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Clean energy can not only alleviate environmental problems but also contribute to rapid and sustainable development. The gray system is based on the sequence operator to process the original data and mine the law of change. GM(1,1) is a specific method of mining data, by building a GM(1,1) model to accumulate and generate data, the randomness of the data can be weakened and its regularity can be revealed. Here we use the GM(1,1) model to dynamically predict the future consumption rate of clean energy. This research not only provides data support for China’s green development, but also provides suggestions for improvement based on actual conditions.

Beginning in the 1970s, academia began to study consumer innovation and used it as an important indicator for predicting consumers’ new product adoption behavior. This article makes a more comprehensive summary and evaluation of the definition of consumer innovation from three aspects (innate innovativeness; special fields innovativeness; actualized innovativeness), summarizes the relationship between the three innovations, and builds a consumer innovation integration model.