Employing long short-term memory and Facebook prophet model in air temperature forecasting-Reference-Cited by-同舟云学术

Employing long short-term memory and Facebook prophet model in air temperature forecasting

Published:2021-01-19 Issue: Volume: Page:1-24
ISSN:0361-0918
Container-title:Communications in Statistics - Simulation and Computation
language:en
Short-container-title:Communications in Statistics - Simulation and Computation

Author:

Toharudin Toni¹²,Pontoh Resa Septiani¹,Caraka Rezzy Eko²³⁴^ORCID,Zahroh Solichatus¹,Lee Youngjo²³^ORCID,Chen Rung Ching⁴^ORCID

Affiliation:

1. Department of Statistics, Faculty of Mathematics and Natural Science, Padjadjaran University, Indonesia

2. Department of Statistics, College of Natural Science, Seoul National University, Seoul metropolis, Republic of Korea

3. Research for Basic Sciences, Lab Hierarchical Likelihood, College of Natural Science, Seoul National University, Seoul Metropolis, Republic of Korea

4. Department of Information Management, College of Informatics, Chaoyang University of Technology, Taiwan (R.O.C.)

Funder

NATIONAL RESEARCH FOUNDATION KOREA

Department of Statistics Padjadjaran University

Publisher

Informa UK Limited

Subject

Modelling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610918.2020.1854302

Reference49 articles.

1. Sequence to Sequence Weather Forecasting with Long Short-Term Memory Recurrent Neural Networks

2. Error measures for generalizing about forecasting methods: Empirical comparisons

3. Learning long-term dependencies with gradient descent is difficult

4. Summary for Policymakers

5. Hybrid support vector regression in electric load during national holiday season

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