Role of Nature-Inspired Algorithms in Real-life Problems | Agenda Bookshop Skip to content
Please note that books with a 10-20 working days delivery time will not arrive before Christmas.
Please note that books with a 10-20 working days delivery time will not arrive before Christmas.
Age Group_Uncategorized
Age Group_Uncategorized
automatic-update
B01=Kusum Deep
B01=Vanita Garg
Category1=Non-Fiction
Category=TJFM1
Category=UYQ
COP=Singapore
Delivery_Pre-order
Language_English
PA=Not yet available
Price_€100 and above
PS=Forthcoming
softlaunch

Role of Nature-Inspired Algorithms in Real-life Problems

English

The book includes nature-inspired optimization techniques and their applications. It offers recent trends in the field of nature-inspired algorithms for solving real-life problems in various fields related to manufacturing, artificial intelligence, finance, etc. Nature-inspired optimization techniques are not only useful but also needed for solving open-ended problems. Understanding nature-inspired techniques and their importance for solving real-life problems can open many directions for researchers and academicians. This book will be helpful in acquiring knowledge of nature-inspired optimization techniques in various fields of real-life applications.

See more
Current price €183.34
Original price €192.99
Save 5%
Age Group_Uncategorizedautomatic-updateB01=Kusum DeepB01=Vanita GargCategory1=Non-FictionCategory=TJFM1Category=UYQCOP=SingaporeDelivery_Pre-orderLanguage_EnglishPA=Not yet availablePrice_€100 and abovePS=Forthcomingsoftlaunch

Will deliver when available. Publication date 03 Jan 2025

Product Details
  • Dimensions: 155 x 235mm
  • Publication Date: 03 Jan 2025
  • Publisher: Springer Verlag Singapore
  • Publication City/Country: Singapore
  • Language: English
  • ISBN13: 9789819747146

About

Dr. Vanita Garg is working as an Assistant Professor in Mathematics at Amity University. Her research interests are nature-inspired algorithms optimization Soft Computing and Reliability. She received her Masters degree (M.SC.) in 2011 from Punjabi University Patiala and Ph.D. from Indian Institute of Technology Roorkee in 2017. She has received the Lady Kaula Award for securing her first position in college. She has published more than 20 research papers in journal papers book chapters and conference papers. She has published edited books in Springer John and Wiley. She is active in current research and has teaching experience of 8 years.   Dr. Kusum Deep is a full Professor with the Department of Mathematics Indian Institute of Technology Roorkee India and a Visiting Professor at Liverpool Hope University UK and University of Technology Sydney Australia. With B.Sc Hons & M.Sc Hons. School from Centre for Advanced Studies Panjab University Chandigarh she is an M.Phil Gold Medalist. She earned her PhD from UOR (now IIT Roorkee) in 1988. She has been a national scholarship holder and a Post Doctoral from Loughborough University UK assisted by an International Bursary funded by the Commission of European Communities Brussels. She has won numerous awards including the Khosla Research Award UGC Career Award Starred Performer of IITR Faculty Best Paper awards by Railway Bulletin of Indian Railways special facilitation in memory of the late Prof. M. C. Puri AIAP Excellence Award. She has authored two books supervised 20 Ph. D.s and published 125 research papers. She is a Senior Member of ORSI CSI IMS and ISIM. She is the Executive Editor of the International Journal of Swarm Intelligence Inderscience. She is Associate Editor of Swarm and Evolutionary Algorithms Elsevier and is on the editorial board of many journals. She is the Founder and President of the Soft Computing Research Society in India. She is the General Chair of a series of International Conferences on Soft Computing for Problems Solving (SocProS). Her research interests are Evolutionary Algorithms Swarm Intelligence and nature-inspired optimization techniques and their applications.  

Customer Reviews

Be the first to write a review
0%
(0)
0%
(0)
0%
(0)
0%
(0)
0%
(0)
We use cookies to ensure that we give you the best experience on our website. If you continue we'll assume that you are understand this. Learn more
Accept