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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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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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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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Smart site monitoring system / Muhammad Azmi and Muhammad Naim Mahyuddin
Published 2023“…The Smart Site Monitoring System is an innovative and integrated approach designed to optimise a construction site management. …”
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A greedy heuristics multiple criteria model for solving multi-landfill site selection and plant propagation algorithm for improving waste collection vehicle routing solutions
Published 2023“…Both models were tested on a WCVRP benchmark problem and a case-based scenario in Kubang Pasu, Kedah. Five candidate landfill sites were considered. …”
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Cloud-based lightweight detection of hardhat compliance based on YOLOv5 in power construction site
Published 2025“…Based on You Only Look Once (YOLO) v5, A cloud-based real-time hardhat-wearing compliance detection system was proposed to detect workers not wearing hardhats in power construction sites. …”
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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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Image Detection Model for Construction Worker Safety Conditions using Faster R-CNN
Published 2024journal::journal article -
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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Modified anfis architecture with less computational complexities for classification problems
Published 2018“…The proposed ANFIS model is trained by one of the metaheuristics approach instead of standard two pass learning algorithm. …”
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SVM for network anomaly detection using ACO feature subset
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Wi-Fi signal strengths database construction for indoor positioning systems using Wi-Fi RFID
Published 2013“…In this research we present a new approach of constructing fingerprint database. We propose a hybrid calibration procedure that combines signal sampling process with path-loss prediction algorithm. …”
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Wi-Fi signals database construction using chebyshev wavelets for indoor positioning systems
Published 2019“…The field tests as well as computer simulation results showed significant improvement in signal strength prediction accuracy compared to existing approximation algorithms. Furthermore, the proposed algorithm can recover missing signal values with much smaller number of on-site measurements compared to conventional calibration algorithm.…”
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