Knowledge engineering for industrial expert systems
-
P. Megaladevi
Abstract
Innovation is the heart of any modern manufacturing to bring high- quality, globally accepted engineering products, and automation has a vital role in industrial improvement. Knowledge engineering (KE) enables data-based application and human thought process in electronic gadgets. The present chapter deals with expert systems, knowledge-based engineering, and KE applications in modern industries by expert systems.
Abstract
Innovation is the heart of any modern manufacturing to bring high- quality, globally accepted engineering products, and automation has a vital role in industrial improvement. Knowledge engineering (KE) enables data-based application and human thought process in electronic gadgets. The present chapter deals with expert systems, knowledge-based engineering, and KE applications in modern industries by expert systems.
Chapters in this book
- Frontmatter I
- Contents V
- Knowledge engineering for industrial expert systems 1
- Machine learning integrated blockchain model for Industry 4.0 smart applications 13
- Prototyping the expectancy disconfirmation theory model for quality service delivery in federal university libraries in Nigeria 26
- Design of chatbot using natural language processing 60
- Algorithm development based on an integrated approach for identifying cause and effect relationships between different factors 80
- Risk analysis and management in projects 96
- Assessing and managing risks in smart computing applications 122
- COVID-19 visualization and exploratory data analysis 145
- Business intelligence and decision support systems: business applications in the modern information system era 156
- Business intelligence implementation in different organizational setup evidence from reviewed literatures 173
- Conceptualization of a modern digital-driven health-care management information system (HMIS) 187
- Knowledge engine for a Hindi text-to-scene generation system 201
- Index 229
Chapters in this book
- Frontmatter I
- Contents V
- Knowledge engineering for industrial expert systems 1
- Machine learning integrated blockchain model for Industry 4.0 smart applications 13
- Prototyping the expectancy disconfirmation theory model for quality service delivery in federal university libraries in Nigeria 26
- Design of chatbot using natural language processing 60
- Algorithm development based on an integrated approach for identifying cause and effect relationships between different factors 80
- Risk analysis and management in projects 96
- Assessing and managing risks in smart computing applications 122
- COVID-19 visualization and exploratory data analysis 145
- Business intelligence and decision support systems: business applications in the modern information system era 156
- Business intelligence implementation in different organizational setup evidence from reviewed literatures 173
- Conceptualization of a modern digital-driven health-care management information system (HMIS) 187
- Knowledge engine for a Hindi text-to-scene generation system 201
- Index 229
