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An improved bat algorithm with artificial neural networks for classification problems
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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Optimum tie switches allocation and DG placement based on maximisation of system loadability using discrete artificial bee colony algorithm
Published 2016“…The proposed algorithm is tested on 16-Bus, 33-Bus and 69-Bus radial distribution test system. …”
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Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing
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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Artificial bee colony for inventory routing problem with backordering
Published 2014“…We modify the standard ABC algorithm by incorporating the inventory and backorder information and, a new inventory updating mechanism incorporating the forward and backward transfers. …”
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Deterministic and stochastic inventory routing problems with backorders using artificial bee colony / Huda Zuhrah Ab Halim
Published 2019“…The DSIRP is then extended to handle backorder decisions (DSIRPB) which is the fourth variant of IRP studied. A new MILP for DSIRPB is formulated and used within the algorithm. …”
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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…This thesis presents works on swarm intelligence algorithms that are inspired by real echolocation of a colony of bats and its performance evaluation to solve optimisation problems. …”
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Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah
Published 2009“…The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah
Published 2009“…The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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Improved tree routing protocol in zigbee networks
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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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm
Published 2013“…Each bat in Bat Algorithm represents a candidate solution for the problem and each dimension in the search space of the Bat Algorithm represents a parameter of intrinsic parameters: skew, focal length, and magnification factor. …”
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Conference or Workshop Item -
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A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem
Published 2022“…The Bat Algorithm's performance is evaluated using a case study from a database from Le2i Universite de Bourgoune. …”
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Optimum network reconfiguration based on maximization of system loadability using continuation power flow theorem
Published 2014“…This paper presents a new algorithm for network reconfiguration based on maximization of system loadability. …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Evaluation was performed separately to further analyze the strength of Bat and Cuckoo Search to optimize LSSVM parameters. …”
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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…This research will conduct comparison of hybrid Genetic Algorithm and Bat Algorithm (GA-BA) with Genetic Algorithm (GA) and Bat Algorithm (BA). …”
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Academic Exercise -
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…The purpose of this research is to apply and evaluate the performance of Bat Algorithm for classification. …”
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Undergraduates Project Papers -
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Bat algorithm for dam–reservoir operation
Published 2018“…This study investigates one of the new optimization algorithms, namely, Bat Algorithm (BA). The BA is incorporated with different rule curves, including first-, second-, and third-order rule curves. …”
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Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months
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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