<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Along with the limited conventional energy sources and the increasingly prominent environmental problems, new energy sources characterized by “environmental protection” and “renewable” are gradually gaining the attention of many countries in the world. In order to accelerate the development of new energy, countries have introduced control strategies for the new energy industry, but the effect is that the seeds are widely planted and thinly sown. This paper constructs a control strategy for new energy trend based on Eviews econometric model through sliding average model calculation, multiple linear regression prediction, statistics of total new energy, new energy usage and new energy market share calculation. The strategy was also experimented, and the experiments analyzed and predicted the development of new energy in the world and China under the new energy trend. The results show that under the Eviews econometric model, the share of world new energy consumption in the total energy consumption market increases from 25% to 80%, while in China the new energy represented by natural gas grows from 698 million cubic meters to 9,671 million cubic meters, a full 70.76%, and with the development of the economy new energy consumption will rise from 5 billion to 11 billion.</p>
</abstract>

Along with the limited conventional energy sources and the increasingly prominent environmental problems, new energy sources characterized by “environmental protection” and “renewable” are gradually gaining the attention of many countries in the world. In order to accelerate the development of new energy, countries have introduced control strategies for the new energy industry, but the effect is that the seeds are widely planted and thinly sown. This paper constructs a control strategy for new energy trend based on Eviews econometric model through sliding average model calculation, multiple linear regression prediction, statistics of total new energy, new energy usage and new energy market share calculation. The strategy was also experimented, and the experiments analyzed and predicted the development of new energy in the world and China under the new energy trend. The results show that under the Eviews econometric model, the share of world new energy consumption in the total energy consumption market increases from 25% to 80%, while in China the new energy represented by natural gas grows from 698 million cubic meters to 9,671 million cubic meters, a full 70.76%, and with the development of the economy new energy consumption will rise from 5 billion to 11 billion.

New anergy tide control strategy based on Eviews econometric model

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"New anergy tide control strategy based on Eviews econometric model"}

Along with the limited conventional energy sources and the increasingly prominent environmental problems, new energy sources characterized by “environmental...

New anergy tide control strategy based on Eviews econometric model

Publicado en línea: 02 jun 2023

Páginas: -

Recibido: 13 jun 2022

Aceptado: 19 oct 2022

DOI: https://doi.org/10.2478/amns.2023.1.00178

Palabras clave
Sliding average model, Multiple linear regression forecasting, New energy usage, New energy market share, Total new energy statistics

© 2023 Jian Ding et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

New anergy tide control strategy based on Eviews econometric model

Publicado en línea: 02 jun 2023

Páginas: -

Recibido: 13 jun 2022

Aceptado: 19 oct 2022

DOI: https://doi.org/10.2478/amns.2023.1.00178

Palabras claveSliding average model, Multiple linear regression forecasting, New energy usage, New energy market share, Total new energy statistics

© 2023 Jian Ding et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
Sliding average model, Multiple linear regression forecasting, New energy usage, New energy market share, Total new energy statistics