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dc.contributor.authorJain, Abhishek
dc.date.accessioned2014-03-03T21:06:13Z
dc.date.available2014-03-03T21:06:13Z
dc.date.issued2003-12
dc.identifier.otherjain_abhishek_200312_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/jain_abhishek_200312_ms
dc.identifier.urihttp://hdl.handle.net/10724/21300
dc.description.abstractOne of the most important factors in crop growth is weather, therefore, weather forecasting is vital for agricultural production decision making. For crops such as peaches and blueberries, low temperatures during the bloom period can result in crop damage. Thus frost forecasts are important to provide a warning to farmers, who can then take appropriate actions to minimize damage to their crop. However there are no local short-term frost forecasting systems available at the moment. The complex and non-linear nature of the relationships between various meteorological factors cannot be easily modeled. The goal of this research was to develop a decision support system using Artificial Neural Networks (ANNs) to forecast temperatures in hourly increments from one to twelve hours for any location in south Georgia region, for which, current weather data was available.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectArtificial Neural Networks
dc.subjectFrost Prediction
dc.subjectTemperature Forecast
dc.subjectAir Temperature
dc.subjectWeather Data Network
dc.subjectDecision Support System
dc.titlePredicting air temperature for frost warning using Artificial Neural Networks
dc.typeThesis
dc.description.degreeMS
dc.description.departmentArtificial Intelligence
dc.description.majorArtificial Intelligence
dc.description.advisorR. W. McClendon
dc.description.committeeR. W. McClendon
dc.description.committeeG. Hoogenboom
dc.description.committeeK. M. Rasheed


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