Data Association Methodology to Improve Spatial Predictions in Alternative Marketing Circuits in Ecuador
Joint Authors
Padilla, Washington R.
García, Jesús
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-11-05
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
This work proposes a methodology that reduces the error of future estimations in commercialization based on multivariate spatial prediction techniques (cokriging) considering the products with strong associations.
It is based on the Apriori algorithm to find association rules in sales of agricultural products of local markets.
Results show the improvement in spatial prediction accuracy after using the best association rules.
American Psychological Association (APA)
Padilla, Washington R.& García, Jesús. 2018. Data Association Methodology to Improve Spatial Predictions in Alternative Marketing Circuits in Ecuador. Computational Intelligence and Neuroscience،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1130813
Modern Language Association (MLA)
Padilla, Washington R.& García, Jesús. Data Association Methodology to Improve Spatial Predictions in Alternative Marketing Circuits in Ecuador. Computational Intelligence and Neuroscience No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1130813
American Medical Association (AMA)
Padilla, Washington R.& García, Jesús. Data Association Methodology to Improve Spatial Predictions in Alternative Marketing Circuits in Ecuador. Computational Intelligence and Neuroscience. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1130813
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1130813