Advanced search
Start date
Betweenand
Related content
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A survey of the applications of Bayesian networks in agriculture

Full text
Author(s):
Drury, Brett [1] ; Valverde-Rebaza, Jorge [1] ; Moura, Maria-Fernanda [2] ; Lopes, Alneu de Andrade [1]
Total Authors: 4
Affiliation:
[1] Univ Sao Paulo, ICMC, Ave Trabalhador Sao Carlense, 400, BR-13566590 Sao Carlos, SP - Brazil
[2] Embrapa Agr Informat, Ave Dr Andre Tosello, 209 Cidade Univ, Campinas, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE; v. 65, p. 29-42, OCT 2017.
Web of Science Citations: 14
Abstract

The application of machine learning to agriculture is currently experiencing a ``surge of interest{''} from the academic community as well as practitioners from industry. This increased attention has produced a number of differing approaches that use varying machine learning frameworks. It is arguable that Bayesian Networks are particularly suited to agricultural research due to their ability to reason with incomplete information and incorporate new information. Bayesian Networks are currently underrepresented in the machine learning applied to agriculture research literature, and to date there are no survey papers that currently centralize the state of the art. The aim of this paper is rectify the lack of a survey paper in this area by providing a self-contained resource that will: centralize the current state of the art, document the historical progression of Bayesian Networks in agriculture and indicate possible future lines of research as well as providing an introduction to Bayesian Networks for researchers who are new to the area. (C) 2017 Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 13/12191-5 - Mining User Behavior in Location-Based Social Networks
Grantee:Jorge Carlos Valverde Rebaza
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 11/20451-1 - Induction of Topic-Based Bayesian Networks from Text for the Prediction of Sugar Cane Yields
Grantee:Brett Mylo Drury
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 15/14228-9 - Social Network Analysis and Mining
Grantee:Alneu de Andrade Lopes
Support Opportunities: Regular Research Grants