Search Results - (( intelligence a ((bee algorithm) OR (bat algorithm)) ) OR ( intelligence based e algorithm ))

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  1. 1

    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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    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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    Article
  3. 3

    A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems by Yaseen, Zaher, Ehteram, Mohammad, Hossain, Md., Fai, Chow, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, Lai, Sai Hin, Zaini, Nuratiah, Ahmed, Ali, El-Shafie, Ahmed

    Published 2019
    “…The current research is devoted to the implementation of hybrid novel meta-heuristic algorithms (e.g., the bat algorithm (BA) and particle swarm optimization (PSO) algorithm) to formulate multi-purpose systems for power production and irrigation supply. …”
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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
  7. 7

    Extended bat algorithm for PID controller tuning of wheeled mobile robot and swarm robotics target searching strategy by Nur Aisyah Syafinaz, Suarin

    Published 2020
    “…Extended Bat Algorithm (EBA) has been chosen as swarm intelligent based method for this research study. …”
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    Thesis
  8. 8

    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
  9. 9

    Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

    Published 2020
    “…The paper also presents the topic of missing values in the dataset, as well as compares the performance of the optimized SVR with the original SVR in terms of accuracy and execution time while handling missing values in a large dataset. The novel optimization-based artificial intelligence algorithm proposed in this paper implies an improved way to overcome a real engineering challenge i.e. handling missing values for better RUL prediction, hence bringing great opportunities for the domain area. …”
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    Article
  10. 10

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

    Published 2016
    “…The algorithm is a hybrid algorithm that operates using dual level search strategy that takes merits of a particle swarm optimisation algorithm and a modified adaptive bats sonar 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
    “…Simulation results show that, at the high-level inverter, the proposed algorithm can easily find the feasible solutions, however, GA, PSO, bee algorithm (BA), and differential evolution (DE) face the difficulty due to less exploration capability. …”
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    Thesis
  12. 12

    A New Bats Echolocation-based Algorithm for Single Objective Optimisation by N. M., Yahya, Tokhi, M. Osman, Kasdirin, Hyreil Anuar

    Published 2016
    “…Bats sonar algorithm (BSA) as a swarm intelligence approach utilises the concept of echolocation of bats to find prey. …”
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    Article
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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
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    Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli by Ramli, Muhammad Harith

    Published 2017
    “…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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    Thesis
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    An improved genetic bat algorithm for unconstrained global optimization problems by Muhammad Zubair, Rehman, Kamal Z., Zamli, Abdullah, Nasser

    Published 2020
    “…Therefore, to ensure that GA converges to a global solution, this paper proposed a two-stage improved Genetic Bat algorithm (GBa) in which the GA finds the optimal solution first and then Bat starts from where the GA has converged. …”
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    Conference or Workshop Item
  20. 20

    An improved bat algorithm with artificial neural networks for classification problems by Rehman Gillani, Syed Muhammad Zubair

    Published 2016
    “…ABC, HS, CS, WS, BPNN, LM, and ERNN etc.). Recently, a new metaheuristic search Bat algorithm has become quite popular due its tendency towards convergence to optimal points in the search trajectory by using echo-location behavior of bats as its random walk. …”
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    Thesis