Verstraete J. Artificial Intelligent Methods for Handling Spatial Data. Fuzzy Rulebase Systems and Gridded Data Problems

New York: Springer, 2019. — 132 p.PreliminariesOrganization of This Book
Feature Based Models
Grid Based Models
Digital Elevation Models
Data Structuring in GIS
Overlaying Gridded Data
Regridding
Spatial Disaggregation
Spatial Smoothing
Data Fusion
Spatial Disaggregation
Regridding
The Rulebase System
Inference Systems
Translating the Spatial Problem
Definition of a Fuzzy Set
α-Cut
Height
Mamdani Rulebase Systems
Concept
Defining the Variables
Using a Global Range
Using a Local Range
Estimated Ranges
Input Parameters
Output ParameterGenerating Rules from Examples with Constant Spaces
What Are Variable Spaces?
Combining the Ranges
Rescaling Most Possible Range Prior to Rulebase Construction
Developed Algorithm for Learning from Examples with Variable Spaces
Definition
CriteriaDefinition
ExamplesValue Comparison: Typical Approaches
Preprocessing of the Reference
Defining the Ranking Value
Data
Applying the Rulebase and Defuzzifying the Results
Complexity
Algorithm & Experiments
Programatory AspectsAlgorithm
Determining the -Intersection Matrix
Values and Possible Range
Training Data
Source Data
Algorithm Settings
Datasets for Disaggregation
Quality of Proxy Data
Disaggregation to Higher Resolutions
Multiple Proxy Data
Regridding of Warsaw Test Data
Angle of the Input Grids
Multiple Proxy Data
Concluding Remarks
Novel Aspects Presented in This Work
Future Directions for Research
Other Application Fields
Refs