Search Results - (( based relationship tree algorithm ) OR ( spider optimization swarm algorithm ))*
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Social Spider Optimization On Pid Controller
Published 2017“…Thus, in order to solve high-dimensional function optimization problem, many swarm intelligence algorithms have been proposed. …”
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Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition
Published 2018“…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…The proposed algorithm has been compared with the other three famous algorithms, which are Particle Swarm Optimization (PSO), Differential Evolutionary (DE), and Bees Optimization Algorithm (BOA). …”
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Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti
Published 2024“…This research project focuses on developing a laptop price prediction model using the decision tree algorithm based on laptop specifications. The objective is to provide a reliable tool for students, laptop buyers, and sellers to estimate laptop prices accurately. …”
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Accuracy and performance analysis for classification algorithms based on biomedical datasets
Published 2021“…Trees based Decision Tree (ID3) algorithm, Bayesian Theorem based Hidden Naïve Bayes (HNB) algorithm. …”
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…Here, a robust stopping rule for the cluster tree base on the median and median absolute deviation (MAD) of the tree heights is proposed. …”
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Using unique-prime-factorization theorem to mine frequent patterns without generating tree
Published 2011“…Our algorithm works based on prime factorization and is called Prime Factor Miner (PFM). …”
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Reverse migration prediction model based on machine learning / Azreen Anuar
Published 2024“…And the third objective is to evaluate reverse migration prediction model based on machine learning analysis. For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
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Seeing trees from space: above-ground biomass estimates of intact and degraded montane rainforests from high-resolution optical imagery
Published 2017“…To this purpose, preprocessed IKONOS imagery was segmented using a watershed algorithm; stem diameter values were then estimated from the cross-sectional crown areas of these trees using regression relationships obtained from ground-based measurements. …”
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A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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Footwear quality evaluation using decision tree and logistic regression models
Published 2022“…The analysis showed that Decision Tree with Gini algorithm (three branches) in the first method prevails against the other methods with misclassification rate of 0.1307. …”
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Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Modelling of trees has attracted scientific research in various fields and disciplines since trees and forests play very important roles in the global system. …”
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Delineating mangrove forest zone using spectral reflectance
Published 2020“…Species identification with spectral library derived from in-situ measurements using SID algorithm and derived from Landsat 8 using SAM algorithm was done. …”
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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