Energy Consumption Optimization of the Aluminum Industrial Production Based on Pattern Recognition

The basic energy consumption situation in 1 ton of aluminum production is addressed in this paper for the current aluminum industry from mining to the aluminum processing. In order to save energy of the aluminum industrial production, the K-means algorithm and threshold cluster analysis algorithm from the pattern recognition are proposed, and the classification of the energy consumption data of the aluminum industrial production is completed by using C++. The two algorithms are compared in terms of minimum total energy consumption and the actual production requirements. A class is found with more data number and smaller total energy consumption data, and such class heart is used as an input to save the aluminum industrial production. Further-more the feasibility and the effectiveness of the algorithms are verified.