Home > Engineering > Computer Engineering > Volume-3 > Issue-3 > Optimizing Multiple Object Tracking and Decision making using neuro–fuzzy

Optimizing Multiple Object Tracking and Decision making using neuro–fuzzy

Call for Papers

Volume-4 | Issue-5

Last date : 27-Aug-2020

Best International Journal
Open Access | Peer Reviewed | Best International Journal | Indexing & IF | 24*7 Support | Dedicated Qualified Team | Rapid Publication Process | International Editor, Reviewer Board | Attractive User Interface with Easy Navigation

Journal Type : Open Access

Processing Charges : 700/- INR Only OR 25 USD (for foreign users)

Paper Publish : Within 2-4 Days after submitting

Submit Paper Online

For Author

IJTSRD Publication

Research Area

Optimizing Multiple Object Tracking and Decision making using neuro–fuzzy

Chineke Amaechi Hyacenth


Chineke Amaechi Hyacenth "Optimizing Multiple Object Tracking and Decision making using neuro–fuzzy" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3, April 2019, pp.871-876, URL: https://www.ijtsrd.com/papers/ijtsrd23185.pdf

The problem of not tracking stolen items and some products that are not of quality standard in our companies and industries has liquidated some companies in our country. It has also made some of our graduates not to be employed. The tracking of a single object is difficult let alone tracking multiple object. This problem has arisen because intelligent agent was not incorporated in the design to enhance the efficiency of tracking multiple objects. This can be overcome by using Optimizing multiple object tracking and decision making using neuro –fuzzy. This is done by optimizing the parametric tracking values, designing membership functions for detecting when there is reduction in efficiency at each stage in the production, monitoring the machine temperature, speed, volume, quality and designing membership function for detecting component failure along the production line and its age deterioration coupled with staff behavior in the company. To train these membership designs to stick strictly to the rules of tracking multiple objects and designing a model for multiple object tracking using neuro-fuzzy. The result obtained is 20% better in tracking ability when compared to the conventional one like using optimization only.

multiple object tracking, neuro-fuzzy, optimization

Volume-3 | Issue-3, April 2019
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

Thomson Reuters
Google Scholer