Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers computer-aided artificial intelligence and machine learning technologies as related to the impacts of climate change and its potential to prevent/remediate the effects. As such, different types of algorithms, mathematical relations and software models may help us to understand our current reality, predict future weather events and create new products and services to minimize human impact, chances of improving and saving lives and creating a healthier world. This book covers different types of tools for the prediction of climate change and alternative systems which can reduce the levels of threats observed by climate change scientists. Moreover, the book will help to achieve at least one of 17 sustainable development goals i.e., climate action.
Dr Arun Lal Srivastav is working as Assistant Professor at Chitkara University, Himachal Pradesh (India). He obtained his Ph.D. from the Indian Institute of Technology (BHU), Varanasi in 2013 followed by Post-Doctoral Research at National Chung Hsing University, Taiwan in 2014. He is currently involved in the teaching of Environmental Science, Environmental Engineering and Disaster Management to the undergraduate engineering students. His research interests include water treatment, river ecosystem, climate change, soil health maintenance, phytoremediation, and waste management. He has published 50 research papers in various prestigious Journals of the Elsevier, Springer, IWA, Taylor and Francis, Wiley, Hindawi, MDPI, Indian Chemical Society along with in prestigious conferences and books. He has also filed 12 patents. Dr. Ashutosh Kumar Dubey received his PhD degree in Computer Science and Engineering from JK Lakshmipat University, Jaipur, Rajasthan, India. He is currently in the department of Computer Science and Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India. He is also the Senior Member of IEEE and ACM. He has more than 14 years of teaching experience. He has authored a book name Database Management Concepts. He has been associated with many international and national conferences as the Technical Program Committee member. He is also associated as the Editor/Editorial Board Member/ Reviewer of many peer-reviewed journals. His research areas are Data Mining, Health Informatics, Optimization, Machine Learning, Cloud Computing, Artificial Intelligence and Object-Oriented Programming. Dr. Abhishek Kumar is doctorate in computer science from University of Madras and research is going on face recognition using IOT concept and done M.Tech in Computer Science & Engineering from Government engineering college Ajmer, Rajasthan Technical University, Kota India. He has total Academic teaching experience of more than 8 years with more than 50 publications in reputed, peer reviewed National and International Journals, books & Conferences. His research area includes Artificial intelligence, Image processing, Computer Vision, Data Mining and Machine Learning. He has been in International Conference Committee of many International conferences. He has been the reviewer/editor of various peer-reviewed journals. Sushil Kumar Narang is Dean and an Associate Professor in the Department of Computer Science & Engineering at Chitkara University, Rajpura, Punjab (India) since 2019. From 2006-2019, He was head of IT department at SAS Institute of IT & Research, Mohali, Punjab (India). From 1996-2006, He was Assistant Professor at Department of Computer Science & Applications, MLN College, Yamuna agar, Haryana (India).He has completed his Ph.D. at Panjab University, Chandigarh (India). His Research on Feature Extraction and Neural Network Classifiers for Optical Character Recognition for Good quality hand written GurmukhiandDevnagariCharacters focused on various image processing, machine as well as deep learning algorithms. His research interests lie in the area of programming languages, ranging from theory to design to implementation, Image Processing, Data Analytics and Machine Learning. He has collaborated actively with researchers in several other disciplines of computer science; particularly Machine Learning on real world use cases.He is a certified Deep Learning Engineer from Edureka. He possesses expertise in Object-Oriented Analysis & Design and Development using Java and Python programming using OpenCV in Image Processing and Neural Network construction. He has strong knowledge of C++ and Java with experience in component architecture of product interface. With Solid training and management skills, He has demonstrated proficiency in leading and mentoring individuals to maximize levels of productivity, while forming cohesive team environments. Moonis Ali Khan received his doctoral degree (Ph.D.) in Applied Chemistry from Aligarh Muslim University, Aligarh, India, in 2009. From 2009 to 2011, he worked as a Post-Doctoral Researcher at Yonsei University, South Korea and Universiti Putra Malaysia, Malaysia. In 2011, he joined the Chemistry Department at the King Saud University (KSU), Saudi Arabia as an Assistant Professor. Currently, he is working as an Associate Professor at KSU. He is an interfacial chemist and his research is focused on the synthesis and development of novel materials for environmental remediation applications. To date, he has guided two doctoral students for their respective degrees. He has published more than hundred (research and review) articles and has two U.S. patents to his credit.
Title: Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence
Author:
ISBN: 9780323997140
Binding:
Publisher: Elsevier - Health Sciences Division
Publication Date: 2022-11-16
Number of Pages: 498
Weight: 1.0383 kg