Name
Title | ||
|---|---|---|
Applying Machine Learning to Extract New Knowledge in Precision Agriculture Applications |
Abstract | ||
|---|---|---|
We are considering a facet of precision agriculture that concentrates on plant-driven crop management. By monitoring soil, crop and climate in a field and providing a decision support system that is able to learn, it is possible to deliver treatments, such as irrigation, fertilizer and pesticide application, for specific parts of a field in real time and proactively. In this context, we have applied machine learning techniques to automatically extract new knowledge in the form of generalized decision rules towards the best administration of natural resources like water. The machine learning application model suggested in this paper is based on an inductive and iterative process of discovering knowledge on the basis of which, patterns and associations having arisen initially are re-examined to expand the pre-existing knowledge. The result of this study was the creation of an effective set of decision rules used to predict the plants' state and the prevention of unpleasant impacts from the water stress in plants. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/PCI.2008.30 | Panhellenic Conference on Informatics |
Keywords | Field | DocType |
decision support system,pre-existing knowledge,new knowledge,pesticide application,extract new knowledge,best administration,water stress,decision rule,application model,plant-driven crop management,machine learning,precision agriculture applications,generalized decision rule,knowledge discovery,natural resources,agriculture,crops,process model,iterative methods,heating,precision agriculture,natural resource,iterative process,learning artificial intelligence,classification algorithms,agricultural engineering,knowledge extraction,decision rules,data mining,data models | Decision rule,Data modeling,Data mining,Iterative and incremental development,Computer science,Decision support system,Precision agriculture,Natural resource,Knowledge extraction,Artificial intelligence,Statistical classification,Machine learning | Conference |
ISBN | Citations | PageRank |
978-0-7695-3323-0 | 3 | 0.65 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Savvas Dimitriadis | 1 | 3 | 0.65 |
| Christos Goumopoulos | 2 | 104 | 18.60 |