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Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…The algorithmic solution with some strategies mainly focuses on efficiency. …”
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Content-based recommender system for an academic social network / Vala Ali Rohani
Published 2014“…In this study, a new algorithm is proposed to represent an enhanced version of content-based recommender systems by utilizing social networking features. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
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Classification models for higher learning scholarship award decisions
Published 2018“…In addition, the knowledge analysis of the decision tree model was also made and found that some new information derived from the acquisition of this research information may help the stakeholders in making new policies and scholarship programs in the future.…”
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Named entity recognition using a new fuzzy support vector machine.
Published 2008“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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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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Multi-criteria divisible load scheduling in binary tree network
Published 2016“…The traditional divisible load scheduling assumes that the processors report their true computation and communication rates, i.e., they do not cheat the algorithm. In the real applications, the processors may cheat the algorithm, which means, the processors might not report their true computation or communication rates. …”
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Determination of tree height based on tree crown using algorithm derived from UAV imagery / Suzanah Abdullah ... [et al.]
Published 2021“…In this study, UAV technology has been taking a look at several algorithms for estimating tree height value of a single tree crown. …”
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Multi-base number representation in application to scalar multiplication and pairing computation
Published 2011“…Multi-bases number representation is used to construct new versions of Miller’s algorithm. …”
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Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti
Published 2024“…This research project focuses on developing a laptop price prediction model using the decision tree algorithm based on laptop specifications. The objective is to provide a reliable tool for students, laptop buyers, and sellers to estimate laptop prices accurately. …”
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Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency
Published 2024“…This study presents a Reinforcement Learning-based algorithm designed to optimise irrigation for Durio Zibethinus (i.e., durian) trees, aiming to maximise tree growth and reduce water usage. …”
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Adaptive beamforming algorithm based on Simulated Kalman Filter
Published 2017“…Some of the metaheuristic algorithms have been modified from the original algorithms to improve the algorithms performance in adaptive beamforming application. …”
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Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks
Published 2015“…Simulation results show that the proposed algorithm converges and outperforms a source based tree algorithm. …”
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Proceeding Paper -
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An extended ID3 decision tree algorithm for spatial data
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