Search Results - machine ((loading algorithm) OR (means algorithm))
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations
Published 2013“…The BFO algorithm is used to create machine cells and part families. …”
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Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer
Published 2023“…Brain; Errors; Forecasting; Learning algorithms; Mean square error; Memory architecture; Network architecture; Smart meters; Time series; Demand-side; Electricity load; Error values; Load predictions; Machine learning algorithms; Mean absolute error; Mean squared error; Prediction errors; Regression problem; Times series; Long short-term memory…”
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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“…Least square support vector machines (LSSVM) are well suited to handle complex non-linear power load series. …”
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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“…Least square support vector machines (LSSVM) are well suited to handle complex non‑linear power load series. …”
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A novel hybrid metaheuristic algorithm for short term load forecasting
Published 2017“…With respect to that matter, this study presents a hybrid Least Squares Support Vector Machines (LSSVM) with a rather new Swarm Intelligence (SI) algorithm namely Grey Wolf Optimizer (GWO). …”
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms
Published 2022“…In the financial sector, machine learning algorithms are used to detect fraud, automate trading, and provide financial advice to investors. …”
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Hybrid Metaheuristic Algorithm for Short Term Load Forecasting
Published 2016“…With respect to that matter, this study presents a hybrid Least Squares Support Vector Machines (LSSVM) with a rather new Swarm Intelligence (SI) algorithm namely Grey Wolf Optimizer (GWO). …”
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Sensorless control system for assistive robotic ankle-foot
Published 2018“…Both estimation algorithms are built using C-code and assessed in MATLAB Simulink. …”
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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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A review energy-efficient task scheduling algorithms in cloud computing
Published 2023Conference Paper -
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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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A hybrid prediction model for short-term load forecasting in power systems
Published 2024“…By integrating the Salp Swarm Algorithm (SSA) with Least Squares Support Vector Machines (LSSVM), the iSSA-LSSVM model significantly improves LSSVM's prediction accuracy. …”
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Analysis Of Large In-Plane Displacement And Strain In Rubber Using 2-D Scanner-Based Digital Image Correlation
Published 2017“…The images were scanned and processed to obtain displacement, strain, load and stress data. The displacement data were obtained by using the incremental image correlation algorithm. …”
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Load forecasting for air conditioning systems using linear regression and artificial neural networks
Published 2024“…These findings suggest significant potential for reducing energy consumption, lowering operational costs, and improving equipment maintenance. Implementing machine learning algorithms in this context underscores their value in enhancing the efficiency, reliability, and cost-effectiveness of Air Handling Units (AHU) in industrial air conditioning systems.…”
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Book recommendation system using content-based filtering / Amalin Aliesya Mohd Azmi
Published 2023“…This is attributed to the intricacy of the content-based filtering algorithm, necessitating a substantial computational load on the central processing unit of a computer. …”
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Linear Discriminate Analysis And K-Nearest Neighbor Based Diagnostic Analytic Of Harmonic Source Identification
Published 2021“…This paper presents a comparison of machine learning (ML) algorithm known as linear discriminate analysis (LDA) and k-nearest neighbor (KNN) in identifying and diagnosing the harmonic sources. …”
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Machine learning application in predicting anterior cruciate ligament injury among basketball players
Published 2025“…A one-year follow-up was conducted to monitor ACL injury, identifying n=11 injured players. Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. …”
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