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Optimizing Multiple Object Tracking and Decision making using neuro–fuzzy

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Optimizing Multiple Object Tracking and Decision making using neuro–fuzzy


Chineke Amaechi Hyacenth

https://doi.org/10.31142/ijtsrd23185



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


IJTSRD23185
Volume-3 | Issue-3, April 2019
871-876
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)

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