Artificial Intelligent Methods for Handling Spatial Data

Beschreibung

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.
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.
Reports on a novel method combining fuzzy inference systems with spatial data to solve the map overlay problem Describes modification of existing inference systems and their applications to new problems Demonstrates the efficacy of the method with several experiments on disambiguation and regridding Offers a detailed description of the algorithm implementation process

Autor*in

Jörg Verstraete

Themen in »Artificial Intelligent Methods for Handling Spatial Data«

Spatial Data Processing Regridding Map Overlay for Grids Applications of Fuzzy Inference Systems Applications of Rulebase Systems Adapting Fuzzy Rulebase Systems Processing of Gridded Spatial Datasets Grid Based Models Combining Gridded Datasets Combining Spatial Datasets Algorithms for Spatial Disaggregation Spatial Similarity between Different Grids Mamdani Rulebase Systems Defuzzification Methods

Stimmen zu »Artificial Intelligent Methods for Handling Spatial Data«

Details

Link teilen