10. 10
    Development of cell formation algorithm and model for cellular manufacturing system

    Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

    Published 2011
    “…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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  11. 11
    Power line faults classification by neural network train by Ant Colony Optimization

    Power line faults classification by neural network train by Ant Colony Optimization by Nasirudin, Mohd Syafiq

    Published 2017
    “…The characteristic of ACO algorithms is their explicit use of elements of previous solutions. …”
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  12. 12
    Nomadic people optimizer (NPO) for large-scale optimization problems

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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  13. 13
    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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  14. 14
    Robust correlation feature selection based support vector machine approach for high dimensional datasets

    Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

    Published 2025
    “…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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  15. 15
    A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems

    A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems by Lutfy, Omar Farouq, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Abbas, Kassim A.

    Published 2010
    “…Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. …”
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  16. 16
    Improving neural networks training using experiment design approach

    Improving neural networks training using experiment design approach by Chong, Wei Kean

    Published 2005
    “…Randomly select the m data set for conventional training algorithm. …”
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  17. 17
    A fuzzy case-based reasoning model for software requirements specifications quality assessment

    A fuzzy case-based reasoning model for software requirements specifications quality assessment by Mostafa S.A., Gunasekaran S.S., Khaleefah S.H., Mustapha A., Jubair M.A., Hassan M.H.

    Published 2023
    “…Additionally, for efficient cases retrieval in the CBR, relevant cases selection and nearest cases selection heuristic search algorithms are used in the system. …”
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  18. 18
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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  19. 19
    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization

    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization by Ee, L.K., Aziz, I.A.

    Published 2018
    “…This project aims to develop a hybrid prediction Model which can target specific corrosion damage mechanisms. The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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  20. 20
    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization

    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization by Ee, L.K., Aziz, I.A.

    Published 2018
    “…This project aims to develop a hybrid prediction Model which can target specific corrosion damage mechanisms. The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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