Search Results - (( data optimization bat algorithm ) OR ( data generation using algorithm ))

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  1. 1

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…As a result, the highest average accuracy generated which is 96.91% by using WBCD dataset. The average accuracy of Bat Algorithm is comparing with other methods. …”
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    Undergraduates Project Papers
  2. 2

    Multi-Robot Learning with Bat Algorithm With Mutation (Bam) by Chandrathevan, Sathiamurthy

    Published 2022
    “…BAT algorithm uses echolocation technique like bats to generate bat population and random data is generated, the robot then traverses and the distance is calculated which is compared to the distance from the obstacle. …”
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    Undergraduates Project Papers
  3. 3

    Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin

    Published 2011
    “…The data for model training and validation are generated using semi-empirical models developed by the authors. …”
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    Conference or Workshop Item
  4. 4

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…Hence, efficient solutions are necessary to optimize EE and at the same time achieve high data rates to meet green LTE requirements. …”
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    Thesis
  5. 5

    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

    Published 2019
    “…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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    Thesis
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    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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    Article
  9. 9

    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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    Thesis
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    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…Secondly, two meta-heuristics, namely, Bi-Objective Gravitational Search Algorithm (BOGSA) and Bi-Objective Bat Algorithm (BOBAT), were combined to form a (BOGS-BAT) algorithm. …”
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    Thesis
  12. 12

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…The Modified Adaptive Bats Sonar Algorithm (MABSA), initially designed for single objective optimization and inspired by colony bats' echolocation, has demonstrated efficiency with its simple structure and reduced computation time. …”
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    Thesis
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    Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram, Mohammad, Othman, Faridah, Yaseen, Zaher Mundher, Afan, Haitham Abdulmohsin, Allawi, Mohammed Falah, Malek, Marlinda Abdul, Ahmed, Ali Najah, Shahid, Shamsuddin, Singh, Vijay P., El-Shafie, Ahmed

    Published 2018
    “…In this study, a hybrid of the bat algorithm (BA) and the particle swarm optimization (PSO) algorithm, i.e., the hybrid bat-swarm algorithm (HBSA), was developed for the optimal determination of these four parameters. …”
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    Article
  16. 16

    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

    Published 2014
    “…Owing to the fact that they are new and much of their relative performance are still unknown (as compared to other established meta-heuristic algorithms), Bacterial Foraging Optimization Algorithm (BFO) and Bat Algorithm (BA) have been adopted for comparison using the 12 selected benchmark functions. …”
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    Conference or Workshop Item
  17. 17

    Metaheuristic Algorithms and Neural Networks in Hydrology

    Published 2024
    “…It starts with the introduction of ANNs as a black box model, followed by the coupling of various metaheuristic algorithms with ANNs to form novel neural network models for solving real-world problems in hydrology, including Particle Swarm Optimization (PSO) for rainfall-runoff modeling, Bat Optimization (Bat) and Cuckoo Search Optimization (CSO) for future rainfall prediction, the Whale Optimization Algorithm (WOA) and Salp Swarm Optimization (SSO) for future water level prediction, Grey Wolf Optimization (GWO), Multi-Verse Optimization (MVO), the Sine Cosine Algorithm (SCA) and the Hybrid Sine Cosine and Fitness Dependent Optimizer (SC-FDO) for imputing missing rainfall data.…”
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    Book
  18. 18

    TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm by Kamal Z., Zamli, Alsariera, Yazan A.

    Published 2016
    “…This project develops a novel strategy to minimize the test consideration using the Particle Swarm Optimization and the Bat Algorithm.…”
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    Conference or Workshop Item
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    Bat algorithm and neural network for monthly streamflow prediction by Zaini N., Malek M.A., Yusoff M., Osmi S.F.C., Mardi N.H., Norhisham S.

    Published 2023
    “…Two prediction models are proposed in this study which are BPNN and hybrid Bat-BPNN. Monthly historical rainfall data, antecedent river flow data and meteorology parameters data for two different rivers were used as the input to the proposed models. …”
    Conference Paper