Search Results - (( data implication machine algorithm ) OR ( variable estimation using algorithm ))
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…The fixed block matching uses the same block size throughout the motion estimation process while the variable block matching uses different block size. …”
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A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The reweighted fast, consistent and high breakdown (RFCH) estimator is a multivariate procedure used to estimate the robust location and scatter matrix. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…The best algorithm will not be the same for all the data sets. …”
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Prediction of payment method in convenience stores using machine learning
Published 2023“…This study explores the application of machine learning techniques, specifically the Random Forest algorithm, to predict payment modes in the context of the Indonesian community. …”
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Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri
Published 2022“…The suitable independent variables (hL, DBH, and CPA) were vital to estimating the dependent variable (Sc) and producing a carbon stock map for the final result. …”
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A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023“…This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models
Published 2025“…Types of attacks can be Ping of Death, flooding, remote-controlled attacks, UDP flooding, and Smurf Attacks. Attack data was obtained from the ClaMP dataset, which has an unbalanced data set, and has very high noise, so it is necessary to analyze data packets in network logs and optimize feature extraction which is then analyzed statistically with machine learning algorithms. …”
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Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search
Published 2014“…These problems resulted in estimation errors and high computational cost. Hybrid genetic algorithm (GA) and Nelder-Mead local search mode 1 has been used to minimize demand estimation errors. …”
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Robust Estimation Methods And Outlier Detection In Mediation Models
Published 2010“…The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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Model selection approaches of water quality index data
Published 2016“…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION
Published 2015“…Hence, one of the objectives of this thesis is to address and enhance the introduced fundamental frequency adaptive filter method which was based on modified variable step size LMS (MVSS) algorithm using generalized square error normalized LMS algorithm. …”
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Bayesian logistic regression model on risk factors of type 2 diabetes mellitus
Published 2016“…The significant variables determined by maximum likelihood method were then estimated using the BLR method. …”
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A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science
Published 2021“…The study also revealed that machine learning algorithms such as random forest, gradient boosting machine, and classification and regression trees (CART) accurately predict air pollution hazard when integrated with spatial models. …”
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Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions
Published 2023“…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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Use of AR Block Processing for Estimating the State Variables of Power System
Published 2008“…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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Conference or Workshop Item -
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