Grey prediction model has good performance in solving small data problem, and has been widely used in various research fields. However, when the data show oscillation characteristic, the effect of grey prediction model performs poor. To this end, a new method was proposed to solve the problem of modelling small data oscillation sequence with grey prediction model. Based on the idea of information decomposition, the new method employed grey prediction model to capture the trend characteristic of complex system, and ARMA model was applied to describe the random oscillation characteristic of the system. Crops disaster area in China was selected as a case study and the relevant historical eight-year data published by government department were substituted to the proposed model. The modelling results of the new model were compared with those of other traditional mainstream prediction models. The results showed that the new model had evidently superior performance. It indicated that the proposed model will contribute to solve small oscillation problems and have positive significance for improving the applicability of grey prediction model.
IntroductionHow enterprises should practice digitalization transformation to effectively improve green innovation performance is related to the sustainable development of enterprises and the economy, which is an important issue that needs to be clarified.MethodsThis research uses the perspective of production and operation to deconstruct the digitalization of industrial listed enterprises from 2016 to 2020 into six features. A variety of machine learning methods are used, including DBSCAN, CART and other algorithms, to specifically explore the complex impact of enterprise digitalization feature configuration on green innovation performance.Conclusions(1) The more advanced digitalization transformation the enterprises have, the more possibly the high green innovation performance can be achieved. (2) Digitalization innovation is the digitalization element with the strongest influence ability on green innovation performance. (3) As the advancement of digitalization transformation, enterprises should also focus on digitalization innovation input and digitalization operation output, otherwise they should pay attention to digitalization management and digitalization operation output.DiscussionThe conclusions of this research will help enterprises understand their digitalization competitiveness and how to practice digitalization transformation to enhance green innovation performance, and also help the government to formulate policies to promote the development of green innovation in the digital economy era.
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