Mechanism models used in cold continuous rolling mills can reflect the general trend of production process. But the precision of models can't satisfy the more requirements of production quality, variety and performance. In order to improve the effective of rolling models, data mining technology can be used to study and find the valuable information and knowledge, which is the newly item and research direction in rolling process field. At present many cold rolling production lines have finished the basic modification works, can acquire and save amounts of process data from the production spot. Various methods such as SVM are used to study the rolling process by model and data from another direction in the paper. The results show that data mining method can help to find more knowledge to improve the production control.
The Mining Kernel System provides a foundation for building data-mining tools that are capable of tackling complex knowledge discovery problems. Examples from applications involving intelligent computerized support for a urology clinic and improved customer database utilization in financial settings illustrate its effectiveness.
Berzelius failed to make use of Faraday's electrochemical laws in his laborious determination of equivalent weights.