Recent Developments In Spatial Analysis
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Recent Developments in Spatial Analysis
Author: Manfred M. Fischer
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-03-09
In recent years, spatial analysis has become an increasingly active field, as evidenced by the establishment of educational and research programs at many universities. Its popularity is due mainly to new technologies and the development of spatial data infrastructures. This book illustrates some recent developments in spatial analysis, behavioural modelling, and computational intelligence. World renown spatial analysts explain and demonstrate their new and insightful models and methods. The applications are in areas of societal interest such as the spread of infectious diseases, migration behaviour, and retail and agricultural location strategies. In addition, there is emphasis on the uses of new technologoies for the analysis of spatial data through the application of neural network concepts.
Recent Trends in Geospatial AI
Geospatial research is facing both enormous new potential and challenges due to artificial intelligence (AI). Theoretical advances, large data, computer hardware, and high-performance computing platforms that enable the creation, training, and deployment of AI models in a reasonable amount of time are the main drivers of its rapid development. There have been notable developments in the field of geospatial AI, particularly in the areas of machine learning, deep learning, and the most recent advancements in AI technology in both academia. These advancements are transforming how spatial data is analyzed and interpreted, enabling more accurate predictions, real-time mapping, and enhanced decision-making capabilities across various applications. Recent Trends in Geospatial AI discusses the emerging potentials, challenges, and trends in geospatial AI. It further explores innovative applications of geospatial AI across a variety of sectors. Covering topics such as data processing, internet of things (IoT), and traffic flow optimization, this book is an excellent resource for graduate and postgraduate students, researchers, academicians, practitioners, and more.
Recent Developments in Data Science and Business Analytics
This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.