Search Results - (( java implementation path algorithm ) OR ( using learning drops 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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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025Subjects:Article -
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Recognising Malaysia traffic sign with rain drop disturbance using deep learning
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Machine learning algorithms for early predicting dropout student online learning
Published 2023“…This study uses access log data recorded in the LMS and student statistical information and calculated data and aims to present a suitable predictive algorithm for dropout early prediction systems for online learning students using machine learning. …”
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A comparative study and simulation of object tracking algorithms
Published 2020“…The algorithms using convolution features and multi-features fusion algorithms have more advantages in tracking accuracy than the algorithm using a single feature, but the tracking speed will also drop rapidly. …”
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DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS
Published 2011“…The ANN model has been developed using resilient back-propagation learning algorithm. …”
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Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman
Published 2025“…In the development phase, Convolutional Neural Network model was designed and trained using sophisticated techniques of data augmentation, dropping out and hyperparameter tuning under the supervised learning methodology to increase the performance of the system. …”
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Experimental implementation controlled SPWM inverter based harmony search algorithm
Published 2023Article -
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Development of predictive modeling and deep learning classification of taxi trip tolls
Published 2022“…Commercial navigation includes a wealth of trip-related data, including distance, expected journey time, and tolls that may be encountered along the way. Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection
Published 2024“…The data was gathered using real-time packet capturing tools which were then processed and moved with model development using different deep learning algorithms such as, LSTM, MLP, RNN and Autoencoders. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability
Published 2023“…Additionally, we find that some algorithms are more sensitive to data leakage than others, as seen by the drop in model accuracy when built without leakage. …”
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Automated traffic counting data collection and analysis
Published 2021“…This project proposed an automated traffic counting data collection and analysis algorithm that is able to use computer vision to count and measure the speed of vehicles, while also able to classify vehicles into different categories using the power of deep learning and AI. …”
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DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS
Published 2023“…Commercial navigation includes a wealth of trip-related data, including distance, expected journey time, and tolls that may be encountered along the way. Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah
Published 2024“…With a huge number of students drop out, the higher education institution’s reputation might be dropped. …”
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