A deep learning model to predict lower temperatures in agriculture-Reference-Cited by-同舟云学术

A deep learning model to predict lower temperatures in agriculture

Published:2020-01-27 Issue:1 Volume:12 Page:21-34
ISSN:1876-1372
Container-title:Journal of Ambient Intelligence and Smart Environments
language:
Short-container-title:AIS

Author:

Guillén-Navarro Miguel A.¹,Martínez-España Raquel¹,Llanes Antonio¹,Bueno-Crespo Andrés¹,Cecilia José M.¹

Affiliation:

1. Computer Science Department, Universidad Católica de Murcia, Murcia, Spain. E-mails: maguillen@ucam.edu, rmartinez@ucam.edu, allanes@ucam.edu, abueno@ucam.edu, jmcecilia@ucam.edu

Publisher

IOS Press

Subject

Software

Reference35 articles.

1. Convolution neural network in precision agriculture for plant image recognition and classification

2. K.A. Al-Gaadi, A.A. Hassaballa, E. Tola, A.G. Kayad, R. Madugundu, B. Alblewi and F. Assiri, Prediction of potato crop yield using precision agriculture techniques, PLoS ONE 11(9) (2016), e0162219.

3. Simulating the impact of extreme heat and frost events on wheat crop production: A review;Barlow;Field Crops Research,2015

4. Big data in precision agriculture: Weather forecasting for future farming

5. On the use of cross-validation for time series predictor evaluation;Bergmeir;Information Sciences,2012

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fuzzy automatic control of the irrigation process for the IoT-based smart farming systems;Journal of Ambient Intelligence and Smart Environments;2024-06-19

2. Incremental–decremental data transformation based ensemble deep learning model (IDT-eDL) for temperature prediction;Modeling Earth Systems and Environment;2024-02-26

3. An LSTM-Based Method for Automatic Reliability Prediction of Cognitive Radio Vehicular Ad Hoc Networks;SN Computer Science;2024-02-26

4. Day-ahead energy-mix proportion for the secure operation of renewable energy-dominated power system;International Journal of Electrical Power & Energy Systems;2024-01

5. A taxonomy for decision making in IoT systems;Internet of Things;2023-12