This page uses JavaScript and requires a JavaScript enabled browser.Your browser is not JavaScript enabled.
This page uses JavaScript and requires a JavaScript enabled browser.Your browser is not JavaScript enabled.
دانشگاه آزاد اسلامی اصفهان(خوراسگان)
منو
درگاههای جستجو
مدارک
جستجوی پیشرفته
مرور
جستجو در سایر کتابخانه ها
مستندات
جستجوی پیشرفته
مرور
منابع دیجیتال
تمام متن
اصطلاحنامه
درختواره
پرسش و پاسخ
سوالات متداول
پرسش از کتابدار
پیگیری پرسش
ورود
ثبت نام
راهنما
خطا
رکورد قبلی
رکورد بعدی
"
BUILDING AN AUTOMATIC TASK SCHEDULER USING GENETIC ALGORITHMS AND ARTIFICIAL NEURAL NETWORKS
"
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]
http://localhost/site/catalogue/150984
آدرس ثابت
پیوستها
عنوان :
نام فایل :
نوع عام محتوا :
نوع ماده :
فرمت :
سایز :
عرض :
طول :
TL46002.pdf
TL46002.pdf
پایان نامه لاتین
متن
application/octet-stream
2.72 MB
85
85
نمایش
نظرسنجی