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114 results for “decision tree”
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Research ArticleOpen accessPhrase in the titleDECISION TREE BASED OCCLUSION DETECTION IN FACE RECOGNITION AND ESTIMATION OF HUMAN AGE USING BACK PROPAGATION NEURAL NETWORKP. Karthigayani, S. SridharOcclusion detection in face verification is an essential problem that has not widely addressed. In this study the research is deals about occlusion detection in face recognition and estimation of human age using image processing. The objects hide from another object is called as occlusion. Occlusion conditions may vary from face wearing sunglasses, wearing of scarf in the eyes and … …Journal of Computer Science, Vol. 10, Issue 1 · 12 Nov 2013 · 6,770 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleClassification Model for Hotspot Occurrences Using Spatial Decision Tree AlgorithmImas Sukaesih Sitanggang, Razali Yaakob, Norwati Mustapha, A. N. AinuddinDeveloping a predictive model for forest fires occurrence is an important activity in a fire prevention program. The model describes characteristics of areas where fires occur based on past fires data. It is essential as an early warning system for preventing forest fires, thus major damages because of fires can be avoided. This study describes the application of data mining … …Journal of Computer Science, Vol. 9, Issue 2 · 11 Apr 2013 · 7,224 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAnalysis of Decision Trees in Context Clustering of Hidden Markov Model Based Thai Speech SynthesisSuphattharachai ChomphanProblem statement: In Thai speech synthesis using Hidden Markov model (HMM) based synthesis system, the tonal speech quality is degraded due to tone distortion. This major problem must be treated appropriately to preserve the tone characteristics of each syllable unit. Since tone brings about the intelligibility of the synthesized speech. It is needed to establish the tone questions and other … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 6,844 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleThe Performance of Maximum Likelihood, Spectral Angle Mapper, Neural Network and Decision Tree Classifiers in Hyperspectral Image AnalysisHelmi Zulhaidi Mohd Shafri, Affendi Suhaili, Shattri MansorSeveral classification algorithms for pattern recognition had been tested in the mapping of tropical forest cover using airborne hyperspectral data. Results from the use of Maximum Likelihood (ML), Spectral Angle Mapper (SAM), Artificial Neural Network (ANN) and Decision Tree (DT) classifiers were compared and evaluated. It was found that ML performed the best followed by ANN, DT and SAM with … …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 142,381 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleData Optimization with Multilayer Perceptron Neural Network and Using New Pattern in Decision Tree ComparativelyMurat Kayri, Omay CoklukProblem statement: The aim of the present study is to exemplify the use of Artificial Neural Networks (ANN) for parameter prediction. Missing value or unreal approach to some questions in scale is a problem for unbiased findings. To learn a real pattern with ANN provides robust and unbiased parameter estimation. Approach: To this end, data was collected from 906 students … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,200 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAnalyzing Temperature-Dependent Thermal Properties of Biomaterials Using Machine Learning MethodsArmaghan Shalbaftabar, Kristen Rhinehardt, Dhananjay KumarThis research utilizes machine learning models ANN, Random Forest, and Decision Tree to predict material properties of Ti-based biomaterials, including Young’s modulus, density, thermal conductivity, and specific heat at various temperatures. Data was sourced using web scraping and Plot Digitizer, validated against literature, and analyzed in Excel. The ANN model achieved strong performance, with R² = 0.980874 for TiAl and … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 12 Sep 2025 · 4,634 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,939 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMachine Learning Approaches for the Prediction of Gas Turbine TransientsArnaud Nguembang Fadja, Giuseppe Cota, Francesco Bertasi et al.Gas Turbine (GT) emergency shutdowns can lead to energy production interruption and may also reduce the lifespan of a turbine. In order to remain competitive in the market, it is necessary to improve the reliability and availability of GTs by developing predictive maintenance systems that are able to predict future conditions of GTs within a certain time. Predicting such situations … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 7,660 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAnalysis of Student Mental Health Dataset Using Mining TechniquesYemima Monica Geasela, Devi Yurisca Bernanda, Johanes Fernandes Andry et al.This study utilizes a decision tree model in RapidMiner to analyze a dataset from Kaggle, comprising 200 student records. Among these, 70 students reported mental health issues, while 130 did not. Strikingly, a significant majority of 58 out of the 70 students with mental health concerns do not seek assistance from professionals. This study underscores the pressing issue of underutilization … …Journal of Computer Science, Vol. 20, Issue 1 · 22 Dec 2023 · 6,963 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIntelligent Digital Signal Modulation Recognition using Machine LearningMudhafar Haji Mala Abd, Sadegh AminifarInrecent years, modulation type recognition has received a lot of attentionacross the board. There are several methods to detect modulation types, butthere are only a few effective methods to handle signals with a higher level ofnoise. This study introduces an approach to verify the ability of differentmachine learning algorithms to automatically manage noise in detecting digitalmodulations. This research examines two … …Journal of Computer Science, Vol. 18, Issue 10 · 26 Sep 2022 · 6,095 accessesView PDFCite