Soft Modeling in Industrial Manufacturing
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Science & Nature, Technology, Engineering, General Computing
| Author: | ISBN: | 9783030032012 | |
| Publisher: | Springer International Publishing | Publication: | December 11, 2018 |
| Imprint: | Springer | Language: | English |
| Author: | |
| ISBN: | 9783030032012 |
| Publisher: | Springer International Publishing |
| Publication: | December 11, 2018 |
| Imprint: | Springer |
| Language: | English |
This book discusses the problems of complexity in industrial data, including the problems of data sources, causes and types of data uncertainty, and methods of data preparation for further reasoning in engineering practice. Each data source has its own specificity, and a characteristic property of industrial data is its high degree of uncertainty. The book also explores a wide spectrum of soft modeling methods with illustrations pertaining to specific cases from diverse industrial processes. In soft modeling the physical nature of phenomena may not be known and may not be taken into consideration. Soft models usually employ simplified mathematical equations derived directly from the data obtained as observations or measurements of the given system. Although soft models may not explain the nature of the phenomenon or system under study, they usually point to its significant features or properties.
This book discusses the problems of complexity in industrial data, including the problems of data sources, causes and types of data uncertainty, and methods of data preparation for further reasoning in engineering practice. Each data source has its own specificity, and a characteristic property of industrial data is its high degree of uncertainty. The book also explores a wide spectrum of soft modeling methods with illustrations pertaining to specific cases from diverse industrial processes. In soft modeling the physical nature of phenomena may not be known and may not be taken into consideration. Soft models usually employ simplified mathematical equations derived directly from the data obtained as observations or measurements of the given system. Although soft models may not explain the nature of the phenomenon or system under study, they usually point to its significant features or properties.
