Application of Cloud Computing and Information Fusion Technology in Green Investment Evaluation System

Abstract

As an important part of the development of green economy, the green investment evaluation system provides a method to identify the performance of the investment environment and also guides the design of green investment plans. This article is aimed at analyzing the application of cloud computing and information fusion technology in the green investment evaluation system, using empirical analysis, qualitative and quantitative analysis, data integration, and distributed computing algorithms to carry out research. Data acquisition is mainly through cloud platform information fusion, to evaluate the investment subject, investment object, and investment vehicle of green investment. Qualitative and quantitative analysis is mainly through the definition of prerequisites by stipulating certain aspects of green, and the analysis of the country’s data changes in a certain time zone. Focus on the qualitative analysis and research on the green benefit attributes of a certain thing. In addition, by analyzing the influencing factors of the investment development status of green industries in different countries, such as green products, green projects, and green funds, it proves that the application of cloud computing and information fusion technology has a huge effect on the green investment evaluation system. Experimental data shows that in the past five years, investment in fixed assets in my country’s major industries accounted for the proportion of fixed asset investment in the whole society, and investment in environmental protection and energy supply industries has continued to rise. This upward trend is manifested in the fact that the amount of energy investment is increasing year by year. The development trend is the strongest during the development period and the entry period, and its data grows the most rapidly, while investment in the transportation industry has always been listed in the tables. For the first place in the industry, the highest was 20.84%.