Search Results - (( variable case based algorithm ) OR ( java application optimisation algorithm ))
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1
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation
Published 2018“…This study presented the most recent variable interaction strength (VS) CT strategy using an enhanced variant in the greedy algorithm. …”
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Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems
Published 2017“…The statistical simulation results of this project proved that MFO is able to produce compromising solutions by yielding the lowest power loss and voltage deviation among other reviewed algorithms. It can reduce 19.01 % (IEEE 30-bus system with 13 control variables), 20.47 % (IEEE 30-bus system with 19 control variables), 50.76 % (IEEE 30-bus system with 25 control variables), 12.96 % (IEEE 57-bus system) and 12.37 % (IEEE 118-bus system) of power losses from base case losses of each test case.…”
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Research Report -
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Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm
Published 2007“…Then the algorithm gathers all the test cases based on the definition occurrence and def-use pair if they cover same definition occurrence of one variable but they don’t cover def-use pair of the same variable. …”
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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“…In order to identify the strength and weakness of these algorithms for MC/DC compliant test cases, this research proposes an experimental study involving four neighborhoods based meta-heuristic algorithms. …”
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CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm
Published 2019“…The result of applying Jaya algorithm in input-output based combinatorial testing is acceptable since it produces nearly optimum number of test cases in the satisfactory time range.…”
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Undergraduates Project Papers -
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A new variable strength t-way strategy based on the cuckoo search algorithm
Published 2019“…Despite much progress, existing strategies have not sufficiently dealt with more than one interaction between input parameters (termed variable strength tway). Complementing existing works, this paper proposes a new variable strength cuckoo search algorithm, called VCS. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Neural network based model predictive control for a steel pickling process
Published 2009“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm
Published 2019“…The result of applying the Jaya algorithm in input-output based combinatorial testing is acceptable since it produces a nearly optimum number of test cases in a satisfactory time range.…”
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A variable combinatorial test suite strategy based on modified greedy algorithm
Published 2015“…This proposed will suggest a new CIT strategy based on a modified greedy algorithm (MGA) with addressing the supporting of variable strength interaction to generate a satisfactory test suite size.…”
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Optimized clustering with modified K-means algorithm
Published 2021“…In dealing with correlated variables, PCA was embedded in the proposed algorithm. …”
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Fault diagnostic algorithm for precut fractionation column
Published 2004“…The fault diagnostic algorithm is supported by the process history based method and developed by using Borland C++ Builder 6.0. …”
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Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems
Published 2015“…The complicated task of design optimization of compact heat exchangers (CHEs) have been effectively performed by using evolutionary algorithms (EAs) in the recent years. However, mainly due to difficulties of handling extra variables, the design approach has been based on constant rates of heat duty in the available literature. …”
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Similarity distance measure and prioritization algorithm for test case prioritization in software product line testing
Published 2019“…Comparative study has been done between different string distance measures and prioritization algorithms to select the best techniques for similarity-based test case prioritization. …”
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Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
Published 2011“…Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. …”
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Dynamic Economic Dispatch For Power System
Published 2016“…The performance of the PSO-based developed algorithm was tested on simple case studies with a small number of generation units and limited constraints, and then on more complex case studies with a large number of variables and complicated constraints. …”
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Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory
Published 2015“…Mathematical models of the plants are first derived through the description of the manifest behavior by elimination of the latent variables via a systematic algorithm. Next, the algorithms for obtaining controllers using pole placement techniques are developed based on specified nominal control laws to retain all the desirable trajectories in the plant behavior while rejecting the undesirable ones. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…However, not all accepted metaheuristic algorithms are compatible with enhancing the ANN for streamflow forecasting, demanding a thorough analysis due to performance differences across cases. …”
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