Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Juan D. Borrero"'
Publikováno v:
Stats, Vol 5, Iss 4, Pp 1145-1158 (2022)
Accurate time series prediction techniques are becoming fundamental to modern decision support systems. As massive data processing develops in its practicality, machine learning (ML) techniques applied to time series can automate and improve predicti
Externí odkaz:
https://doaj.org/article/6ce67ab0479743e9b7e918ac4c732947
Autor:
Juan D. Borrero, Jesus Mariscal
Publikováno v:
Algorithms, Vol 16, Iss 9, p 423 (2023)
Efforts across diverse domains like economics, energy, and agronomy have focused on developing predictive models for time series data. A spectrum of techniques, spanning from elementary linear models to intricate neural networks and machine learning
Externí odkaz:
https://doaj.org/article/d27d6e36d6f8437a8864094fab87628e
Publikováno v:
Horticulturae, Vol 9, Iss 5, p 549 (2023)
This study presents a novel hybrid model that combines two different algorithms to increase the accuracy of short-term berry yield prediction using only previous yield data. The model integrates both autoregressive integrated moving average (ARIMA) w
Externí odkaz:
https://doaj.org/article/da7b60242e78482583e9d84c6799c230
Publikováno v:
Mathematics, Vol 11, Iss 1, p 145 (2022)
Achieving sustainable economic development is always considered one of the main economic goals of countries. Therefore, researchers are interested in presenting new econometric models for more accurate identification of factors affecting economic gro
Externí odkaz:
https://doaj.org/article/62bf21c5512a49a89c8e05901e57f354
Autor:
Juan D. Borrero, Jesus Mariscal
Publikováno v:
Mathematics, Vol 10, Iss 16, p 2915 (2022)
Time series forecasting is one of the main venues followed by researchers in all areas. For this reason, we develop a new Kalman filter approach, which we call the alternative Kalman filter. The search conditions associated with the standard deviatio
Externí odkaz:
https://doaj.org/article/a8b25df1cebf4cc999be2e9597ecaf46
Autor:
Juan D. Borrero, Jesús Mariscal
Publikováno v:
Agriculture, Vol 12, Iss 6, p 767 (2022)
New players are entering the new and important digital data market for agriculture, increasing power asymmetries and reinforcing their competitive advantages. Although the farmer remains at the heart of agricultural data collection, to date, only a f
Externí odkaz:
https://doaj.org/article/c08019af2f674aacb99edd52edf09f15
Autor:
Juan D. Borrero, Jesus Mariscal
Publikováno v:
Mathematics, Vol 9, Iss 23, p 3034 (2021)
In this work, we attempted to find a non-linear dependency in the time series of strawberry production in Huelva (Spain) using a procedure based on metric tests measuring chaos. This study aims to develop a novel method for yield prediction. To do th
Externí odkaz:
https://doaj.org/article/30be8d5f1d214a1ca0aceb85c426a9eb
Autor:
Juan D. Borrero
Publikováno v:
Inventions, Vol 6, Iss 4, p 68 (2021)
Climate and social changes are deeply affecting current agro-food systems. Unsustainable agricultural practices and the low profitability of small farmers are challenging the agricultural development of rural areas. This study aims to develop a novel
Externí odkaz:
https://doaj.org/article/a7d5c731c8024998b22c423bca0ca525
Autor:
Juan D. Borrero
Publikováno v:
Revista Iberoamericana de Economía Solidaria e Innovación Socioecológica, Vol 1 (2018)
A pesar de la rápida expansión de la investigación sobre el espíritu empresarial de las mujeres, todavía escasean los estudios que exploren la intersección o simultaneidad entre género y país en desarrollo. El ambiente empresarial es fundamen
Externí odkaz:
https://doaj.org/article/cf8de64042ef4affb5726a832384755e
Autor:
Juan D. Borrero, Alberto Zabalo
Publikováno v:
Agronomy, Vol 11, Iss 4, p 809 (2021)
Data are currently characterized as the world’s most valuable resource and agriculture is responding to this global trend. The challenge in that particular field of study is to create a Digital Agriculture that help the agri-food sector grow in a f
Externí odkaz:
https://doaj.org/article/cfc1da11093044dcbe477d4eb3ece74f