Spatially Explicit Hyperparameter Optimization for Neural Networks

Dr. Minrui Zheng is an Associate Professor in the School of Public Administration and Policy at Renmin University of China. She earned her M.S. in mathematical finance and her Ph.D. from the University of North Carolina at Charlotte. She has published over 10 articles in peer-reviewed journals and book chapters, and is a Member of several professional organizations including the American Association of Geographers and the North American Regional Science Council. Her research and teaching interests focus on GIScience, spatial analysis and modeling, machine learning, high-performance and parallel computing, and land change modeling. Her work focuses on using advanced spatial modeling techniques and high-performance and parallel computing to analyze big data-driven spatial problems.

Chapter 1: Introduction.- Chapter 2: Literature Review.- Chapter 3: Methodology.- Chapter 4: Study I. Hyperparameter optimization of neural network-driven spatial models accelerated using cyber-enabled high-performance computing.- Chapter 5: Study II. Spatially explicit hyperparameter optimization of neural networks accelerated using high-performance computing.- Chapter 6: Study III. An integration of spatially explicit hyperparameter optimization with convolutional neural networks-based spatial models.