Search Results - (( intelligence based real algorithm ) OR ( intelligence based search algorithm ))

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  1. 1

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. …”
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  2. 2

    Comparison of swarm intelligence algorithms for high dimensional optimization problems by Bashath, Samar, Ismail, Amelia Ritahani

    Published 2018
    “…This paper presents a comprehensive study of two swarm intelligence based algorithms: 1- particle swarm optimization (PSO), 2-cuckoo search (CS).The two algorithms are analyzed and compared for problems consisting of high dimensions in respect of solution accuracy, and runtime performance by various classes of benchmark functions.…”
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    Article
  3. 3

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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  4. 4

    Swarm intelligence algorithms’ solutions to the travelling salesman’s problem by Odili, Julius Beneoluchi, Noraziah, Ahmad, Roslina, Mohd Sidek

    Published 2020
    “…After a number of experimental procedures, the study concludes that all the comparative algorithms are very efficient in providing solutions to the benchmark travelling salesman’s problems considered, though the Discrete Cuckoo Search and the African Buffalo Optimization have a slight edge in performance over the other comparative algorithms. …”
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    Conference or Workshop Item
  5. 5

    Nature-Inspired Heuristic Frameworks Trends in Solving Multi-objective Engineering Optimization Problems by Chang C.C.W., Ding T.J., Ee C.C.W., Han W., Paw J.K.S., Salam I., Bhuiyan M.A.S., Kuan G.S.

    Published 2025
    “…These algorithms are inspired and modelled based on the searching behaviour of animals in real life. …”
    Review
  6. 6

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…Swarm intelligence algorithms are metaheuristic algorithms inspired by the simple interactions of biological organisms in a population. …”
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    Swarm intelligence algorithms' solutions to the travelling salesman's problem by Odili, Julius Beneoluchi, Noraziah, Ahmad, Roslina, Mohd Sidek

    Published 2020
    “…After a number of experimental procedures, the study concludes that all the comparative algorithms are very efficient in providing solutions to the benchmark travelling salesman's problems considered, though the Discrete Cuckoo Search and the African Buffalo Optimization have a slight edge in performance over the other comparative algorithms. …”
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    Mathematical formulation of tabu search in combinatorial optimization by Ismail, Zuhaimy

    Published 2008
    “…CARP is known to be Non-deterministic Polynomialtime hard (NP-hard) where solutions are obtained through heuristic methods. Tabu Search (TS) is a heuristic method based on the use of prohibition-based techniques and basic heuristics algorithms like local search. …”
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    Monograph
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    Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

    Published 2020
    “…Finally, the obtained results corroborate the premise of the proposed method through the enhanced accuracy compared to the existing artificial intelligence-based models. …”
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  14. 14

    Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

    Published 2013
    “…To overcome the problems, this research work has proposed few modified and new ABC variants; Gbest Influenced-Random ABC (GRABC) algorithm systematically exploits two different mutation equations for appropriate exploration and exploitation of search-space, Multiple Gbest-guided ABC (MBABC) algorithm enhances the capability of locating global optimum by exploiting so-far-found multiple best regions of a search-space, Enhanced ABC (EABC) algorithm speeds up exploration for optimal-solutions based on the best so-far-found region of a search-space and Enhanced Probability-Selection ABC (EPS-ABC) algorithm, a modified version of the Probability-Selection ABC algorithm, simultaneously capitalizes on three different mutation equations for determining the global-optimum. …”
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  15. 15

    Ant colony optimization algorithm for rule based classification: Issues and potential by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2018
    “…ACO has gained importance because of its stochastic feature and iterative adaptation procedure based on positive feedback, both of which allow for the exploration of a large area of the search space. …”
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    Modelling of flexible beam based on ant colony optimization and cuckoo search algorithms by Ali, Siti Khadijah, Fadzilan, Mohamad Faisal, Shaari, Aida Nur Syafiqah, Hadi, Muhamad Sukri, Ting, Rickey Pek Eek, Mat Darus, Intan Zaurah

    Published 2021
    “…Currently, there are plenty of methods that have been developed by researchers to suppress undesired vibration. Based on previous studies, most researchers nowadays use system identification (SI) as a modelling technique to develop a dynamic model of flexible structure via swarm intelligence algorithm (SIA). …”
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    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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