Search Results - (( _ application ((means algorithm) OR (tree algorithm)) ) OR ( its application usage algorithm ))
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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Photogrammetric unmanned aerial vehicle for digital terrain model estimation under oil palm tree canopy area / Suzanah Abdullah
Published 2021“…Following the application of a new methodology on the real site, the result indicated the consistency of DTM values of all the algorithms at different flying heights but there were relatively small differences between all the algorithms used. …”
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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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Parsing algorithms for grammars with regulated rewriting
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An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP
Published 2007“…It has been shown that MEMISP algorithm has outperformed all other algorithms in terms of efficiency and scalability. …”
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Sentiment Analysis on Users' Satisfaction for Mobile Banking Apps in Malaysia
Published 2022“…The best accuracy result shows 94.37% by the Decision Tree algorithm, and Naïve Bayes obtained the worst outcome at 66%.…”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Comparative study of clustering-based outliers detection methods in circularcircular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. …”
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A new mobile botnet classification based on permission and API calls
Published 2024Subjects:Conference Paper -
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Developing emergency application for LRT passengers with decision tree algorithm (RailAlert!) / Ezrren Natasha Baddru’l-Sham … [et al.]
Published 2023“…With geolocation and decision tree algorithms, this project aims to design and develop an emergency application for LRT passengers. …”
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Book Section -
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Developing emergency application for LRT passengers with decision tree algorithm (RailAlert!) / Ezrren Natasha Baddru’l-Sham … [et al.]
Published 2023“…With geolocation and decision tree algorithms, this project aims to design and develop an emergency application for LRT passengers. …”
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Book Section -
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Resource-Efficient Coverage Path Planning for UAV-Based Aerial IoT Gateway
Published 2023“…As a result, the Energy Efficient Coverage Path Planning (EECPP) algorithm has been proposed. The EECPP is composed of two algorithms: the Stop Point Prediction Algorithm using K-Means, and Path Planning Algorithm using Particle Swarm Optimization. …”
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Assessment and enhancement of Landsat 8 land surface temperature retrieval using Mono Window Algorithm and machine learning approaches
Published 2025“…The Fine Tree of Regression Trees model achieved the highest accuracy, with RMSE of 0.8876 °C, MAE of 0.7878 °C, and R2 of 0.7011. …”
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Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms
Published 2023“…Carbon nanotubes; Electrocatalysts; Electrooxidation; Forestry; Formic acid; Gaussian distribution; Learning algorithms; Palladium; Parameter estimation; Regression analysis; Support vector machines; Formic acid electrooxidation; Fuel cell application; Gaussian kernel functions; Gaussian process regression; Interaction effect; Machine learning algorithms; Performance; Process parameters; Regression trees; Support vector machine regressions; Sensitivity analysis…”
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