Search Results - (( developing intention tree algorithm ) OR ( java implication based algorithm ))
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Detection of multiple mangoes using histogram of oriented gradient technique in aerial monitoring
Published 2016“…The project uses shape identification algorithm and Histogram of Oriented Gradient principle to detect and count the total number of mango on its tree using a quad copter with an attachable webcam. …”
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Classification model for hotspot occurrences using a decision tree method
Published 2011“…Forest fires in Indonesia mostly occur because of errors or bad intentions. This work demonstrates the application of a decision tree algorithm, namely the C4.5 algorithm, to develop a classification model from forest fire data in the Rokan Hilir district, Indonesia. …”
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Machine learning in predicting anti-money laundering compliance with protection motivation theory among professional accountants
Published 2023“…The research elaborates on the design and implementation of machine learning models based on three algorithms: Decision Tree, Gradient Boosted Tree, and Support Vector Machine. …”
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Reverse migration prediction model based on machine learning / Azreen Anuar
Published 2024“…For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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Modeling purchase intention towards edible bird's nest products among Malaysians
Published 2018“…Results showed logistic regression outer perform other classifiers to develop the purchase intention model. There are five variables identified which consist of age, gender, price, accessibility and halal authorize. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Gateway placement optimisation problem for mobile multicast design in wireless mesh networks
Published 2012“…Furthermore, the paper develops the sketch of modeling and formulation of IGW placement problem with the objective of optimising IGW placement while cost of multicast tree and mobility are optimised. …”
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Predicting factors of library traffic for UiTMCTKKT Cendekiawan Library using predictive analytics / Azzatul Husna Abdul Aziz
Published 2025“…The CRISP-DM methodology was followed to apply machine learning algorithms, namely Random Forest, Decision Tree, and Naive Bayes, to the data gathered in the library which is traffic, book rentals, and questionnaires. …”
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