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Solving university examination timetabling problem using intelligent water drops algorithm
Published 2024Subjects: “…Intelligent water drops algorithm…”
Conference Paper -
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Solving University Examination Timetabling Problem Using Intelligent Water Drops Algorithm
Published 2024“…IWD is a recent metaheuristic population-based algorithm belonging to swarm intelligent category which simulate river system. …”
Proceedings Paper -
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Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging
Published 2016“…This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. …”
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Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
Published 2024“…In this paper, the optimised Apriori association rule algorithm is used as technical support to realise the function of interlocking fault diagnosis in the intelligent fault diagnosis system module. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. ANN is a computer-based simulation of the living nervous system which works quite differently from conventional programming. …”
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Thesis -
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Hybrid intelligent approach for network intrusion detection
Published 2015“…Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
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Optimal power allocation scheme for plug-in hybrid electric vehicles using swarm intelligence techniques
Published 2016“…However, PSOGSA method takes much longer computational time than single methods because of incorporating two single methods in one algorithm. …”
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Optimal power allocation scheme for plug-in hybrid electric vehicles using swarm intelligence techniques
Published 2016“…However, PSOGSA method takes much longer computational time than single methods because of incorporating two single methods in one algorithm. …”
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Computational dynamic support model for social support assignments around stressed individuals among graduate students
Published 2020“…Furthermore, this study provides an alternative method for software engineers in intelligent stress management systems to integrate social support-based concepts as one of the mechanisms in addressing the support of an individual with cognitive related stress.…”
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Thesis -
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Exploring c Environment (S/O: 12826)
“…It is relatively new swarm intelligence method, and it belongs to a kind of interactive evolutionary computation. …”
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Monograph -
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…Copyright © 2025 Basma Jumaa Saleh et al. Applied Computational Intelligence and Soft Computing published by John Wiley & Sons Ltd.…”
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Artificial intelligence technique in solving nano-process parameter optimization problem / Norlina Mohd Sabri...[et al.]
Published 2017“…The techniques are Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023Conference Paper -
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Cancer Prediction Based On Data Mining Using Decision Tree Algorithm
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Undergraduates Project Papers -
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Classification of Cervical Cancer Using Ant-Miner for Medical Expertise Knowledge Management
Published 2018“…However, none of existing intelligent methods is comprehensible, and they look like a black box to clinicians. …”
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Conference or Workshop Item -
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Artificial neural network approach for electric load forecasting in power distribution company / Hambali M. A ... [et al.]
Published 2017“…In recent years, there have been extensive researches seeking the best methods of improving the load forecast accuracy. Many of these methods are statistical based methods which include time series, regression, Box-Jenkins model, exponential smoothing and so on. …”
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