Search Results - (( _ application ((ccl algorithm) OR (tree algorithm)) ) OR ( its selection based algorithm ))
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1
A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…Ant-tree-miner (ATM) has an advantage over the conventional decision tree algorithm in terms of feature selection. …”
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014“…In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. …”
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3
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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4
Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
5
Data Classification and Its Application in Credit Card Approval
Published 2004“…The result of this application using the sample credit card approval dataset includes a decision tree, a set of rules derived from the decision tree and its accuracy. …”
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6
Assessment and enhancement of Landsat 8 land surface temperature retrieval using Mono Window Algorithm and machine learning approaches
Published 2025“…These findings demonstrate the potential of combining MWA with machine learning for reliable LST estimation and highlight its applicability in environmental and urban climate analysis research.…”
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A new mobile botnet classification based on permission and API calls
Published 2024Subjects:Conference Paper -
8
Improved tree routing protocol in zigbee networks
Published 2010“…ImpTR protocol uses an approach to select next hope depending on new algorithm and uses the same tree topology construction for distributing address to all sensor nodes in the network. …”
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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“…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. The base models' predictions are integrated using a support vector machine, significantly enhancing detection accuracy. …”
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11
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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Implementing BiSM and CCL algorithm for managing audio storage
Published 2012“…Therefore, this paper analyzed the issues and proposed a solution to manage the audio storage.The elements from biological inspired components were studied and identified to seek for the requirements of Bio-Inspired Storing Model (BiSM).Then a structural architecture of BiSM was designed in addition the Cognitive and Constructive Learning (CCL) algorithm was proposed.Finally, BiSM and CCL algorithm were evaluated with exemplar application settings and the results were presented in a case study of MP3 music collections.…”
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13
Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob
Published 2022“…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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14
Integrated reconstruction of 2D overlapping coronary artery from x-ray angiography with 3D virtual myocardial model using non-rigid iterative closest point algorithm
Published 2019“…In the reconstructed coronary artery tree. Its peculiar advantage lies in the 3D reconstruction of the coronary artery tree from X-ray angiographic images without the need for corresponding points between vessels in each view. …”
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15
Developing A Prediction Tool To Improve The Shading Efficiency Of The Pedestrian Zones
Published 2020“…The development of the prediction tool was conducted base on integrating three sequenced algorithms, which are sun position algorithm, shadow length and position algorithm, and expansion limit algorithm. …”
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16
An Automated System For Classifying Conference Papers
Published 2021“…The project is also aimed to select the best classification model for the system, based on an empirical study. …”
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17
Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing
Published 2015“…OBIA was performed in a rule-based structure that requires selecting and identifying rules. …”
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18
Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia
Published 2025“…The effectiveness of ITPS was evaluated using five machine learning algorithms: J48, Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbors. …”
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Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks
Published 2012“…Finally, we propose Self-Decision Route Selection scheme which is an improvement of the Hop-based Spanning Tree (HST) algorithm that is used in some routing protocols such as AODV and DSR. …”
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20
Integrating Information Gain and Chi-Square for Enhanced Malware Detection Performance
Published 2025“…As malware has progressed from its simpler, monomorphic variants to more sophisticated forms like oligomorphic, polymorphic, and metamorphic, a machine learning-based detection system is now required, surpassing the limitations of traditional signature-based methods. …”
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