A web-based fuzzy expert system for frost warnings in horticultural crops

Authors:
Robert F. Chevalier;Gerrit Hoogenboom;Ronald W. McClendon;Joel O. Paz
Affiliations:
Institute for Artificial Intelligence, the University of Georgia, Athens, GA 30602, United States;Institute for Artificial Intelligence, the University of Georgia, Athens, GA 30602, United States and Department of Biological and Agricultural Engineering, the University of Georgia, Griffin, GA ...;Institute for Artificial Intelligence, the University of Georgia, Athens, GA 30602, United States and Department of Biological and Agricultural Engineering, the University of Georgia, Athens, GA 3 ...;Department of Biological and Agricultural Engineering, the University of Georgia, Griffin, GA 30223, United States
Venue:
Environmental Modelling & Software
Year:
2012

Citing 10
Cited 3

A meteorological fuzzy expert system incorporating subjective user input

Knowledge and Information Systems
Development of an ENSO-based irrigation decision support tool for peanut production in the southeastern US

Computers and Electronics in Agriculture
A new approach to testing an integrated water systems model using qualitative scenarios

Environmental Modelling & Software
Linking science with environmental decision making: Experiences from an integrated modeling approach to supporting sustainable water resources management

Environmental Modelling & Software
ENSEMBLE ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF DEW POINT TEMPERATURE

Applied Artificial Intelligence
An integrated system for publishing environmental observations data

Environmental Modelling & Software
Artificial neural networks for automated year-round temperature prediction

Computers and Electronics in Agriculture
Generic integration of environmental decision support systems - state-of-the-art

Environmental Modelling & Software
Real-time, rapidly updating severe weather products for virtual globes

Computers & Geosciences
Support vector regression with reduced training sets for air temperature prediction: a comparison with artificial neural networks

Neural Computing and Applications

A genetic algorithm to refine input data selection for air temperature prediction using artificial neural networks

Applied Soft Computing
Position paper: Selecting among five common modelling approaches for integrated environmental assessment and management

Environmental Modelling & Software
Comparison of individual and combined ANN models for prediction of air and dew point temperature

Applied Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Frost damage is responsible for more economic losses than any other weather related phenomenon in the United States (USA) and many other regions across the globe. With sufficient warning, producers can minimize the potential damages caused by frost and freeze events. However, the severity of these events is dependent upon several factors including air temperature, dew point temperature, and wind speed. Methods for assessing this risk are not easily quantifiable and require the insight of experts familiar with the process. Georgia's Extreme-weather Neural-network Informed Expert (GENIE) incorporates the knowledge of expert agrometeorologists and additional information on air temperature, dew point temperature, and wind speed into a fuzzy expert system for use by Georgia producers to provide warning levels of frost and freeze for blueberries and peaches. Artificial neural network (ANN) predictions of air temperature and dew point temperature across the state of Georgia for one to 12 h ahead and observed wind speed are used as input variables for this fuzzy expert system. Meteorological conditions were classified into five levels of frost and freeze by the expert agrometeorologists. These expertly classified scenarios were then used to develop fuzzy logic rules and membership functions for GENIE. Additional scenarios were presented to GENIE for evaluation and it classified all scenarios correctly. This tool will be made available to Georgia producers through a web-based interface, which can be found at www.georgiaweather.net.