Search Results - (( development team optimization algorithm ) OR ( java application clustering algorithm ))
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Some metaheuristic algorithms for solving multiple cross-functional team selection problems
Published 2022“…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…The prototypes will be developed using JAVA language united with a MySQL database. Core functionality of the simulator are job generation, volunteer generation, simulating algorithms, generating graphical charts and generating reports. …”
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Final Year Project -
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Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Final Year Project / Dissertation / Thesis -
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Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem
Published 2022“…Emperor Penguin Optimizer (EPO) is a recently developed population-based meta-heuristic algorithm that simulates the huddling behavior of emperor penguins. …”
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Shared mental model as an enabler of Malaysia waqf land development
Published 2017“…The adoption and adaption cycle was going so quickly along the waqf land development. 2.SMM also being interacted by other indirect team members. who involves in the WSA development 3. …”
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Development of optimized maintenance scheduling model for coal-fired power plant boiler
Published 2023“…The optimal schedules obtained were compared with the actual based on parameters and judgement from power plant planning team. …”
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A collaborative model for post flood activities exploiting an enhanced expanding neighborhood search algorithm
Published 2019“…The network performance (e.g., packet delivery ratio nearing 80-90%) also demonstrates the capability of CP-AGCM to provide ProSe in the post-flood scenarios and optimality of efficient search algorithm.…”
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Abnormalities detection in apert syndrome using hierarchical clustering algorithms
Published 2025“…This guidance has the potential to optimize surgical outcomes and reduce the risk of potential complications.…”
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An integrated model of automated elementary programming feedback using assisted and recommendation approach
Published 2017“…Meanwhile, similar difficulty groups of the computer programs were generated using a K-Means clustering algorithm that was enhanced with ranking consideration. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Developing best practice guidelines for oral cancer management in Malaysia / Aznilawati Abdul Aziz
Published 2017“…The draft version of the Malaysian guidelines comprised three sections (Section 1: Introduction, Section II: Development of the guidelines and Section III: eighty-eight clinical recommendations and summary of the evidence) and an algorithm of the whole process of oral cancer management. …”
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