A Complementary Review on Various Artificial Intelligence Techniques

Authors(2) :-V. Ramesh, G Raju

Since scheduling process is a very important and complex method, several programmers are searching and working on this issue for years. Still, several researchers within the educational institutes try to seek out the simplest resolution. As time is cash, time improvement is that the most significant purpose, that makes the researchers develop a system for programming in the simplest manner by applying the simplest resolution. Once inspect the assembly line of a works or a number of categories and lecture rooms in a university, shows that having a plan in these places not solely helps regulate things, however conjointly it helps optimize consumption of resources like time and energy among the constraints and limitations. This paper explains and reviews the three techniques that have antecedently been applied to programming domain by researchers and developers among many artificial intelligence techniques. These various techniques i.e. genetic formula, Neural Network and fuzzy logic are outlined, mentioned and compared in terms of some measures.

Authors and Affiliations

V. Ramesh
Assistent Professor CSE, Sri Indu College of Engineering And Technology, Hyderabad, Telangan, India
G Raju
Assistent Professor CSE, Vaagdevi College of Engineering, Hyderabad, Telangan, India

Artificial Intelligence; Scheduling Problem; Genetic Algorithm; Neural Network, Fuzzy logic;

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Publication Details

Published in : Volume 2 | Issue 1 | January-February 2017
Date of Publication : 2017-02-27
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 276-284
Manuscript Number : CSEIT172693
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

V. Ramesh, G Raju, "A Complementary Review on Various Artificial Intelligence Techniques", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 1, pp.276-284, January-February-2017.
Journal URL : http://ijsrcseit.com/CSEIT172693

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