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Document Type : Latin Dissertation
Language of Document : English
Record Number : 150984
Doc. No : ET22776
Main Entry : PRAVEENRAO KALMADI
Title Proper : BUILDING AN AUTOMATIC TASK SCHEDULER USING GENETIC ALGORITHMS AND ARTIFICIAL NEURAL NETWORKS
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : In the modem world. where users send requests via the Internet requesting tasks tobe performed, efficient scheduling of those requests becomes a major concern. This thesisconcentrates on a robotic domain. The robot is working in an unpredictable environmentwhere in, the system must be able to handle requests arriving at a continuous rate andprovide an optimal schedule in real time.In this thesis, we describe a research project, which performs optimization ofrobotic task schedules using genetic algorithms. To estimate the task execution times. aset of training examples is collected by running a simulator. A neural network is thentrained using these collected examples. The output of the neural network is fed into thegenetic algorithm allowing it to get an estimate.,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL46002.pdf
Title and statement of responsibility and : BUILDING AN AUTOMATIC TASK SCHEDULER USING GENETIC ALGORITHMS AND ARTIFICIAL NEURAL NETWORKS [Thesis]
 
 
 
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