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Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data
Published 2016“…This paper integrates decision tree–based data mining (DM) and object-based image analysis (OBIA) to provide a transferable model for the detailed characterization of urban land-cover classes using WorldView-2 (WV-2) satellite images. …”
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Genetic algorithms for VLSI micro-Cell layout area optimization based on binary tree
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Performance evaluation for different intrusion detection system algorithms using machine learning
Published 2018“…The objectives of this project is to evaluate the performance of various intrusion detection algorithms based on machine learning. The algorithms considered are the Naive Bays Algorithm, Decision Tree Algorithm and Hybrid Algorithm for different datasets. …”
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Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system
Published 2021“…In this paper, the Dijkstra-ant colony algorithm (ACO) with binary search tree (BST) has been proposed. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman
Published 2024“…The result indicated that the highest accuracy of 89.34% was achieved by the Random Tree algorithm, while the rule-based algorithm PART reached an accuracy of 87.56%. …”
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Nano-scale VLSI clock routing module based on useful-skew tree algorithm
Published 2006“…We implemented Useful-Skew Tree (UST) algorithm which is based on the deferred-merge embedding (DME) paradigm, as the clock layout synthesis engine. …”
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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor
Published 2024“…Subsequently, predictive models employing k-nearest neighbour and decision tree algorithms are constructed and evaluated based on accuracy, precision, and recall metrics. …”
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An efficient model for indoor radio signal prediction and coverage estimation / Md. Sumon Sarker
Published 2011“…In this regards, this study explores two algorithms. The first algorithm is an efficient and faster ray-tracing technique based on binary angle division for radio signal prediction in indoor environment. …”
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Prediction of Heart Disease Risk Using Machine Learning with Correlation-based Feature Selection and Optimization Techniques
Published 2021“…Numerous machine learning classifiers, Decision Tree, Discriminant Analysis, Logistic Regression, Naïve Bayes, Support Vector Machines, k-Nearest Neighbors, Bagged Trees, Optimizable Tree, and Optimizable k-Nearest Neighbors are trained using 10-fold cross-validation for efficient heart disease risk prediction on the Correlation-based Feature Selection optimal set of the integrated heart dataset. …”
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A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation
Published 2025“…Quantitative analysis highlights China’s prominent contributions to the field, while the thematic analysis reveals three key findings: (1) optimization methods based on intelligent algorithms such as NSGA-II, artificial neural networks, and gradient-boosted decision trees significantly enhance computational efficiency; (2) dynamic simulation integrated with lifecycle assessment enables a more comprehensive evaluation of building performance; and (3) climate-adaptive strategies improve building resilience to future climate uncertainties. …”
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Enhanced faster region-based convolutional neural network for oil palm tree detection
Published 2021“…Hence, this research aims to close the research gaps by exploring the deep learning-based object detection algorithm and the classical convolutional neural network (CNN) to build an automatic deep learning-based oil palm tree detection and counting framework. …”
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis
Published 2016“…In addition, exponential growth of data causes high computational costs in Apriori-like algorithms. Hence, this research aims to propose a two stage FPM, integrating Principal Component Analysis (PCA) and Weighted Apriori-T (PCA-WAT) algorithm to address these problems. …”
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…The integration of machine learning (ML) with gas hydrate-based desalination (GHBD) presents a significant advancement in the produced water treatment with special focus on efficient prediction of removal efficiency. …”
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Crown counting and mapping of missing oil palm tree using airborne imaging system
Published 2019“…The undetected group of missing oil palms trees are estimated based on the planting pattern design. …”
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Enhanced computational methods for detection and interpretation of heart disease based on ensemble learning and autoencoder framework / Abdallah Osama Hamdan Abdellatif
Published 2024“…In contrast, the second method addresses the data-level imbalance through a novel framework named Conditional Autoencoder with Stack Predictor for Heart Disease (CAVE-SPFHD). This approach integrates a conditional variational autoencoder (CVAE) to effectively balance the dataset and a stack predictor (SPFHD) that utilizes tree-based ensemble learning algorithms. …”
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