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Research on Energy Saving of the Aluminum Industrial Production Based on Technologies of Pattern Recognition and Data Mining

Author: LouXiaoFang
Tutor: ZouFengXing
School: National University of Defense Science and Technology
Course: Control Science and Engineering
Keywords: Pattern Recognition Data Mining Aluminum Industry Energy consumption optimization Association rule mining Correlation Analysis K- averaging algorithm Threshold method cluster analysis algorithm Energy-saving
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 132
Quote: 0
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Abstract


The process industry is an important pillar of the development of the national economy, and widely exist in metallurgy, pharmaceutical, chemical and other industries, and holds an important position. Advanced manufacturing, control and management technology to transform the on process industrial production systems, maintain a sound and rapid development of key industrial sectors of the people's livelihood, are very critical for the protection of national security, to safeguard national interests and enhance the competitiveness of the national economy. With the rapid global economic development, the contradiction between energy supply and demand has become more prominent, energy conservation has become the subject of all mankind, is a long-term strategic approach to the economic development of each country. Especially in the huge energy consumption in the metallurgical industry, research in the production, how to reduce energy consumption is of great practical significance. This is not only able to reduce the production costs of enterprises, enhance their competitiveness and ability to adapt to the market, and of great strategic significance to alleviate the situation of China's energy shortage, to solve the bottleneck problem of sustainable development, and to promote the development of China's economic and social 1]. Aluminum industrial production, for example, the main factor in the aluminum industry in the production process of its energy-intensive process, the use of pattern recognition methods to study in order to achieve the data mining to find out which implied the law, which impact energy consumption avoid these factors, to find an energy saving production line, so that the scientific production of the arrangements, will be able to save a lot of energy in the production process. Can help enterprises to improve the agility degree, reduce material and energy consumption, improve market competitiveness in the global economy and the economic efficiency of enterprises. The nonferrous metallurgy process to the National Natural Science Foundation of the key projects for energy saving control of a sub-project of a number of theories and methods \Scheduling Method \energy consumption in industrial processes are reviewed, and the energy consumption of the production of tons of aluminum refining, and modeling of the energy consumption in the production of the aluminum industry. Due to the lack of actual production data, in order to facilitate the simulation study, the energy consumption for the production of tons of aluminum using Matlab simulation generated 1000 energy consumption data. 2, saving energy for the production of tons of aluminum, based on the principle of data mining association rule mining, the proposed association rule mining algorithm based on correlation analysis. Found the main factors affecting energy consumption through simulation, dig out the law of implied algorithm to solve the problem of energy saving industrial production of aluminum on the feasibility and effectiveness. 3, based on the modeling of the energy consumption of the industrial production of aluminum, the use of the C programming K-averaging algorithm used to solve the production of aluminum industry in saving energy, the first attempt similar pattern recognition algorithms used in the aluminum industry production and energy consumption optimization problems, through simulation, to find a solution to the problem. Algorithm is feasible, indicating that the attempt was successful. Energy consumption for the production of aluminum industry, a new pattern recognition algorithm - the threshold method cluster analysis algorithm. The algorithm is used to solve the problem of the energy consumption of the aluminum industrial production, and achieved good results, but the choice of algorithm parameters blindness, so the algorithm has been improved. By calculating the distance between the data to define the parameters, improved threshold method cluster analysis algorithm, to be able to find a better solution, but the increase in computation time. 5, various algorithms together comparative analysis of various results. The comparison results show that several algorithms are feasible to solve the problem of energy saving industrial production of aluminum, have advantages and disadvantages, in practice, as the case may be, to select the appropriate algorithm. Finally, a summary of the full text, and the aluminum industry based on pattern recognition and data mining, the next step in the production of energy saving focus.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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