Search Results - (( mobile relationships tree algorithm ) OR ( panel classification based algorithm ))*
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Reverse migration prediction model based on machine learning / Azreen Anuar
Published 2024“…For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach
“…A variation of k-NN algorithms were tested based on the number of neighbours, as well as the weight and the type of distance metric used. …”
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Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques
Published 2018“…Two classification methods, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used in order to investigate the performance of classification accuracy for this E-nose system. …”
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Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection
Published 2024“…On the KDDTest+ dataset, the proposed method also outperforms single CART and ANFIS in terms of various metrics other than precision. Since the CART tree is a binary tree, it can only represent the relationship between data through a split based on a single attribute at a single tree node. …”
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A quality of experience approach in smartphone video selection framework for energy efficiency
Published 2021“…A smartphones energy management is crucial to overcome both of these issues. Thus, a QoE Mobile Video Selection (QMVS) framework is proposed. …”
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State of charge estimation for electric vehicles using random forest
Published 2024“…By leveraging decision trees and ensemble learning, the RF model forms resilient relationships between input parameters, such as voltage, current, ambient temperature, and battery temperatures, and SOC values. …”
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study
Published 2019“…After choosing the optimal sensor combination for each soil property, the predictive capability was compared using different data mining algorithms, including support vector machines (SVM), random forest (RF), multivariate adaptive regression splines (MARS), and regression trees (CART). …”
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