Search Results - (( java implementation path algorithm ) OR ( waste solution learning 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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Waste management using machine learning and deep learning algorithms
Published 2020“…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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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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RGB and RGNIR image dataset for machine learning in plastic waste detection
Published 2025“…Machine learning has emerged as a potential solution for plastic waste due to its ability to analyse and interpret large volumes of data using algorithms. …”
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IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management
Published 2025“…The methodology integrates IoT technology and machine learning to tackle waste classification and collection inefficiencies. …”
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Modelling Of Biogas Production From Banana Stem Waste With Neural Networks Learning Strategies To Optimse The Production
Published 2017“…Biogas production from waste is a valuable renewable energy and with better process design, maximum biogas yield can be obtained from the same amount of waste. …”
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Novel Approaches to Plastic Pollution: Leveraging Machine Learning and Metaproteomics for Advanced Plastic Degradation
Published 2025journal::journal article::research article -
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Smart waste management system with IoT monitoring
Published 2023“…The Smart Waste Management System (SWMS) with IoT monitoring is a cutting-edge solution that utilizes Internet of Things technologies to optimize waste management processes. …”
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Efficient Model for Waste Load and Route Optimization
Published 2024“…The model utilizes machine learning techniques to forecast the quantity of waste collected by GPTs. …”
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Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption
Published 2015“…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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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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Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques
Published 2024“…To address these challenges, this project proposes an innovative solution that leverages computer vision and machine learning techniques. …”
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Selective opposition based constrained barnacle mating optimization: Theory and applications
Published 2024“…In addition to increasing efficiency by cutting down on wasted time spent exploring, this also increases the likelihood of stumbling onto optimal solutions. …”
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