Search Results - regression ((((line algorithm) OR (acs algorithm))) OR (bees algorithm))
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…The contributions of this study straddle research perspectives of enhancing Regression Testing with Particle Swarm-Artificial Bee Colony Algorithm, and practical perspectives by providing software testing practitioners the TCP framework that can facilitate and accelerate the production of high-quality software products by revealing faults early and reducing time, cost, and human efforts through automation.…”
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Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm
Published 2022“…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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Do CEO and chairman characteristics affect green innovation? evidence from a comparative analysis of machine learning models
Published 2024“…Using the extreme gradient boosting (XGBoost) algorithm, which is at the forefront of machine learning algorithms, this study comprehensively examines the impact of CEO and chairman characteristics on corporate green innovation. …”
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Prediction of forex trend movement using linear regression line, two-stage of multi-layer perceptron and dynamic time warping algorithms
Published 2016“…This paper aims to investigate the repeated trend patterns as features from historical Forex data, which proposes new combination techniques - Linear Regression Line, two-stage of Multi-Layer Perceptron and Dynamic Time Warping algorithms in order to improve the performance of prediction significantly, thus achieving greater accuracy.…”
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Estimation of optimal machining control parameters using artificial bee colony
Published 2013“…It was reported by previous researches that artificial bee colony (ABC) algorithm has less computation time requirement and offered optimal solution due to its excellent global and local search capability compared to the other optimization soft computing techniques. …”
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Prediction of Forex trend movement using linear regression line, two-stage of multi-layer perceptron and dynamic time warping algorithms
Published 2016“…This paper aims to investigate the repeated trend patterns as features from historical Forex data, which proposes new combination techniques - Linear Regression Line, two-stage of Multi-Layer Perceptron and Dynamic Time Warping algorithms in order to improve the performance of prediction significantly, thus achieving greater accuracy…”
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Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms
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Depth Map Estimation based on Linear Regression using Image Focus
Published 2011“…Then linear regression model is used to find lines that approximate these datasets. …”
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Three-term conjugate gradient method under Armijo line search for unemployment rate in Malaysia / Muhammad Fiqhi Zulkifli
Published 2023“…TTDY is the most effective method based on numerical results but only TTRMIL+ can be applied in regression analysis.…”
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Sales prediction for media platforms advertising expenditure using Linear Regression / Nur Athirah Abdurahman
Published 2023“…The study focuses on the application of the Linear Regression algorithm to predict sales outcomes based on advertising spending patterns. …”
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Detection of multiple outliners in linear regression using nonparametric methods
Published 2004“…REFERENCES Agullo, J. (2000). New Algorithms for Computing the Least Trimmed Squares Regression Estimator. …”
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Extended spatial decision tree algorithm for classifying hotspot occurrence
Published 2013“…For comparison, classifiers for hotspots occurrence were also developed using the non-spatial methods namely the ID3 algorithm and the C4.5 algorithm as well as the logistic regression. …”
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Predicting the onset of acute coronary syndrome events and in-hospital mortality using machine learning approaches / Song Cheen
Published 2023“…The ML models for regression and classification were developed and optimized; the regression models aimed to predict ACS patients’ hospitalization and mortality rates, while the classification models were designed to predict the mortality risk of ACS patients under the influence of air pollution. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer
Published 2023“…This algorithm named JAABC5ROC is the enhancement of Artificial Bee Colony (ABC) variant, JA-ABC5 by combining with Rate of Change (ROC)\. …”
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Optimal timber transportation planning in tropical hill forest using bees algorithm
Published 2022“…This study proposed a multi-objective linear programming model with Bees algorithm (BA) to find an optimal cost TTP for extraction, forest road, and landing locations. …”
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AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION
Published 2022“…The developed algorithm is trained on the augmented Chinese Power Line Insulator Dataset (CPLID) that consisted of normal and missing cap insulator images. …”
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Real time long range (LoRa) based indoor positioning system using Deep Gaussian Process (DGP) algorithm / Ng Tarng Jian
Published 2025“…Through experimental evaluation and comparison of various machine learning algorithms, including Deep Gaussian Process (DGP) regression, the research demonstrates the effectiveness of DGPs in achieving precise single-point estimation, by keeping the mean absolute error to below 5 meters. …”
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Twisted pair cable fault diagnosis via random forest machine learning
Published 2022“…Then, the random forests algorithms (RFs), a data-driven method, are adopted to train the fault diagnosis classifier and regression algorithm with the processed fault data. …”
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