Remote sensing in decision support systems: Using fuzzy post adjustment in localisation of weed prediction

被引：3

作者：

Chiou, Andrew ^{[1
]}

Yu, Xinghuo ^{[2
]}

机构：

[1] Univ Cent Queensland, Sch Comp Sci, Rockhampton, Qld 4702, Australia

[2] RMIT Univ, Sch Elect & Comp Engn, Melbourne, Vic 3001, Australia

来源：

PROCEEDINGS OF THE 2007 INTERNATIONAL CONFERENCE ON INTELLIGENT SENSORS, SENSOR NETWORKS AND INFORMATION PROCESSING | 2007年

关键词：

D O I：

10.1109/ISSNIP.2007.4496899

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper explores the post adjustment of input data from a remote source to fit localised weed prediction for the control and management of weed infestation. The deployment of decision support systems in agricultural sectors often require refinement of its results to adapt to data that has been acquired externally via remote sensing. This paper will detail the fuzzy meta-consequent functions to facilitate the post adjustment. A case study is presented to demonstrate the workability of such fuzzy post-adjustment in the prediction of weed infestation.

引用

页码：533 / +

页数：2

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