Search Results - (( parameter evaluation tree algorithm ) OR ( parameter optimization _ algorithm ))
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Tree-based contrast subspace mining method
Published 2020“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan A...
Published 2023“…To achieve these objectives, the methods employed involve data preprocessing and implementing the Decision Tree (DT) algorithm for classification. The classification model is trained and tested using various split ratios, and the optimal depth for the DT is determined through parameter tuning to achieve the best accuracy. …”
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Differentially expressed wound-response-related proteins from a major agarwood-producing tree, Aquilaria malaccensis Lam. identified via 2-D electrophoresis
Published 2018“…A population-based metaheuristic, namely, Differential Evolution (DE) algorithm is then proposed to handle the multiobjective UTRP with the aim of devising an efficient transit route network that optimizes both passengers' and operators' costs. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…By using clustering method K-Means, we have found the best center point position to calculate Kernel matrix. at last, we have employed Quantum-behaved Particle Swarm Optimization (QPSO) to get the optimal kernel parameter in the proposed model. …”
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Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem
Published 2022“…It is also used extensively in experiments to test the performances of metaheuristic algorithms and their hybrids. For example, Tabu Search (TS) has been successfully hybridized with other techniques, including particle swarm optimization (PSO) algorithm and the two-stage TS algorithm to solve MKP. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. …”
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Water Quality Evaluation and Analysis by Integrating Statistical and Machine Learning Approaches
Published 2026journal::journal article -
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Development of Anthro-Fitness Model for evaluating firefighter recruits’ performance readiness using machine learning
Published 2024“…A k-means clustering algorithm was utilized to group the performance levels of the firefighters whilst a quadratic discriminant analysis model was employed to predict the grouping of firefighters based on these parameters. …”
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Development of anthro-fitness model for evaluating firefighter recruits' performance readiness using machine learning
Published 2024“…A k-means clustering algorithm was utilized to group the performance levels of the firefighters whilst a quadratic discriminant analysis model was employed to predict the grouping of firefighters based on these parameters. …”
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Comprehensive comparison of various machine learning algorithms for short-term ozone concentration prediction
Published 2023“…Forecasting; Learning algorithms; Machine learning; Monitoring; Neural networks; Ozone; Public health; Regression analysis; Air quality monitoring; Artificial neural network modeling; Gaussian process regression; Hyper-parameter; Hyper-parameter optimizations; Machine learning models; Ozone concentration; Ozone concentrations predictions; Quality monitoring system; Support vector regressions; Air quality…”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Near-infrared spectroscopy modeling of combustion characteristics in chip and ground biomass from fast-growing trees and agricultural residue
Published 2024“…This study focuses on the investigation and comparison of combustion characteristic parameters and combustion performance indices between fast-growing trees and agricultural residues as biomass sources. …”
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Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging
Published 2022“…The results showed that the support vector machine achieved the best performance from the combination of optimal image parameters with the highest classification rate of 100 %. …”
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Imbalanced multi-class power transformer fault data classification through Edited Nearest Neighbour-Manhattan-Random Forest
Published 2025“…Furthermore, Random Forest is compared to four machine learning algorithms including Support Vector Machine, XGBoost, Convolutional Neural Networks, and Decision Trees. …”
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A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh
Published 2021“…The second evaluation divides into three scenarios. The first one evaluates Coalition-Based Index-Tree framework independently, without any effect from Dynamic-Coalition framework and Static-Coalition algorithm. …”
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The supervised machine learning algorithm, SVM and Decision Tree are used for the estimation of the mangrove age into young and mature. …”
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