Search Results - (( intelligence based can algorithm ) OR ( intelligence based ((_ algorithm) OR (bee algorithm)) ))

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  1. 1
    Local search manoeuvres recruitment in the bees algorithm

    Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

    Published 2011
    “…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. …”
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  2. 2
    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots

    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

    Published 2019
    “…According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
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    Monograph
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  3. 3
    HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION

    HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION by Kappagantula, S., Vojjala, S., Iyer, A.A., Velidi, G., Emani, S., Vandrangi, S.K.

    Published 2023
    “…The Bat Algorithm is a population-based meta-heuristic algorithm for solving continuous optimization problems. …”
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  4. 4
    Artificial bee colony for inventory routing problem with backordering

    Artificial bee colony for inventory routing problem with backordering by Moin, N.H., Halim, H.Z.A.

    Published 2014
    “…We propose a metaheuristic method, Artificial Bee Colony (ABC) to solve the IRPB.The ABCalgorithm is a swarm based heuristics which simulates the intelligent foraging behaviour of a honey bee swarm and sharing that information of the food sources with the bees in the nest. …”
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  5. 5
    A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali

    A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali by Mohamed Kamali, Mohd Zahurin

    Published 2015
    “…In- stead of a sophisticated controller that governs the global behavior of the system, the swarm intelligence principle is based on many unsophisticated entities (for example such as ants, termites, bees etc.) that cooperate and interact in order to exhibit a desired behav- ior. …”
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  6. 6
    A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting

    A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting by Ibrahim K.S.M.H., Huang Y.F., Ahmed A.N., Koo C.H., El-Shafie A.

    Published 2023
    Review
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  7. 7
    Methane plume localization with enhanced self-best reduction and Gaussian improved particle swarm optimization (GiPSO)

    Methane plume localization with enhanced self-best reduction and Gaussian improved particle swarm optimization (GiPSO) by Liew, Jia Hun

    Published 2024
    “…Secondly, our research questions how the Gaussian gas plume model can address the adaptation of swarm intelligence in drone-based gas leakage detection. …”
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  8. 8
    Artificial neural networks based optimization techniques: A review

    Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

    Published 2023
    “…In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”
    Review
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  9. 9
    Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System

    Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

    Published 2013
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  10. 10
    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
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  11. 11
    Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed

    Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed by Mudasir , Ahmed

    Published 2019
    “…The preliminary review of existing control techniques revealed that the Bio-inspired intelligent algorithms (BIAs) based selective harmonic elimination pulse width modulation (SHEPWM) are more proficient to eliminate the loworder harmonics. …”
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  12. 12
    An efficient multi join query optimization for relational database management system using swarm intelligence approaches

    An efficient multi join query optimization for relational database management system using swarm intelligence approaches by Alsaedi, Ahmed Khalaf Zager

    Published 2016
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  13. 13
    An efficient multi join query optimization for relational database management system using swarm intelligence approaches

    An efficient multi join query optimization for relational database management system using swarm intelligence approaches by Alsaedi, Ahmed Khalaf Zager

    Published 2016
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  14. 14
    An Intelligent Modeling of Oil Consumption

    An Intelligent Modeling of Oil Consumption by Chiroma, Haruna, Abdulkareem, Sameem, Muaz, Sanah Abdullahi, Abubakar, Adamu I., Sutoyo, Edi, Mungad , Mungad, Saadi, Younes, Sari, Eka Novita, Tutut, Herawan

    Published 2015
    “…In this study, we select Middle East countries involving Jordan, Lebanon, Oman, and Saudi Arabia for modeling oil consumption based on computational intelligence methods. The limitations associated with Levenberg-Marquardt (LM) Neural Network (NN) motivated this research to optimize the parameters of NN through Artificial Bee Colony Algorithm (ABC-LM) to build a model for the prediction of oil consumption. …”
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    Book Chapter
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  15. 15
    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm

    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

    Published 2024
    “…The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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  16. 16
    Optimal placement of actuator for vibration suppression based on intelligent PID controller

    Optimal placement of actuator for vibration suppression based on intelligent PID controller by Muhamad Sukri, Hadi, Nadzirah, Mohd Mokhtar, Intan Zaurah, Mat Darus

    Published 2020
    “…The PID controller tuned by artificial bee colony (ABC) algorithm was used to control the undesired vibration on the structure. …”
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  17. 17
    Intelligent Examination Timetabling System Using Hybrid Intelligent Water Drops Algorithm

    Intelligent Examination Timetabling System Using Hybrid Intelligent Water Drops Algorithm by AlDeeb, BA, Norwawi, NM, Al-Betar, MA, Jali, MZ

    Published 2024
    “…Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops. …”
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  18. 18
    Active intelligent control of vibration of flexible plate structures

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

    Published 2011
    “…It is shown that higher levels of vibration can be achieved with model-based SIMO-AVC algorithms as compared to those model- based SISO-AVC algorithms. …”
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  19. 19
    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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  20. 20
    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
    “…This paper proposes Hybrid Intelligent Water Drops (HIWD) algorithm to solve Tamhidi programs uncapacitated examination timetabling problem in Universiti Sains Islamic Malaysia (USIM).Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops.The results of this study prove that the proposed algorithm can produce a high quality examination timetable in shorter time in comparison with the manual timetable.…”
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