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  1. 1
    Exploring fruit fly evolutionary algorithm in a university examination timetabling environment

    Exploring fruit fly evolutionary algorithm in a university examination timetabling environment by Abdul Rahman, Syariza, Benjamin, Aida Mauziah, Ramli, Razamin, Ku-Mahamud, Ku Ruhana, Omar, Mohd Faizal

    Published 2019
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  2. 2
    Face recognition-based real-time system for surveillance

    Face recognition-based real-time system for surveillance by Mahdi, F.P., Habib, M.M., Ahad, M.A.R., McKeever, S., Moslehuddin, A.S.M., Vasant, P.

    Published 2017
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  3. 3
    Evolutionary Integrated Heuristic with Gudermannian Neural Networks for Second Kind of Lane–Emden Nonlinear Singular Models

    Evolutionary Integrated Heuristic with Gudermannian Neural Networks for Second Kind of Lane–Emden Nonlinear Singular Models by Kashif, Nisar, Zulqurnain, Sabir, Muhammad Asif Zahoor, Raja, Ag. Asri Ag., Ibrahim, Joel J. P. C., Rodrigues, Adnan, Shahid Khan, Manoj, Gupta, Aldawoud, Kamal, Danda B., Rawat

    Published 2021
    “…In this work, a new heuristic computing design is presented with an artificial intelligence approach to exploit the models with feed-forward (FF) Gudermannian neural networks (GNN) accomplished with global search capability of genetic algorithms (GA) combined with local convergence aptitude of active-set method (ASM), i.e., FF-GNN-GAASM to solve the second kind of Lane–Emden nonlinear singular models (LE-NSM). …”
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  4. 4
    Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models

    Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models by Kashif Nisar, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, Adnan Shahid Khan, Manoj Gupta, Aldawoud Kamal, Danda B. Rawat

    Published 2021
    “…In this work, a new heuristic computing design is presented with an artificial intelligence approach to exploit the models with feed-forward (FF) Gudermannian neural networks (GNN) accomplished with global search capability of genetic algorithms (GA) combined with local convergence aptitude of active-set method (ASM), i.e., FF-GNN-GAASM to solve the second kind of Lane–Emden nonlinear singular models (LE-NSM). …”
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  5. 5
    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line

    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

    Published 2010
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  6. 6
    Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem

    Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem by Bashar A.Aldeeb, Mohammed Azmi Al-Betar, Norita Md Norwawi, Khalid A.Alissa, Mutasem K.Alsmadi, Ayman A.Hazaymeh, Malek Alzaqebah

    Published 2024
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  7. 7
    A Comparative Study of the Application of Swarm Intelligence in Kruppa-Based Camera Auto-Calibration

    A Comparative Study of the Application of Swarm Intelligence in Kruppa-Based Camera Auto-Calibration by Jaafar, Hazriq Izzuan

    Published 2013
    “…The fitness function used in the camera calibration problem is based on the Kruppa’s equation. A case study from a dataset provided by Le2i Universite de Bourgoune is taken for benchmarking the performance of both algorithms. …”
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  8. 8
    Active intelligent control of vibration of flexible plate structures

    Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

    Published 2011
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    Thesis
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  9. 9
    Multi-target tracking algorithm in intelligent transportation based on wireless sensor network

    Multi-target tracking algorithm in intelligent transportation based on wireless sensor network by Lei, Yang, Wu, Yuan, Khan Chowdhury, Ahmed Jalal

    Published 2018
    “…A multi-target tracking algorithm using wireless sensors in an intelligent transportation system is proposed. …”
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  10. 10
    A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption

    A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

    Published 2019
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  11. 11
    Integration of dual intelligent algorithms in shunt active power filter

    Integration of dual intelligent algorithms in shunt active power filter by Abdul Rahman, Nor Farahaida, Mohd Radzi, Mohd Amran, Mariun, Norman, Che Soh, Azura, Abd Rahim, Nasrudin

    Published 2013
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  12. 12
    RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review

    RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review by YEJIAO, WANG, KAMALUDIN, HAZALILA, MOHAMMED ALDUAIS, NAYEF ABDULWAHAB, MOHD SAFAR, NOOR ZURAIDIN, ZHONGCHAO, HAO

    Published 2024
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  13. 13
    Intelligent examination timetabling system using hybrid intelligent water drops algorithm

    Intelligent examination timetabling system using hybrid intelligent water drops algorithm by AlDeeb, Bashar A., Md Norwawi, Norita, Al-Betar, Mohammed A., Jali, Mohd Z.

    Published 2015
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  14. 14
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
    “…MALESAbrain1-3 is an intelligent algorithm which originally is designed for problem-based learning (PBL) environment. …”
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  15. 15
    Healthy Lifestyle Management System

    Healthy Lifestyle Management System by Abu Bakar, Muhammad Syazwan

    Published 2011
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  16. 16
    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach

    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach by Najeeb, Mushtaq, Muhamad, Mansor, Ramdan, Razali, Hamdan, Daniyal, Ali, Mahmood

    Published 2017
    “…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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  17. 17
    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
    “…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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  18. 18
    WiFi-based human activity recognition through wall using deep learning

    WiFi-based human activity recognition through wall using deep learning by Wong, Yan Chiew, Ahmed Abuhoureyah, Fahd Saad, Mohd Isira, Ahmad Sadhiqin

    Published 2023
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  19. 19
    Decentralized Intelligent PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator with Experimental Validation

    Decentralized Intelligent PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator with Experimental Validation by Annisa, Jamali, Mat Darus, I.Z., M. H., Hassan, Tokhi, M.O.

    Published 2018
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    Proceeding
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  20. 20
    A Comparative Study of the Application of Swarm Intelligence in Kruppa-Based Camera Auto-Calibration

    A Comparative Study of the Application of Swarm Intelligence in Kruppa-Based Camera Auto-Calibration by Jaafar, Hazriq Izzuan

    Published 2013
    “…The fitness function used in the camera calibration problem is based on the Kruppa’s equation. A case study from a dataset provided by Le2i Universite de Bourgoune is taken for benchmarking the performance of both algorithms. …”
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