Estimation of global natural gas spot prices using big data and symbolic regression

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F24%3A10255198" target="_blank" >RIV/61989100:27740/24:10255198 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0301420724005117?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0301420724005117?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.resourpol.2024.105144" target="_blank" >10.1016/j.resourpol.2024.105144</a>

Result language

angličtina

Original language name

Estimation of global natural gas spot prices using big data and symbolic regression

Original language description

This article provides an estimation of future natural gas spot prices on the global international market based on symbolic regression where the sensitivity analysis is performed to identify the most important input parameters. Numerical data sets, comprising various parameters, some of which demonstrate stronger correlations with the global spot price of natural gas, are utilised in this context. PySR (Python Symbolic Regression), a free and open-source software for symbolic regression written in Python, and Julia is used for the presented analysis. Based on the accuracy of the prediction and after sensitivity analysis performed in SALib software, some of the parameters are discovered to be more influencing on natural gas prices compared with others, making this approach suitable for further deeper energy analysis. The analysis shows that in general, global prices of natural gas are influenced mostly by the price of crude oil. The article also presents an overview of methods for predicting natural gas prices with a complementary contribution (interpretable models provided by symbolic regression and sensitivity analysis) tested on the real gas price time-series dataset. (C) 2024 Elsevier Ltd

Czech name

—

Czech description

—

Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

—

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Resources Policy

ISSN

0301-4207

e-ISSN

—

Volume of the periodical

95

Issue of the periodical within the volume

August

Country of publishing house

US - UNITED STATES

Number of pages

11

Pages from-to

—

UT code for WoS article

—

EID of the result in the Scopus database

2-s2.0-85195287934