Active Extraction Method for Standardized Features of Energy Big Data Based on Dynamic Weighting

Abstract:
Energy is an important foundation for the development of human society, and it is also an important source for ensuring the sustained and steady growth of the national economy and sustainable utilization. At the same time, the energy consumed by human beings is also increasing day by day. Nowadays, energy has become the material basis for the survival and development of human society, and has a particularly important strategic position in the national economy. Ensuring energy security and development is of great significance to building a modern socialist country. In order to realize the active extraction of standardized features of energy data, this paper proposes a framework for active extraction of energy big data features based on dynamic weighting. Through dynamic weighting, rich and diverse energy data with representative characteristic indicators can be extracted. This paper mainly uses the data method and experimental method to study the correlation between dynamic weighting and energy data extraction methods. In the test, the accuracy of the dynamic weighting method exceeds 0.5. Experimental results show that the method of actively extracting standardized features of energy big data based on dynamic weighting can save time and effort, and is easy to operate, which further improves the accuracy of the measurement results.