Tea is one of the major health drinks of our society. It is a perennial crop in India and other countries. One of the production barriers of tea is insect pests. This paper presents an automatic diagnosis system for detecting tea insect pests based on artificial neural networks. We apply correlation-based feature selection (CFS) and incremental back propagation network (IBPLN). This is applied on a new database created by the authors based on the records of tea gardens of North Bengal Districts of India. We compare classification results with reduction of dimension and without reduction of dimension. The correct classification rate of the proposed system is 100% in both the cases.
Comments: 13 Pages.
[v1] 2012-08-19 00:16:35
Unique-IP document downloads: 770 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.