Search Results - (( intelligence based bee algorithm ) OR ( intelligence based ((e algorithm) OR (new algorithm)) ))

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  1. 1

    Application of Bee Colony Optimization (BCO) in NP-Hard Problems by Kamarudin, Muhammad Sariy Syazwan

    Published 2011
    “…Bee-Inspired algorithms were presumed to bring the new direction in the field of Swann Intelligence. …”
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    Final Year Project
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    Optimal design of step – cone pulley problem using the bees algorithm by Yusof, Noor Jazilah, Kamaruddin, Shafie

    Published 2021
    “…Most of these algorithms were developed based on the collective behavior of social swarms of ants, bees, a flock of birds, and schools of fish. …”
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    Book Chapter
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    Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

    Published 2013
    “…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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    Thesis
  6. 6

    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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    Conference or Workshop Item
  7. 7

    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

    Published 2021
    “…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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    Article
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    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
  10. 10

    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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    Thesis
  11. 11

    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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    Thesis
  12. 12

    Time series forecasting of energy commodity using grey wolf optimizer by Yusof, Yuhanis, Mustaffa, Zuriani

    Published 2015
    “…The ability to model and perform decision making is an essential feature of many real-world applications including the forecasting of commodity prices.In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting.The model is built upon data obtained from the West Texas Intermediate (WTI) crude oil and gasoline price.Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE).Results showed that the GWO model outperformed DE in both crude oil and gasoline price forecasting. …”
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    Conference or Workshop Item
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    Machine Learning and Dyslexia-Diagnostic and Classification System (DCS) for Kids with Learning Disabilities by Rehman Ullah, Khan, Julia Ai Cheng, Lee, Oon, Yin Bee

    Published 2018
    “…Most experts are using manual techniques to diagnose dyslexia. Machine learning algorithms are capable enough to learn the knowledge of experts and intelligently diagnose and classify dyslexics. …”
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    Article
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    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2015
    “…This paper proposes a new meta-heuristic approach to solving numerical and graph-based problems. …”
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    Article
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    Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

    Published 2023
    “…A new case is retained in the case base for future retrievals. …”
    Conference paper
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    Time Series Forecasting of Energy Commodity using Grey Wolf Optimizer by Zuriani, Mustaffa, Yuhanis, Yusof

    Published 2015
    “…In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting. …”
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    Conference or Workshop Item
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    Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach by Quadros, Jaimon Dennis, Khan, Sher Afghan, T., Prashanth

    Published 2021
    “…In this paper, we report an intelligent model based on ANN to optimize the performance of an internally cooled membrane-based liquid desiccant dehumidifier (IMLDD). …”
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    Article
  20. 20

    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm by Mohammed, Zahraa Abdulkareem

    Published 2017
    “…These two algorithms are compared to their original artificial intelligence algorithms, i.e. particle swarm optimization algorithm and genetic algorithm. …”
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    Thesis