Название: Artificial Intelligent Methods for Handling Spatial data: Fuzzy Rulebase Systems and Gridded Data Problems Автор: Jorg Verstraete
Издательство: Springer
ISBN: 3030002373
Год: 2018 (2019 Edition)
Страниц: 137
Язык: английский
Формат: pdf (true), djvu
Размер: 10.16 MB
This book combines and summarizes the author’s research in developing an artificial intelligent method to cope with the map overlay problem for gridded datasets. This problem encompasses both spatial disaggregation, i.e. increasing the spatial resolution of a gridded dataset, and regridding, i.e. the remapping of a gridded dataset onto another raster; and both approaches take advantage of additional available proxy data to allow the artificial intelligent system to determine the underlying spatial distribution.
This book provides readers with an insight into the development of a novel method for regridding gridded spatial data, an operation required to perform the map overlay operation and apply map algebra when processing spatial data. It introduces the necessary concepts from spatial data processing and fuzzy rulebase systems and describes the issues experienced when using current regridding algorithms. The main focus of the book is on describing the different modifications needed to make the problem compatible with fuzzy rulebases.
It offers a number of examples of out-of-the box thinking to handle aspects such as rulebase construction, defuzzification, spatial data comparison, etc. At first, the emphasis is put on the newly developed method, and additional datasets containing information on the underlying spatial distribution of the data are identified. After this, an artificial intelligent system (in the form of a fuzzy inference system) is constructed using this knowledge and then applied on the input data to perform the regridding. The book offers an example of how an apparently simple problem can pose many different challenges, even when trying to solve it with existing soft computing technologies. The workflow and solutions to solve these challenges are universal and may therefore be broadly applied into other contexts.
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