Name
Abstract | ||
|---|---|---|
This research explores the capacity of Information Fusion to extract knowledge about associations among agricultural products, which allows prediction for future consumption in local markets in the Andean region of Ecuador. This commercial activity is performed using Alternative Marketing Circuits (CIALCO), seeking to establish a direct relationship between producer and consumer prices, and promote buying and selling among family groups. In the results we see that, information fusion from heterogenous data sources that are spatially located allows to establish best association rules among data sources (several products on several local markets) to infer significant improvement in time forecasting and spatial prediction accuracy for the future sales of agricultural products. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-92639-1_40 | HYBRID ARTIFICIAL INTELLIGENT SYSTEMS (HAIS 2018) |
Keywords | Field | DocType |
Data Fusion, Alternative circuits of commercialization, Associations mining, Predictive analysis | Producer–consumer problem,Spatial prediction,Computer science,Sensor fusion,Agriculture,Association rule learning,Artificial intelligence,Industrial organization,Information fusion,Machine learning | Conference |
Volume | ISSN | Citations |
10870 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Washington R. Padilla | 1 | 0 | 0.34 |
| Jesús García | 2 | 238 | 30.37 |
| José M. Molina | 3 | 604 | 67.82 |