Search Results - (( data distribution bees algorithm ) OR ( model validation bat algorithm ))

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  1. 1

    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
  2. 2

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”
    Conference paper
  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 fuzzy models are trained applying locally linear model tree algorithm followed by a meta-heuristic nature inspired algorithm called bat algorithm. …”
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    Conference or Workshop Item
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    A hybrid bat–swarm algorithm for optimizing dam and reservoir operation by Yaseen, Zaher Mundher, Allawi, Mohammed Falah, Karami, Hojat, Ehteram, Mohammad, Farzin, Saeed, Ahmed, Ali Najah, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, El-Shafie, Ahmed

    Published 2019
    “…This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). …”
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    Article
  6. 6

    Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia by Wee W.J., Chong K.L., Ahmed A.N., Malek M.B.A., Huang Y.F., Sherif M., Elshafie A.

    Published 2024
    “…Only a few simulation systems, where previous techniques failed to anticipate SF data quickly, let alone cost-effectively, and took a long time to execute. The bat algorithm (BA), a meta-heuristic approach, was used in this study to optimize the weights and biases of the artificial neural network (ANN) model. …”
    Article
  7. 7

    Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation by Islam, Syed Zahurul, Othman, Mohammad Lutfi, Islam, Syed Zahidul

    Published 2021
    “…The communication requirement for integrating Distributed Renewable Generation (DRG) into Smart Grid (SG) is not strict, where the reliability and critical demand of data delivery are compromised due to the low-data rate and power of ZigBee. …”
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    Article
  8. 8

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

    Published 2024
    “…Thirdly, the thesis validates the algorithm's performance on standard constrained single objective and multi objective benchmark test functions. …”
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    Thesis
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    An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

    Published 2021
    “…Therefore, to overcome these problems, this study proposed an improved dynamic load balancing technique known as HBAC algorithm which dynamically allocates task by hybridizing Artificial Bee Colony (ABC) algorithm with Bat algorithm. …”
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    Thesis
  12. 12

    Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

    Published 2018
    “…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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    Article
  13. 13

    Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia by Joe Wee Wei, Mr.

    Published 2023
    “…Uncertainty Analyses such as Taylor Diagram, Violin Plot, Relative Error, and Scatter Plot were applied to further validate the results. The Hybrid BA-ANN model proved to be versatile and robust when being applied to other study areas in Malaysia. …”
    text::Thesis
  14. 14

    Improved tree routing protocol in zigbee networks by Al-Harbawi, Mostafa Kamil Abdulhusain

    Published 2010
    “…ImpTR protocol uses an approach to select next hope depending on new algorithm and uses the same tree topology construction for distributing address to all sensor nodes in the network. …”
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    Thesis
  15. 15

    Investigation on the potential to integrate different artificial intelligence models with metaheuristic algorithms for improving river suspended sediment predictions by Ehteram M., Ghotbi S., Kisi O., Ahmed A.N., Hayder G., Fai C.M., Krishnan M., Afan H.A., EL-Shafie A.

    Published 2023
    “…Although the adaptive neuro fuzzy system (ANFIS) and multilayer feed-forward neural network (MFNN) have been widely used to simulate hydrological variables, improving the accuracy of the above models is an important issue for hydrologists. In this article, the ANFIS and MFNN models were improved by the bat algorithm (BA) and weed algorithm (WA). …”
    Article
  16. 16

    Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months by Suarin, Nur Aisyah Syafinaz, Chia, Kim Seng, Mohamad Fuzi, Siti Fatimah Zaharah

    Published 2024
    “…Since it is unrealistic to have a NIRS dataset that can represent unforeseen future changes, an algorithm that can adapt existing data for new samples is worth to be investigated. …”
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    Article
  17. 17

    Enhanced ABD-LSSVM for energy fuel price prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2013
    “…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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    Article
  18. 18

    Analysis the effectiveness of cryogenic treatment through roughness and temperature prediction using bonn technique / Manjunath.S and Ajay Kumar by S., Manjunath, Ajay, Kumar

    Published 2017
    “…Thus, the bat algorithm coupled with artificial neural network is a dynamic and specific method in advancing the overall least possible method for surface roughness prediction in face milling operations.…”
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    Article
  19. 19

    Enhanced ABC-LSSVM For Energy Fuel Price Prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2014
    “…This paper presents an enhanced Artifi cial Bee Colony (eABC) based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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    Article
  20. 20

    Optimizing the Social Force Model Using New Hybrid WOABAT-IFDO in Crowd Evacuation in Panic Situation by Hamizan, Sharbini, Roselina, Sallehuddin, Habibollah, Haron

    Published 2022
    “…Thus, this research proposes optimization using the one of the latest nature inspired algorithm namely WOABAT-IFDO (Whale-Bat and Improved Fitness-Dependent Optimization) in the SFM interaction component. …”
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    Proceeding