Search Results - (( using modification tree algorithm ) OR ( java application stemming algorithm ))
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Amtree Protocol Enhancement by Multicast Tree Modification and Incorporation of Multiple Sources
Published 2008“…In mobile environment, when the source is mobile and migrates to a new location, the multicast tree needs to be rebuilt. AMTree is an active network based protocol intended to make the sending packets to the tree after source migration an efficient process without much modifications to the multicast tree. …”
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Pattern generation through feature values modification and decision tree ensemble construction
Published 2013“…It is found that the performance of bagging and RSM algorithms can be improved by incorporating feature values modification with their training processes. …”
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Research on risk detection of autonomous vehicle based on rapidly-exploring random tree
Published 2023“…On the premise of ensuring safety and meeting the requirements of the vehicle’s kinematic constraints through the expansion of obstacles, the dynamic step size is used for random tree growth. A non-particle collision detection (NPCD) collision detection algorithm and path modification (PM) path modification strategy are proposed for the collision risk in the turning process, and geometric constraints are used to represent the possible security threats, so as to improve the efficiency and safety of vehicle global path driving and to provide reference for the research of driverless vehicles.…”
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Classification of stock market index based on predictive fuzzy decision tree
Published 2005“…In this research, another modification of Fuzzy Decision Tree (FDT) classification techniques called predictive FDT is presented that aims to combine symbolic decision trees in data classification with approximate reasoning offered by fuzzy representation. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…We present another modification of fuzzy decision tree (FDT) classification techniques that aims to combine symbolic decision trees in data classification with approximate reasoning offered by fuzzy representation. …”
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Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem
Published 2022“…Multidimensional Knapsack Problem (MKP) has been widely used to model real-life combinatorial problems. It is also used extensively in experiments to test the performances of metaheuristic algorithms and their hybrids. …”
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. …”
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Articulated robots motion planning using foraging ant strategy
Published 2008“…An alternative search approach using ant behaviour in a robotics application is applied. …”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The Random Tree standalone ML-AP relay model presented the best performing models from the ML-APS relay model with the best average performance for the correctly classified fault types of 97.61 % at 5 % significance level above other ML algorithms. …”
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Tracking and recognizing the activity of multi resident in smart home environments
Published 2017“…Existing works mainly manipulate data association and algorithm modification on extra auxiliary of graphical nodes to model human tracking information in an environment to incorporate with the problems. …”
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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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