Search Results - (( developing policy evolution algorithm ) OR ( java optimization techniques algorithm ))
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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia
Published 2024“…Principle component analysis was used to determine which predictors were most reliable. Hybrid model development included the optimization of ANN coefficients (its weights and biases) using adaptive guided differential evolution algorithm. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Hybrid genetic algorithm for improving fault localization
Published 2018“…Genetic algorithm (GA) is well known in finding an optimal solution to a problem while local search is capable of removing duplication. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Scalable approach for mining association rules from structured XML data
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Conference or Workshop Item -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Improving Class Timetabling using Genetic Algorithm
Published 2006“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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An enhancement of multi-factor weighted approach technique in prioritizing test cases by comparing similarity distance
Published 2025“…Therefore, numerous factors and techniques have been used to optimize the prioritization process. …”
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Proposed algorithm for scheduling in computational grid using backfilling and optimization techniques
Published 2016“…To allocate the suitable resources for the incoming jobs, a scheduling algorithm has to manage this process.In this paper, we provide a critical review the recent mechanisms in “grid computing” environment.In addition, we propose a new scheduling algorithm to minimize the delay for the end user, Gap Filling policy will be applied to improve the performance of the priority algorithm.Then, an optimization algorithm will perform in order to further enhance the initial result for that obtained from backfilling mechanism.The main aim of the proposed scheduling mechanism is to improve the QoS for the end user in a real grid computing environment.…”
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Agro-ento bioinformation: towards the edge of reality
Published 2002“…The protocols range from the molecular levels to domains of larger dimensions such as those encompassing fraternities of politics and policies, and societal applications. These protocols, algorithms, and visualisations undergo dynamic incubation processes to produce the end product, which is bioinformation. …”
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Conclusion
Published 2019“…The first six chapters of the book provide the fundamental details of the authentication technologies.The objective of Chapters 7 to 11 is to develop fast and secure algorithms for resource-constrained IoT and cloud computing, while the aim of Chapter 12 is to protect the data by laws and policies. …”
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Book Chapter -
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Autonomous formation flight control of multiple UAVs with motion capture system
Published 2013“…If the leader were nonfunctional, the whole system will be nonfunctional. There is no policy of algorithm were by the leader's task can be pass to other quad-rotor UAV. …”
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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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