Scipediacontent: Scipediacontent moved page Draft Content 471152404 to Li et al 2017e

2021-02-12T12:08:54Z

Scipediacontent moved page Draft Content 471152404 to Li et al 2017e

Scipediacontent: Created page with " == Abstract == The potential demand of battery electric vehicle (BEV) is the base of the decision-making to the government policy formulation, enterprise manufacture capacit..."

2021-02-12T12:08:50Z

Created page with " == Abstract == The potential demand of battery electric vehicle (BEV) is the base of the decision-making to the government policy formulation, enterprise manufacture capacit..."

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== Abstract ==

The potential demand of battery electric vehicle (BEV) is the base of the decision-making to the government policy formulation, enterprise manufacture capacity expansion, and charging infrastructure construction. How to predict the future amount of BEV accurately is very important to the development of BEV both in practice and in theory. The present paper tries to compare the short-term accuracy of a proposed modified Bass model and Lotka-Volterra (LV) model, by taking China’s BEV development as the case study. Using the statistics data of China’s BEV amount of 21 months from Jan 2015 to Sep 2016, we compare the simulation accuracy based on the value of mean absolute percentage error (MAPE) and discuss the forecasting capacity of the two models according to China’s government expectation. According to the MAPE value, the two models have good prediction accuracy, but the Bass model is more accurate than LV model. Bass model has only one dimension and focuses on the diffusion trend, while LV model has two dimensions and mainly describes the relationship and competing process between the two populations. In future research, the forecasting advantages of Bass model and LV model should be combined to get more accurate predicting effect.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_471152404-beopen116-5320-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://downloads.hindawi.com/journals/jat/2017/7801837.pdf http://downloads.hindawi.com/journals/jat/2017/7801837.pdf] under the license https://creativecommons.org/licenses/by

* [http://dx.doi.org/10.1155/2017/7801837 http://dx.doi.org/10.1155/2017/7801837] under the license cc-by

* [http://downloads.hindawi.com/journals/jat/2017/7801837.pdf http://downloads.hindawi.com/journals/jat/2017/7801837.pdf],
: [http://downloads.hindawi.com/journals/jat/2017/7801837.xml http://downloads.hindawi.com/journals/jat/2017/7801837.xml],
: [http://dx.doi.org/10.1155/2017/7801837 http://dx.doi.org/10.1155/2017/7801837]

* [http://dx.doi.org/10.1155/2017/7801837 http://dx.doi.org/10.1155/2017/7801837],
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license http://creativecommons.org/licenses/by/4.0/

* [https://www.hindawi.com/journals/jat/2017/7801837 https://www.hindawi.com/journals/jat/2017/7801837],
: [http://downloads.hindawi.com/journals/jat/2017/7801837.pdf http://downloads.hindawi.com/journals/jat/2017/7801837.pdf],
: [https://core.ac.uk/display/87803703 https://core.ac.uk/display/87803703],
: [https://academic.microsoft.com/#/detail/2744639363 https://academic.microsoft.com/#/detail/2744639363]

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Li et al 2017e - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 471152404 to Li et al 2017e

Scipediacontent: Created page with " == Abstract == The potential demand of battery electric vehicle (BEV) is the base of the decision-making to the government policy formulation, enterprise manufacture capacit..."