Search Results - (( job application bees algorithm ) OR ( wave optimization sensor algorithm ))
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Multi objective bee colony optimization framework for grid job scheduling
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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Bee foraging behaviour techniques for grid scheduling problem
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.These resources are collected together to make a huge computing power.Job scheduling problem is one of the key issues in grid computing and failing to look into grid scheduling results in uncompleted view of the grid computing.Achieving optimized performance of grid system, and matching application requirements with available computing resources, are the objectives of grid job scheduling.Bee colony approaches are more adaptive to grid scheduling due to high heterogeneous and dynamic nature of resources and applications in grid.These algorithms have shown encouraging results in terms of time and cost.This paper presents some resent research activities inspired by bee foraging behavior for grid job scheduling especially ABC and BCO approaches.Different original studies related to this area are briefly described along with their comparisons against them and results.The review summary of their derived algorithms and research efforts is done.…”
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A miniature stub-loaded antenna optimized at VHF band for FSR sensor application / Hasrul Hisyam Harun
Published 2014“…This article demonstrated a miniature monopole antenna optimization at VHF band (30-300MHz) for FSR sensor application. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…The results obtained in these experiments would provide some overview in deploying machine learning algorithm for characterizing the Brillouin-based fibre sensor signals.…”
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Efficient and scalable ant colony optimization based WSN routing protocol for IoT
Published 2020“…For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. …”
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Optimisation of energy efficient hybrid flowshop scheduling problem using firefly algorithm
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Feasibility study on utilization of stub loaded miniature monopole antenna for forwards scattering micro-radar (FSR) network project: article / Hamid Salim
Published 2013“…The result obtained from both execution of Genetic Algorithm (GA) optimization and Parameter Sweep analysisis presented and conclude by future work recommendations for the continuity of this research.…”
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Feasibility study on utilization of stub loaded miniature monopole antenna for forwards scattering micro-radar (FSR) network project / Hamid Salim
Published 2013“…The result obtained from both execution of Genetic Algorithm (GA) optimization and Parameter Sweep analysisis presented and conclude by future work recommendations for the continuity of this research.…”
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Bayesian Network Classifiers for Damage Detection in Engineering Material
Published 2007“…To validate the classi¯ers and the proposed algorithm, two data sets were used, the ¯rst set represents voltage amplitudes of Lamb-waves produced and col- lected by sensors and actuators mounted on the surface of laminates contain di®erent arti¯cial damages. …”
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