隨著科學技術的進步，人類社會發展不斷提速。各種新生事物及其伴生物隨之生滅。面對新事物，人們充滿好奇。大家總是希望能在短時間內能對新事物及其共生物的發展需求進行預測和總結。
由於新生事物及其共生需求的特點，系統動力學成為較為適宜的研究方法之一。但在實際研究中，經常碰到“因新生而少數據”的尷尬。為了解決少數據情境下的複雜共生需求預測研究，本文採用組合理念融合灰色預測理論的系統動力學進行探討，這樣既能實現定性與定量的結合，又能系統且全面地分析新事物共生需求的互動關係。
本文通過對新能源汽車車樁比案例的研究，不僅綜合利用線性回歸等方法，還開放性的選擇了灰色理論來參與系統動力學的參數賦值和方程建立。可以看出在新事物共生環境下，包容性極強的系統動力學能很好地適應其研究需求。特別是灰色預測方法能非常靈活的實現少數據預測，避免因數據缺乏而導致研究止步，進而為少數據情境下的研究多提供了一種新選擇，便於人們能夠在共生事物發展的初期介入研究。

With the advancement of science and technology, the development of human society continuously increase. Nowadays users have been overwhelmed by several new techniques and products which are introduced almost every day. When dealing with new techniques and products, people are full of curiosity and always hope to be able to understand its performance as well as forecast its demands in a short period of time.
Due to short period of time, the most prominent challenge we have encountered is "lacking data due to first appearance". In order to solve the complex forecast demand problem under lacking data situation, this thesis adopts the approach of integrating system dynamics and the grey forecasting theory to discuss, describe and analyze the interactions of different factors on product demands.
Through the case study of the vehicle-to-pile ratio of new energy vehicles, not only the linear regression and other methods are used comprehensively, but also the grey theory is selected to identify parameters and establish equations of the system dynamics. It can be seen that in the innovative environment of new things, the system dynamics can be well adapted to the research needs. In particular, the grey prediction method is very effective in prediction performance of first appeared products when the data are limited. This prevent study from being stuck in early stage of the research when data are rare.

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