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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. …”
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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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An improved genetic bat algorithm for unconstrained global optimization problems
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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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Modified adaptive bats sonar algorithm with doppler effect mechanism for solving single objective unconstrained optimization problems
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Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm
Published 2022“…Three different optimization algorithms which are Bat Algorithm (BA), Bat Algorithm with Mutation (BAM) and Extended Bat Algorithm (EBA) are implemented to optimize the value of PID controller gain for wheel mobile robot. …”
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PID controller design for mobile robot using Bat Algorithm with Mutation (BAM)
Published 2019“…Here, an optimization algorithm called Bat Algorithm with Mutation (BAM) is proposed to optimize the value of PID controller gain for mobile robot. …”
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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali
Published 2025“…This study explores the application of sentiment analysis using the Naive Bayes algorithm to understand public perceptions of marital issues, particularly factors contributing to the rising divorce rate. …”
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
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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Enhancing benchmark optimization with evolutionary random approach: A comparative analysis of modified adaptive bats sonar algorithm (MABSA)
Published 2025“…This article presents a novel hybrid algorithm, combining the Modified Adaptive Bats Sonar Algorithm (MABSA) with the Squirrel Search Algorithm (SSA), and compares its performance with the original MABSA. …”
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Text classification using Naive Bayes: An experiment to conference paper
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad
Published 2023“…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment
Published 2024Proceedings Paper -
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad, Khyrina Airin Fariza Abu Samah and Nuwairah Aimi Ahmad...
Published 2023“…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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Book Section -
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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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