Search Results - (( intelligence based bees algorithm ) OR ( intelligence system way algorithm ))

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    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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    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
    “…Hence, this research presents the optimal placement of actuator and sensor on the experimental rig for vibration cancelation of the flexible plate structure based on intelligent PID controller. The PID controller tuned by artificial bee colony (ABC) algorithm was used to control the undesired vibration on the structure. …”
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    Conference or Workshop Item
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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
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    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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    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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    Conference or Workshop Item
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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
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    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
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    A quick gbest guided artificial bee colony algorithm for stock market prices prediction by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…In this respect, in the present manuscript, we propose an algorithm based on ABC to minimize the error in the trend and actual values by using the hybrid technique based on neural network and artificial intelligence. …”
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    Article
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    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

    Published 2017
    “…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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    Article
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    Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

    Published 2021
    “…The MOSI algorithms are based on the integration of single objective algorithms and multi-objective optimization (MOO) approach. …”
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    Article
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    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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    Thesis
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    Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

    Published 2020
    “…A total of 6 datasets were deployed to evaluate the effectiveness of the proposed algorithm. Results showed that EACS(TS) outperformed in terms of success rate, packet loss, latency, and energy efficiency when compared with single swarm intelligence routing algorithms which are Energy-Efficient Ant-Based Routing (EEABR), BeeSensor and Termite-hill. …”
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    Thesis
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