Computational Intelligence Techniques in Earth and Environmental Sciences - Tapa blanda

Acerca del autor

Dr. Tanvir Islam is working as a post-doctoral scientist with CIRA/CSU at the NOAA/NESDIS Center for Satellite Applications and Research (STAR), College Park, MD, USA. Before joining NOAA/NESDIS, he worked as a visiting scientist/research collaborator at the University of Tokyo, Japan. He finished his PhD from the Department of Civil Engineering, University of Bristol, UK. Dr. Prashant K. Srivastava worked as an assistant professor in Environmental Sciences at Sardar Patel University, Anand, Gujarat, India from June 2007 to Sep 2010. He finished his PhD under commonwealth plan in Remote Sensing from Department of Civil Engineering, University of Bristol, U.K. Currently, he is working as a research scientist for the SMAP satellite soil moisture retrieval at ESSIC/NASA Goddard Space Flight Center, Maryland, USA. Dr. Manika Gupta completed her PhD in Geo-Environmental pollution at the Department of Civil Engineering, IIT Delhi, India. Currently, she is working as a research consultant for satellite based slum area delineation. Dr. Xuan Zhu is a senior lecturer and director of the Centre for GIS at Monash University. Dr Zhu’s areas of expertise include GIS theory, techniques and applications, decision support systems for regional sustainable development and environmental decision analysis and modelling. Dr. Saumitra Mukherjee is a professor in Geology & Remote sensing, School of Environmental sciences, Jawaharlal Nehru University, New Delhi.

De la contraportada

Computational intelligence techniques have enjoyed growing interest in recent decades among the earth and environmental science research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward a sustainable earth. This book compiles a collection of recent developments and rigorous applications of computational intelligence in these disciplines. Techniques covered are divided into three categories - classical intelligence techniques, probabilistic and transforms intelligence techniques, and hybrid intelligence techniques. Further topics given treatment in this volume include meteorology, atmospheric modeling, climate change, water resources engineering, and hydrological modeling.

By linking computational intelligence techniques with earth and environmental science oriented problems, this book promotes synergistic activities among scientists and technicians working in areas such as data mining and machine learning. We believe that a diverse group of academics, scientists, environmentalists, meteorologists, and computing experts with a common interest in computational intelligence techniques within the earth and environmental sciences will find this book to be of great value.