Search Results - (( java implementation path algorithm ) OR ( _ implementation case algorithm ))
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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Thesis -
2
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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3
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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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…Late Acceptance Hill Climbing (LAHC) and the Great Deluge Algorithm (GDA) which are our new implementation, Simulated Annealing (SA) and Hill Climbing (HC) are re-implemented to generate test cases satisfying MC/DC criterion for comparative analysis. …”
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7
Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…Within the GA, nearest neighbor algorithm is used in determining the most similar recorded case that can be used in solving the new case. …”
Conference paper -
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A study of fluctuations in genetic algorithm optimized network in data centre
Published 2017“…The reliability of genetic algorithm may vary based on implementation case, hence it is necessary to investigate its performance pattern for each implementation case. …”
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A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre
Published 2018“…The reliability of genetic algorithm may vary based on implementation case, hence it is necessary to investigate its performance pattern for each implementation case. …”
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A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre
Published 2018“…The reliability of genetic algorithm may vary based on implementation case, hence it is necessary to investigate its performance pattern for each implementation case. …”
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PID control system implementation in embedded system for DC motor speed control
Published 2008“…The result shows that, implementation of PID algorithm in small scale MCU is possible. …”
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Undergraduates Project Papers -
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An improved algorithm in test case generation from UML activity diagram using activity path
Published 2011“…This paper proposed an improved algorithm to automatically generate test cases directly from UML activity diagram using an activity graph.This algorithm has been implemented as a prototype using UML activity diagrams as inputs to generate test cases.These generated test cases are generated automatically are compared to test cases that are generated manually in order to evaluate the algorithm’s usability and reliability.The result shows that the test cases generated by the developed test case generator program are the same as the one manually derived.…”
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Construction of prioritized t-way test suite using Bi-objective Dragonfly Algorithm
Published 2022“…We have designed and implemented a Bi-objective Dragonfly Algorithm (BDA) for prioritized t-way test suite generation, and the two objectives are test case weight and test case priority. …”
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…However, in many cases, implementing the suitable hybrid algorithms for a given optimization problem is a considerably difficult, which in most cases, is time consuming. …”
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15
A comparative study on ant-colony algorithm and genetic algorithm for mobile robot planning.
Published 2024“…Results indicates that ACO outperforms GA in minimizing travel distance, establishing it as the superior routing algorithm for both case studies. Case study 1, the ACO algorithm achieved a best distance of 1036 (u) with execution time 1.67 (s), while the GA algorithm resulted in a best distance 1062 (u) with execution time 0.08 (s). …”
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Conference or Workshop Item -
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Implementing case-based reasoning approach to framework documentation
Published 2023“…In CBR, reasoning is based on remembering past cases. Genetic algorithm (GA) is used in implementing the CBR's "retrieve", "reuse", and "revise" steps. …”
Conference paper -
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IMPLEMENTATION OF GRAPH BASED PATH PLANNING ALGORITHMS FOR INDOOR NAVIGATION
Published 2018“…Also, to observe the advantages and disadvantages of these four path planning algorithms. In this case, we are splitting the project task into two parts, one of which is to implement the four algorithms on a small mobile robot, which will traverse within an indoor environment. …”
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Final Year Project -
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Similarity distance measure and prioritization algorithm for test case prioritization in software product line testing
Published 2019“…Identified enhancements have been implemented to both techniques for a better adoption of prioritizing SPL test cases. …”
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Manufacturing process planning optimisation in reconfigurable multiple parts flow lines
Published 2008“…Design/methodology/approach: The genetic algorithm methodology implements a genetic algorithm that is augmented by application specific heuristics in order to guide the search for an optimal solution. …”
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