Title :
Energy consumption optimization of the aluminum industrial production based on K-means algorithm
Author :
Xiao-Fang, Lou ; Feng-xing, Zou
Author_Institution :
Dept. of Autom. Control, Nat. Univ. of Defense Technol., Changsha, China
Abstract :
This paper extracted the basic energy consumption situation in 1 ton of aluminum production, for the current aluminum industry from mining to the aluminum processing. For a lot of multi-dimensional energy data, this paper based on the principle of K-means algorithm, and introduced into the error limit, then completed the data mining of the multi-dimensional energy consumption data of the aluminum industrial production by using C++. After a comprehensive consideration of two factors of the total energy consumption data is smallest and the data number is largest, this paper found the classes that the total energy consumption data is smallest and the data number is largest, contrasted and analyzed their class hearts, finally arrived at a reasonable input to achieve the purpose of energy saving of the aluminum industrial production. Further more verified the feasibility and effectiveness of the algorithm.
Keywords :
C++ language; aluminium industry; aluminium manufacture; data mining; energy consumption; C++ language; K-means algorithm; aluminum industrial production; aluminum industry; aluminum processing; data mining; energy consumption optimization; energy saving; error limit; multidimensional energy data; Analytical models; Atmospheric modeling; Casting; Materials; Water conservation; K-means algorithm; aluminum industry; clustering; data mining; energy consumption;
Conference_Titel :
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-7957-3
DOI :
10.1109/CMCE.2010.5610390