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1
Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The BOGS-BAT algorithm is based on three techniques. The first technique is to move or switch solution from single function to functions that contain more than one objective functions. …”
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Thesis -
2
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. The value of parameter is already set to use when applying every dataset in an experiment. …”
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Undergraduates Project Papers -
3
A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm
Published 2013“…A case study taken from database, provided by Le2i Universite de Bourgoune is used to evaluate the performance of the Bat Algorithm. …”
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4
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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Article -
5
Extended Bat Algorithm (EBA) as an improved searching optimization algorithm
Published 2018“…This paper presents a new searching technique by using a new variant of Bat Algorithm (BA) known as Extended Bat Algorithm (EBA). …”
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Book Chapter -
6
Application of adaptive bats sonar algorithm to minimise car side impact design
Published 2017“…This project was focusing on the modification of bats sonar algorithm (BSA) and renamed to adaptive bats sonar algorithm (ABSA) due to some limitations of previous algorithm. …”
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Undergraduates Project Papers -
7
Bats echolocation-inspired algorithms for global optimisation problems
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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8
Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization
Published 2022“…Experimental and statistical analyses show that, in comparison with the bat as well as variants of the bat and state-of-the-art algorithms, the proposed algorithm substantially outperforms them significantly, based on MSE and BER.…”
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Article -
9
An improved bat algorithm with artificial neural networks for classification problems
Published 2016“…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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10
Dual level searching approach for solving multi objective optimisation problems using hybrid particle swarm optimisation and bats echolocation-inspired algorithms
Published 2019“…A dual level searching approach for multi objective optimisation problems using particle swarm optimisation and modified adaptive bats sonar algorithm is presented. …”
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Article -
11
Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions
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 -
12
Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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13
New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…However, the complexity significantly rises when dealing with multi objective functions. 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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14
Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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15
Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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16
Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024“…Thus, this study proposed an Opposition-based Learning Binary Bat Algorithm as the feature selection technique in the T-method. …”
Conference Paper -
17
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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18
An application of modified adaptive bats sonar algorithm (MABSA) on fuzzy logic controller for dc motor accuracy
Published 2021“…Therefore, this research presents works on the FLC system which is the fuzzy inference system that will be optimized by the modified adaptive bats sonar algorithm (MABSA) for the DC servo motor position control. …”
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19
An automated strabismus classification using machine learning algorithm for binocular vision management system
Published 2023“…To overcome these limitations, a machine learning algorithm, which is a case-based reasoning, is developed to automate the strabismus classification. …”
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Proceeding Paper -
20
Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. …”
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