Search Results - (( using ((factor error) OR (vector error)) algorithm ) OR ( java application using algorithm ))
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Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
Published 2021“…This work aims to model the combined cycle power plant (CCPP) using different algorithms. The algorithms used are Ridge, Linear regressor (LR), and support vector regressor (SVR). …”
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Multi-scene design analysis of integrated energy system based on feature extraction algorithm
Published 2022“…Then, convolution neural network is used to extract the feature vectors of comprehensive environmental factors. …”
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Data-driven rice yield predictions and prescriptive analytics for sustainable agriculture in Malaysia
Published 2024“…The study specifically evaluates the performance of Random Forest, Support Vector Machine (SVM), and Neural Network (NN) models using metrics like Correlation Coefficient, Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). …”
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Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu
Published 2018“…The position of reference currents is used to detect the voltage vectors surrounding the reference voltage vector in every sampling period. …”
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Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework
Published 2024“…The accuracy of the prediction was controlled using the root-mean-square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2). …”
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Optimization techniques to enhance the performance of induction motor drives: A review
Published 2023Review -
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Forecast innovative development level in green supply chains using a comprehensive fuzzy algorithm
Published 2022“…Then, a new method for using fuzzy weights of the factors used in the Support Vector Machine algorithm is proposed. …”
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Machine learning techniques for reference evapotranspiration and rice irrigation requirements prediction: a case study of Kerian irrigation scheme, Malaysia
Published 2025“…Two machine learning algorithms, named Support Vector Regression (SVR) and Random Forest (RF), were applied to predict ETo and rice irrigation requirements using only climatic data (rainfall, temperature, relative humidity, and wind speed). …”
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Assessment of suitable hospital location using GIS and machine learning
Published 2022“…The ML models Performance were verified using the receiver operating characteristics (ROC) curves and cross-validation with other evaluation metrics; correlation coefficient, root mean square error (RMSE), mean absolute error (MAE), relative absolute error (RAE), as well as root relative squared error (RRSE). …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…We used Nash-Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE) as evaluation metrics. …”
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…The lvABC algorithm is introduced to overcome the local optima problem by enriching the searching behaviour using Levy mutation. …”
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Web Algorithm search engine based network modelling of Malaria Transmission
Published 2013“…There are observed cases of attempting vector control on a trial and errors basis, with no scientific way of determining the locations of critical vector densities. …”
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Distance vector-hop range-free location algorithm for wireless sensor network
Published 2015“…Distance Vector-Hop (DV-Hop) algorithm has become the focus of studies for range-free localization algorithms. …”
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Modeling of mechanical properties of silica fume-based green concrete using machine learning techniques
Published 2022“…ML algorithms are used to predict SFC compressive strength to promote the use of green concrete. …”
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EMS decoding algorithm that introduced shuffled strategy and improved variable node update
Published 2022“…This algorithm updates by column, so that the latest variable node information of the last column can be used. …”
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