Search Results - (( java implementation path algorithm ) OR ( using negative tree algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Extended spatial decision tree algorithm for classifying hotspot occurrence
Published 2013“…This work proposes a new spatial decision tree algorithm namely the extended spatial ID3 decision tree algorithm to classify hotspots occurrence from a forest fires dataset that contains point, line and polygon features. …”
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Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm
Published 2021“…Proposed SVM algorithm achieved the lowest false negative value of (87 messages) while decision table and Naïve Bayes achieved false negative messages of 672 and 1359, respectively…”
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Classification model for hotspot occurrences using a decision tree method
Published 2011“…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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Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.]
Published 2023“…The results indicated that the Decision Tree and Random Forest algorithms provided the best detection accuracy at 96%, followed by the K-NN algorithm at 95%. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This work employed the use of machine learning approach. Four conventional classification algorithms: naïve bayes (NB), support vector machines (SVM), nearest neighbor (k-NN), and decision trees (J48) classifiers are implemented in identifying and categorizing tweet data of three political figures in Malaysia: Dato Seri Anwar, Dato Hadi Awang, and Lim Guang Eng, as either positive, negative, or neutral perceptions. …”
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Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems
Published 2016“…In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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Hotspot occurences classififcation using decision tree method: case study in the Rokan Hilir, Riau Province, Indonesia
Published 2010“…The results were a decision tree which contains 18 leaves and 26 nodes with accuracy about 63.17%. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg...
Published 2022“…Correlation analysis and four machine learning algorithms (random forest, decision tree regression, linear regression, and support vector regression) were used to analyze ozone and meteorological dataset in the study area. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg...
Published 2022“…Correlation analysis and four machine learning algorithms (random forest, decision tree regression, linear regression, and support vector regression) were used to analyze ozone and meteorological dataset in the study area. …”
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Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems
Published 2016“…In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms
Published 2022“…In the financial sector, machine learning algorithms are used to detect fraud, automate trading, and provide financial advice to investors. …”
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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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Thunderstorm Prediction Model Using SMOTE Sampling and Machine Learning Approach
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Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…In contrast to the conventional methods which perform detection from a single image, the stenosis detection algorithm using two images from various view angles to avoid false positive (stenosis overestimated) and false negative (stenosis underestimated). …”
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Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat
Published 2021“…Extracting the behaviour of polymorphic malware is one of the major issues that affect the detection result.The main idea in this work is focus the behaviour(dynamic) of polymorphic malware infect in computer system and to extract feature selection and evaluate a limited set of dataset in order to improve detection of polymorphic malware.This study used dynamic analysis and machine learning to improve malware detection.This research demonstrated improved polymorphic malware detection can be achieved with machine learning.This research used four types of machine algorithm which are K-Nearest Neighbours, Decision Tree, Logistic Regression, and Random Forest. …”
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