Jatinderkumar R. Saini

Work place: Narmada College of Computer Application, Bharuch, Gujarat, India

E-mail: saini_expert@yahoo.com


Research Interests: Applied computer science, Computational Science and Engineering, Computer systems and computational processes, Theoretical Computer Science


Dr. Jatinderkumar R. Saini is Ph.D. in Computer science and secured first rank in all three years of MCA in college and has been awarded gold medals for this. He is also a recipient of silver medal for B.Sc. (Computer Science). He is an IBM Certified Data Associate- DB2 as well as IBM certified Associate Developer- RAD. He has presented 14 papers in international and national conferences supported by agencies like IEEE, AICTE, IETE, ISTE, INNS etc. One of his papers has also won the ‘Best Paper Award’.9 of his papers have been accepted for publication at international level and 13 papers have been accepted for national level publication. He is a chairman of many academic committees. He is also a member of numerous national and international professional bodies and scientific research academies and organizations.

Dr. Saini is currently working as Professor & Incharge Director at Narmada College of Computer Application, Bharuch, Gujarat, India. He is also working as Director (Information Technology) at Gujarat Technological University's AB Innovation Sankul. Dr. Saini is working as Gujarat Technological University's Zonal Exam Coordinator for South Gujarat, India.  Formerly, he has worked as Associate Professor & Head of Department in MCA & Gujarat Technological University (GTU) Coordinator at Sankalchand Patel College of Engineering, Mehsana, Gujarat, India.

Author Articles
Estimation and Approximation Using Neuro-Fuzzy Systems

By Nidhi Arora Jatinderkumar R. Saini

DOI: https://doi.org/10.5815/ijisa.2016.06.02, Pub. Date: 8 Jun. 2016

Estimation and Approximation plays an important role in planning for future. People especially the business leaders, who understand the significance of estimation, practice it very often. The act of estimation or approximation involves analyzing historical data pertaining to domain, current trends and expectations of people connected to it. Exercising estimation is not only complicated due to technological change in the world around, but also due to complexity of the problems. Traditional numerical based techniques for solution of ill-defined non-linear real world problems are not sufficient. Hence, there is a need of some robust methodologies which can deal with dynamic environment, imprecise facts and uncertainty in the available data to achieve practical applicability at low cost. Soft computing seeks to solve class of problems not suited for traditional algorithmic approaches.
To address the common problems in business of inexactness, some models are put forward for servicing, support and monitoring by approximating and estimating important outcomes. This work illustrates some very general yet widespread problems which are of interest to common people. The suggested approaches can overcome the fuzziness in traditional methods by predicting some future events and getting better control on business. This includes study of various neuro-fuzzy architectures and their possible applications in various areas, where decision-making using classical methods fail.

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