P. Building your own FIS Error Models

Synopsis of Topic

An FIS can be constructed and implemented in a variety of ways. In the GCD software, we have adopted a standard format for fuzzy inference systems (*.fis) that is defined in Matlab's Fuzzy Logic Toolbox. In this session, we show you how to build and edit your own FIS and emphasize the thought process behind choosing inputs, defining categories and their membership functions, building the rule table, calibrating the output, and verifying the behavior and performance of your FIS.

An example from Matlab's Fuzzy Logic Toolbox Support Documentation of an FIS for determining a tip.

Why we're Covering it

Fuzzy inference systems are supported in the GCD Software and the appropriate construction, calibration and applications of FIS is a critical skill to develop. In this section we focus on the construction and calibration aspects of building an FIS.

Learning Outcomes Supported

This topic will help fulfill the following primary learning outcome(s) for the workshop:
  • A comprehensive overview of the theory underpinning geomorphic change detection
  • The fundamental background necessary to design effective repeat topographic monitoring campaigns and distinguish geomorphic changes from noise (with particular focus on restoration applications)
  • Hands-on instruction on use of the GCD software through group-led and self-paced exercises


Slides and/or Handouts


Relevant Online Help or Tutorials for this Topic

IIf you would like to contribute FIS error models you've made to the community, use our BitBucket Fuzzy Inference System (FIS) Repository for DEM Error Models

Relevant or Cited Literature

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