Neural Networks for Food Export Gain Forecasting

Dmitry Devyatkin; Roman Suvorov; Ilya Tikhomirov; Yulia Otmakhova

doi:10.1109/IS.2018.8710561

Neural Networks for Food Export Gain Forecasting

Dmitry Devyatkin, Roman Suvorov, Ilya Tikhomirov, Yulia Otmakhova

Исследовательский центр продовольственной безопасности ЭФ

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › рецензирование

Аннотация

Agriculture and food production could be an engine of economic growth in a lot of countries. The obvious way to force food and agriculture development is to discover new foreign markets with high probability of growth in the nearest future. The objective of this study is to reveal combinations of commodities and partner countries for which persistent growth of export value is expected. The proposed framework uses open data about international trade flows and production from United Nations, International Monetary Found, weather databases and quantile regression models based on neural networks. The experiments show that considering retrospective data allows to accurate forecast the desired combinations.

Язык оригинала	английский
Название основной публикации	9th International Conference on Intelligent Systems 2018
Подзаголовок основной публикации	Theory, Research and Innovation in Applications, IS 2018 - Proceedings
Редакторы	Joao Martins, Vladimir Jotsov, Robert Bierwolf, Joao Pedro Mendonca, Ricardo Jardim-Goncalves, Maria Marques
Издатель	Institute of Electrical and Electronics Engineers Inc.
Страницы	312-317
Число страниц	6
ISBN (электронное издание)	9781538670972
DOI	https://doi.org/10.1109/IS.2018.8710561
Состояние	Опубликовано - 2 июл 2018
Событие	9th International Conference on Intelligent Systems, IS 2018 - Funchal - Madeira, Португалия Продолжительность: 25 сен 2018 → 27 сен 2018

Серия публикаций

Название	9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings

Конференция

Конференция	9th International Conference on Intelligent Systems, IS 2018
Страна	Португалия
Город	Funchal - Madeira
Период	25.09.2018 → 27.09.2018

Fingerprint

Цитировать

Devyatkin, D., Suvorov, R., Tikhomirov, I., & Otmakhova, Y. (2018). Neural Networks for Food Export Gain Forecasting. В J. Martins, V. Jotsov, R. Bierwolf, J. P. Mendonca, R. Jardim-Goncalves, & M. Marques (Ред.), 9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings (стр. 312-317). [8710561] (9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IS.2018.8710561

Devyatkin, Dmitry ; Suvorov, Roman ; Tikhomirov, Ilya ; Otmakhova, Yulia. / Neural Networks for Food Export Gain Forecasting. 9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings. редактор / Joao Martins ; Vladimir Jotsov ; Robert Bierwolf ; Joao Pedro Mendonca ; Ricardo Jardim-Goncalves ; Maria Marques. Institute of Electrical and Electronics Engineers Inc., 2018. стр. 312-317 (9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings).

@inproceedings{c09054d2d3454f2fbd0ece5b4eb39dcb,

title = "Neural Networks for Food Export Gain Forecasting",

abstract = "Agriculture and food production could be an engine of economic growth in a lot of countries. The obvious way to force food and agriculture development is to discover new foreign markets with high probability of growth in the nearest future. The objective of this study is to reveal combinations of commodities and partner countries for which persistent growth of export value is expected. The proposed framework uses open data about international trade flows and production from United Nations, International Monetary Found, weather databases and quantile regression models based on neural networks. The experiments show that considering retrospective data allows to accurate forecast the desired combinations.",

keywords = "Data mining, Food market, International trade, Machine learning, Neural networks, Open data, Quantile regression",

author = "Dmitry Devyatkin and Roman Suvorov and Ilya Tikhomirov and Yulia Otmakhova",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/IS.2018.8710561",

language = "English",

series = "9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "312--317",

editor = "Joao Martins and Vladimir Jotsov and Robert Bierwolf and Mendonca, {Joao Pedro} and Ricardo Jardim-Goncalves and Maria Marques",

booktitle = "9th International Conference on Intelligent Systems 2018",

address = "United States",

note = "9th International Conference on Intelligent Systems, IS 2018 ; Conference date: 25-09-2018 Through 27-09-2018",

}

Devyatkin, D, Suvorov, R, Tikhomirov, I & Otmakhova, Y 2018, Neural Networks for Food Export Gain Forecasting. в J Martins, V Jotsov, R Bierwolf, JP Mendonca, R Jardim-Goncalves & M Marques (ред.), 9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings., 8710561, 9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., стр. 312-317, 9th International Conference on Intelligent Systems, IS 2018, Funchal - Madeira, Португалия, 25.09.2018. https://doi.org/10.1109/IS.2018.8710561

Neural Networks for Food Export Gain Forecasting. / Devyatkin, Dmitry; Suvorov, Roman; Tikhomirov, Ilya; Otmakhova, Yulia.

9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings. ред. / Joao Martins; Vladimir Jotsov; Robert Bierwolf; Joao Pedro Mendonca; Ricardo Jardim-Goncalves; Maria Marques. Institute of Electrical and Electronics Engineers Inc., 2018. стр. 312-317 8710561 (9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings).

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › рецензирование

TY - GEN

T1 - Neural Networks for Food Export Gain Forecasting

AU - Devyatkin, Dmitry

AU - Suvorov, Roman

AU - Tikhomirov, Ilya

AU - Otmakhova, Yulia

PY - 2018/7/2

Y1 - 2018/7/2

N2 - Agriculture and food production could be an engine of economic growth in a lot of countries. The obvious way to force food and agriculture development is to discover new foreign markets with high probability of growth in the nearest future. The objective of this study is to reveal combinations of commodities and partner countries for which persistent growth of export value is expected. The proposed framework uses open data about international trade flows and production from United Nations, International Monetary Found, weather databases and quantile regression models based on neural networks. The experiments show that considering retrospective data allows to accurate forecast the desired combinations.

AB - Agriculture and food production could be an engine of economic growth in a lot of countries. The obvious way to force food and agriculture development is to discover new foreign markets with high probability of growth in the nearest future. The objective of this study is to reveal combinations of commodities and partner countries for which persistent growth of export value is expected. The proposed framework uses open data about international trade flows and production from United Nations, International Monetary Found, weather databases and quantile regression models based on neural networks. The experiments show that considering retrospective data allows to accurate forecast the desired combinations.

KW - Data mining

KW - Food market

KW - International trade

KW - Machine learning

KW - Neural networks

KW - Open data

KW - Quantile regression

UR - http://www.scopus.com/inward/record.url?scp=85065967127&partnerID=8YFLogxK

U2 - 10.1109/IS.2018.8710561

DO - 10.1109/IS.2018.8710561

M3 - Conference contribution

AN - SCOPUS:85065967127

T3 - 9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings

SP - 312

EP - 317

BT - 9th International Conference on Intelligent Systems 2018

A2 - Martins, Joao

A2 - Jotsov, Vladimir

A2 - Bierwolf, Robert

A2 - Mendonca, Joao Pedro

A2 - Jardim-Goncalves, Ricardo

A2 - Marques, Maria

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 9th International Conference on Intelligent Systems, IS 2018

Y2 - 25 September 2018 through 27 September 2018

ER -

Devyatkin D, Suvorov R, Tikhomirov I, Otmakhova Y. Neural Networks for Food Export Gain Forecasting. В Martins J, Jotsov V, Bierwolf R, Mendonca JP, Jardim-Goncalves R, Marques M, редакторы, 9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. стр. 312-317. 8710561. (9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings). https://doi.org/10.1109/IS.2018.8710561

Доступ к документу

10.1109/IS.2018.8710561

Link to publication in Scopus