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

Biology

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