Improving Forecasting Using Information Fusion In Local Agricultural Markets

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

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.

Translated title of the contributionMejora de las previsiones mediante la fusión de información en los mercados agrícolas locales
Original languageEnglish (US)
Title of host publicationImproving Forecasting Using Information Fusion In Local Agricultural Markets
EditorsAlvaro Herrero, Hector Quintian, Jose Antonio Saez, Emilio Corchado, Francisco Javier de Cos Juez, Jose Ramon Villar, Enrique A. de la Cal
PublisherSpringer Verlag
Pages479-489
Number of pages11
ISBN (Print)978-3-319-92638-4
DOIs
StatePublished - 8 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10870 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Alternative circuits of commercialization
  • Associations mining
  • Data Fusion
  • Predictive analysis

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