E-Book, Englisch, Band 698, 643 Seiten, eBook
Malik / Srivastava / Sood Applications of Artificial Intelligence Techniques in Engineering
1. Auflage 2019
ISBN: 978-981-13-1819-1
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
SIGMA 2018, Volume 1
E-Book, Englisch, Band 698, 643 Seiten, eBook
Reihe: Advances in Intelligent Systems and Computing
ISBN: 978-981-13-1819-1
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
The book is a collection of high-quality, peer-reviewed innovative research papers from the International Conference on Signals, Machines and Automation (SIGMA 2018) held at Netaji Subhas Institute of Technology (NSIT), Delhi, India. The conference offered researchers from academic and industry the opportunity to present their original work and exchange ideas, information, techniques and applications in the field of computational intelligence, artificial intelligence and machine intelligence. The book is divided into two volumes discussing a wide variety of industrial, engineering and scientific applications of the emerging techniques.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Chapter 1: Annual Energy Savings with Multiple DG and D-STATCOM Allocation using PSO in DNO Operated Distribution Network.- Chapter 2: Optimized 2DOF PID for AGC of Multi Area Power System using Dragon-Fly.- Chapter 3:Wide Area Monitoring System using Integer Linear Programming.- Chapter 4: Fault Classification and Faulty Phase Selection Using Symmetrical Components of Reactive Power for EHV Transmission Line.- Chapter 5: Optimal Bidding Strategy in Deregulated Power Market Using Krill Herd Algorithm.- Chapter 6: A Novel Intelligent Bifurcation Classification Model Based on Artificial Neural Network (ANN).- Chapter 7: Teaching Learning Based Optimization for Frequency Regulation in Two Area Thermal-Solar Hybrid Power System.- Chapter 8: An Approach to Minimize the Transmission Loss and Improves the Voltage Profile of Load Bus Using Interline Power Flow Controller (IPFC).- Chapter 9: A Novel Intelligent Transmission Line Fault Diagnosis Model Based on EEMD And Multiclass PSVM.




