Research On The Integrated Information Process Technique And Its Application In Industry Systems

The purpose of this thesis is to resolve the puzzle of the contradiction between data acquisition and data utilization in the industry system, to develop methods in finding hidden knowledge from vast primary data and developing information process models accordingly. Thereby the industry system's performance could be improved by taking corresponding intelligence actions. And a modeling method based on the data origin from the industry system itself could be adopted if the precise math model is hard to develop because of the complicated production process.Research works are taken under the guidance of system analysis. First, the conversion relations of "data—information—knowledge—intelligence actions" are detected out, which uncover the basic tasks of the industry system information process. Further research works run under these relations of conversion. Second, as to data mining and data fusion, particular analyses are done in seeking the similarity and difference between these two. Some reciprocity of these two is found. Functions and limitations of respectively using of these two in industry system information process are also pointed out. With this understanding, an integrated information process technique and the corresponding models are developed. Third, the industry system's topological structure, which independent from hardware facilities, is abstracted at the angle of information process. The input and the output of the information process system are classified, and corresponding process methods are developed. Then the general information process model of industry system is developed based on the integrated information process technique. After that, the relations between the model's abstract levels and analytic levels of the amount of information are discussed, and the basic implementation methods are discussed too. Furthermore, these models are applied in the coking process of the coking factory in a metallurgical enterprise. In this case, artificial neural network ensembles and rough set theory are applied as the concrete algorithm; software programs are designed on the condition of the existent of monitor and supervise control system. As a result of the using of the industry system's general information process model, the factory's long-puzzled problem of coke quality forecasting and coke oven temperature's intelligent control are basically resolved. Finally, the steps of developing a general model of the industry information process are concluded.