Search Results - (( java implementation path algorithm ) OR ( waste estimation 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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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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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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DeMI interface tool for profit estimation and waste conversion technology recommendations in enhancing municipal solid waste management
Published 2024“…The M5P algorithm, adept at profit estimation, establishes correlations between MSW weight and profitability, while the J48 algorithm offers recommendations for suitable waste conversion technologies based on profit potential. …”
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7
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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Prediction of biochemical oxygen demand in Mexican surface waters using machine learning / Maximiliano Guzmán-Fernández ... [et al.]
Published 2021“…Two groups were formed and used as input to four machine learning algorithms. Random forest algorithm obtained the best performance. …”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar
Published 2015“…The SLFN is trained by an algorithm named Extreme Learning Machine (ELM). The extracted features will be fed up into SLFN to classify the fault. …”
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Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar
Published 2015“…The SLFN is trained by an algorithm named Extreme Learning Machine (ELM). The extracted features will be fed up into SLFN to classify the fault. …”
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Student Project -
12
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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Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques
Published 2024“…Overfeeding due to imprecise population estimates leads to wasted resources and potential environmental issues. …”
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Final Year Project / Dissertation / Thesis -
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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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15
Prediction on the mechanical strength of coal ash concrete using artificial neural network
Published 2022“…The mechanical strength prediction based on machine learning is more exact, accurate, and dependable than the standard concrete strength estimate.…”
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