Scheda di dettaglio – i prodotti della ricerca
| Dato | Valore |
|---|---|
| Title | Data Mining in the development of predictive models for the integrated management of sustainable agriculture |
| Abstract | Starting from the literature concerning applications of Data Mining (DM) for the integrated management of environmental information, in the present work an application path referred to the smart use of spatial data is traced to encourage the adoption of sustainable practices in agriculture, overcoming the limitations to the productivity related to biological agriculture. In particular, this work focuses its attention on the class of DM algorithms called "supervised algorithms" addressed to the clustering of the cultivated area of farms, illustrating its potentiality to define the typical decision making of management and planning of interventions. This approach is particularly significant for the integrated management of regionalized and environmental data to the topographical and soil features of the area that we want to model and to the physical-chemical nature of soil, to the kind of cultivation used, to the availability and quality of the water, as well as economic and socio-economic aspects. |
| Source | Italian journal of agrometeorology 16 (2), pp. 42–47 |
| Keywords | Agrometeorological systemsPrecision FarmingPredictive modelsData MiningSpatial Clustering |
| Journal | Italian journal of agrometeorology |
| Editor | AIM : Milano, [poi] Patron Granarolo dell'Emilia, Bologna, Italia |
| Year | 2011 |
| Type | Articolo in rivista |
| Authors | D'Arpa, Stefania; Barca, Emanuele; Uricchio, Vito Felice |
| Text | 298556 2011 ISI Web of Science WOS 000208680800007 Agrometeorological systems Precision Farming Predictive models Data Mining Spatial Clustering Data Mining in the development of predictive models for the integrated management of sustainable agriculture D Arpa, Stefania; Barca, Emanuele; Uricchio, Vito Felice Consiglio Nazionale delle Ricerche CNR Starting from the literature concerning applications of Data Mining DM for the integrated management of environmental information, in the present work an application path referred to the smart use of spatial data is traced to encourage the adoption of sustainable practices in agriculture, overcoming the limitations to the productivity related to biological agriculture. In particular, this work focuses its attention on the class of DM algorithms called supervised algorithms addressed to the clustering of the cultivated area of farms, illustrating its potentiality to define the typical decision making of management and planning of interventions. This approach is particularly significant for the integrated management of regionalized and environmental data to the topographical and soil features of the area that we want to model and to the physical chemical nature of soil, to the kind of cultivation used, to the availability and quality of the water, as well as economic and socio economic aspects. 16 Articolo in rivista AIM Milano 2038 5625 Italian journal of agrometeorology Italian journal of agrometeorology Italian journal of agrometeorology. Ital. j. agrometeorol. Rivista italiana di agrometeorologia emanuele.barca BARCA EMANUELE |