Search Results - (( its application _ algorithm ) OR ( job application ((mining algorithm) OR (means algorithm)) ))*

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    Cycle time minimization in production line using robust hybrid optimization algorithm by Noorazliza, Sulaiman, Zetty Ain, Kamaruzzaman, Junita, Mohamad Saleh, Ahmad Afif, Ahmarofi

    Published 2021
    “…This project proposes the application of new hybrid optimization algorithm named JAABC5-RRO to minimize cycle time to produce a new audio product on a production line in a production company.…”
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    Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems by Talebpour, Faraz

    Published 2016
    “…It will also result in increasing the number of iteration required to estimate the channel values In the proposed schemes, the problem of channel estimation accuracy for an adaptive algorithm named “least mean square algorithm” (LMS) with one feedback is avoided via a two feedback scheme. …”
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    Thesis
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    Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

    Published 2006
    “…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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    Article
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    A New Model for Trojan Detection using Machine Learning Inspired by Al-Furqan Verse by Madihah Mohd Saudi, Areej Mustafa Abuzaid, Masrur Ibrahim

    Published 2024
    “…Moreover, the knowledge discovery techniques (KDD) and the data mining algorithm were used to optimize the accuracy result. …”
    Article
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    Multi objective bee colony optimization framework for grid job scheduling by Alyaseri, Sana, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources.…”
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    Data Mining On Machine Breakdowns And Effectiveness Of Scheduled Maintenance by Tan, Su Sze

    Published 2019
    “…This provides a large corpus of information retrievable for data mining and knowledge discovery. The case study is focused on the investigation of machine breakdown and the effectiveness of scheduled maintenance with the application of data mining. …”
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    Monograph
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    Survey on job scheduling mechanisms in grid environment by S. M., Argungu, Che Mohamed Arif, Ahmad Suki, Omar, Mohd Hasbullah

    Published 2015
    “…Grid systems provide geographically distributed resources for both computational intensive and data-intensive applications.These applications generate large data sets.However, the high latency imposed by the underlying technologies; upon which the grid system is built (such as the Internet and WWW), induced impediment in the effective access to such huge and widely distributed data.To minimize this impediment, jobs need to be scheduled across grid environments to achieve efficient data access.Scheduling multiple data requests submitted by grid users onto the grid environment is NP-hard.Thus, there is no best scheduling algorithm that cuts across all grids computing environments.Job scheduling is one of the key research area in grid computing.In the recent past many researchers have proposed different mechanisms to help scheduling of user jobs in grid systems.Some characteristic features of the grid components; such as machines types and nature of jobs at hand means that a choice needs to be made for an appropriate scheduling algorithm to march a given grid environment.The aim of scheduling is to achieve maximum possible system throughput and to match the application needs with the available computing resources.This paper is motivated by the need to explore the various job scheduling techniques alongside their area of implementation.The paper will systematically analyze the strengths and weaknesses of some selected approaches in the area of grid jobs scheduling.This helps researchers better understand the concept of scheduling, and can contribute in developing more efficient and practical scheduling algorithms.This will also benefit interested researchers to carry out further work in this dynamic research area.…”
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    Article
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    Checkpointing in selected most fitted resource task scheduling in grid computing by Latip, Rohaya, Lew, Wai San, Chanchary, Fara Habib

    Published 2012
    “…Results show that with MeanFailureCP-SMF has reduce the average execution time (AET) compare to the current SMF and MeanFailure Algorithm.…”
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    A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem by Lee, Lai Soon, Nazif, Habibeh

    Published 2009
    “…Hence when setup time is small more batches are formed which means fewer jobs are to be processed per batch.The proposed OCGA effectively solve the problem with better solution quality compared to other local search methods. …”
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