Search Results - (( java implementation path algorithm ) OR ( after implementation 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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2
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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3
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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5
An optimized attack tree model for security test case planning and generation
Published 2018“…By leveraging on the optimized attack tree algorithm used in this research work, the threat model produces efficient test plans from which adequate test cases are derived to ensure a secured web application is designed, implemented and deployed. …”
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Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013“…The objective was to identify and implement the most accurate algorithm for the KPTM dataset and to come up with a good prediction model using decision tree technique. …”
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Conference or Workshop Item -
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An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery
Published 2021“…This research implemented a technique for detecting, segmenting, classifying, and measuring tree stumps by using the Multiresolution Segmentation Algorithm method. …”
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Online Clothing Shopbots via Web Content Extraction / Nurul Syazwani Ramzi
Published 2017“…These block tree is constructed by using DOM (document object model) tree. …”
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9
Cyberbullying detection: a machine learning approach
Published 2022“…The machine learning algorithm, Support Vector Machine was chosen after comparing it with other algorithms such as Multinomial Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. …”
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Final Year Project / Dissertation / Thesis -
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis
Published 2016“…In conclusion, the proposed algorithm is able to overcome the rare item issue by implementing covariance based support value normalization and high computational costs issue by implementing indexing enumeration tree structure.Future work of this study should focus on rule interpretation to generate more human understandable rule by novice in data mining. …”
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Image segmentation for songket motif / Zati Iwani Zaharudin
Published 2007“…After process of comparing the three methods of image segmentation; region growing, edge detection and watershed segmentation, most appropriate method has been chosen and implemented it in prototype module. …”
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Dynamic scene occlusion culling in architectural scenes based on dynamic bounding volume
Published 2006“…In this thesis, the aim of the research carried out, is to handle dynamic objects efficiently with faster frame rate display. This algorithm is implemented using portal occlusion culling and kD-tree, which is suitable for indoor and architectural scenes. …”
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Water optimization technique for precision irrigation system using IoT and machine learning
Published 2022“…After implementation of proposed work, for single banana tree 31.4 of the water requirement has been optimized in 2020 time period. …”
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Phishing attack detection using machine learning method
Published 2019“…The study of this algorithm is made thoroughly and the methods in implementing this algorithm have been discussed in detail. …”
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Undergraduates Project Papers -
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A conceptual model for the E-commerce application recommendation framework using exploratory search
Published 2024journal::journal article -
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Classification of water quality using artificial neural network
Published 2020“…Then, the model performance was compared with the k-NN and Decision Tree models. The results obtained after training and testing the network showed that ANN performed better than to k-NN and Decision Tree model with the values of accuracy, sensitivity, precision and RMSE is 95.24%, 93.51%, 94.43% and 0.207 respectively. …”
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Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure
Published 2011“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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20
Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…Results: Based on the findings, neural network scored the highest overall accuracy of 98.6% after conducting filtering technique. Furthermore, reliefF-Gradient boosting and random forest algorithms achieved promising overall accuracy of 97.4% and 96.9%, respectively after implementing filtering and feature selection techniques. …”
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