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Bee colony optimisation of the travelling salesman problem in light rail systems
Published 2019“…The study reported in this paper aimed to identify the most efficient algorithm and develop a mathematical model based on artificial bee colony optimisation to solve this problem in light rail transit systems. …”
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Data-driven state of charge estimation of lithium-ion batteries: Algorithms, implementation factors, limitations and future trends
Published 2023“…Automotive batteries; Charging (batteries); Digital storage; Electric automobiles; Fossil fuels; Fuel storage; Ions; Lithium-ion batteries; Battery storage system; Data-driven algorithm; Detailed classification; Evaluation indicators; Global carbon emission; High energy densities; State-of-charge estimation; Vehicle applications; Battery management systems…”
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LSSVM parameters tuning with enhanced artificial bee colony
Published 2014“…The proposed model was employed in predicting financial time series data and comparison is made against the standard Artificial Bee Colony (ABC) and Cross Validation (CV) technique.The simulation results assured the accuracy of parameter selection, thus proved the validity in improving the prediction accuracy with acceptable computational time.…”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Laser-induced backscattering imaging for classification of seeded and seedless watermelons
Published 2017“…The LDA and kNN-based algorithms also obtained quite high classification accuracies with all the accuracies above 90%. …”
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Maldroid- attribute selection analysis for malware classification
Published 2019“…Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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Hybrid Classification Algorithm For Denial Of Service Attack Detection Using Rough Set Theory And Artificial Immune
Published 2024thesis::master thesis -
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Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months
Published 2024“…Thus, this study aims to evaluate the feasibility of homogenous transfer learning approaches to overcome data constraints in developing NIRS predictive models of stingless bee honey qualities across different months. …”
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A review of controllers and optimizations based scheduling operation for battery energy storage system towards decarbonization in microgrid: Challenges and future directions
Published 2022“…Additionally, the influences of battery energy storage system scheduling controllers in the decarbonizing microgrid are analyzed rigorously. …”
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A review of controllers and optimizations based scheduling operation for battery energy storage system towards decarbonization in microgrid: Challenges and future directions
Published 2022“…Additionally, the influences of battery energy storage system scheduling controllers in the decarbonizing microgrid are analyzed rigorously. …”
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Development of intrusion detection system using residual feedforward neural network algorithm
Published 2022“…An intrusion detection system (IDS) is required to protect data from security threats that infiltrate unwanted information via a regular channel, both during storage and transmission. …”
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Proceeding Paper -
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Efficient feature selection analysis for accuracy malware classification
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Conference or Workshop Item -
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Enhanced ABD-LSSVM for energy fuel price prediction
Published 2013“…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming
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Enhanced ABC-LSSVM For Energy Fuel Price Prediction
Published 2014“…To evaluate the effi ciency of the proposed model, crude oil prices data was employed as empirical data and a comparison against four approaches were conducted, which include standard ABC-LSSVM, Genetic Algorithm-LSSVM (GA-LSSVM), Cross Validation-LSSVM (CV-LSSVM), and conventional Back Propagation Neural Network (BPNN). …”
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CORROSION DAMAGE ANALYSIS USING IMAGE PROCESSING
Published 2018“…NDE is an automatic detection method for corrosion classification which can be implemented for the inspection of the pipelines and storage tanks in the oil and gas industry as it will not disturb their properties and performance.…”
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