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.
|Title of host publication||Hybrid Artificial Intelligent Systems - 13th International Conference, HAIS 2018, Proceedings|
|Editors||Alvaro Herrero, Hector Quintian, Jose Antonio Saez, Emilio Corchado, Francisco Javier de Cos Juez, Jose Ramon Villar, Enrique A. de la Cal|
|Number of pages||11|
|State||Published - 2018|
|Event||13th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2018 - Oviedo, Spain|
Duration: 20 Jun 2018 → 22 Jun 2018
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||13th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2018|
|Period||20/06/18 → 22/06/18|
Bibliographical noteFunding Information:
Acknowledgements. This work was supported in part by Project MINECO TEC2017-88048-C2-2-R and by Commercial Coordination Network, Ministry of Agriculture, Livestock, Aquaculture and Fisheries Ecuador.
© Springer International Publishing AG, part of Springer Nature 2018.
- Alternative circuits of commercialization
- Associations mining
- Data Fusion
- Predictive analysis