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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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QoS based fair load-balancing: paradigm to IANRA routing algorithm for wireless networks (WNs)
Published 2008“…In this paper, a new algorithm, Intelligent agent AntNet based Routing Algorithm (IANRA) is proposed to enhance load balancing strategy in Wireless Networks (WNs). …”
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Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive
Published 2023Conference Paper -
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Optimal short term load forecasting using LSSVM and improved BFOA considering Malaysia pandemic disrupted situation
Published 2024“…Inaccurate forecasts can have substantial economic consequences, especially during peak load periods. Due to that reason, in this study, the hybrid forecasting model based on the Least Square Support Vector Machine (LSSVM) and Improved Bacterial Foraging Optimization Algorithm (IBFOA) is developed to perform an accurate STLF and applied to load in Peninsular Malaysia during the pandemic disrupted situation. …”
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NEXT-HOUR ELECTRICITY PRICE FORECASTING USING LEAST SQUARES SUPPORT VECTOR MACHINE AND GENETIC ALGORITHM
Published 2023“…This is due to the fact that only two algorithms were used (LSSVM and GA), with the load and HOEP for the week preceding the forecasting hour as the inputs. …”
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Specific heat capacity extraction of soybean oil/mxene nanofluids using optimized long short-term memory
Published 2024“…Notably, 95% of the recorded data via differential scanning calorimetry (DSC) is used for training machine learning techniques. In comparison, 5% is used for testing and validation purposes of the developed algorithm. …”
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Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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Machine learning application in predicting anterior cruciate ligament injury among basketball players
Published 2025“…The optimal model was selected based on the mean area under the receiver operating characteristic curve (AUC-ROC) across 10 cross-validation runs and was used with Shapley Additive exPlanations to analyze the risk factors. …”
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Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm
Published 2023“…The algorithm aids in identifying ideal proportional, integral, and derivative gains based on varying load conditions. …”
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…In this project, an Artificial Neural Network (ANN) trained by the Invasive Weed Optimization (IWO) learning algorithm is proposed for short term load forecasting (STLF) model. …”
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Student Project -
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An evaluation of network load balancing through Ant Colony Optimization (ACO) based technique / Muhammad Nur Zikri Mohamad Hafizan
Published 2020“…This project works on developing an efficient network load balancing mechanism based on the Ant Colony Optimization (ACO) algorithm. …”
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Student Project -
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Optimized Load Balancing based Task Scheduling in Cloud Environment
Published 2014“…In this paper, task scheduling strategy based on load balancing Quantum Particles Swarm algorithm (BLQPSO) was proposed. …”
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Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Monograph -
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Evolutionary Programming (EP) based technique for secure point identification with load shedding technique in power transmission / Abdul Rahman Minhat
Published 2008“…The ability of EP to search for the optimal values of multi-load increase as compared to AVSA which is only able to conduct uniform load increase at several load buses has been identified as the strength of EP over AVSA.…”
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Optimization of load frequency control permancein two-area power system with PID controller using ICA and GSA algorithms / Mumuney Nurullahi Lekan
Published 2018“…The change in the system is signified by the change in the system frequency and tie-line (T-L) load. The performance of LFC has to be tuned properly so that the response can be optimized with a selected controller and algorithm for optimization. …”
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