Fuzzy attributes

Instructions for use

Settings window

“Layers” field

The “Layers” field displays the list of loaded layers, limited to geopackage tables.

⚠️The current version only takes into account data stored in geopackage files (gpkg).

“Attributes” field

Once the layer has been selected, this drop-down menu displays all of its numeric fields.

“Statistics” button

Click this button to view basic statistics for the selected field. This will be useful for defining the transformation function parameters.

Transformation function

This drop-down menu allows you to choose the type of transformation function. See below for details of these functions.

Function parameters

Enter your parameter values, separated by commas. The next line (e.g., ……) gives you the format corresponding to the selected function.

Transformation history

Each time a transformation or aggregation is performed by the plugin, a line is added to a history management table, metafuzzy, which is created and maintained within the data geopackage.

In the case of fuzzy transformations, the fields filled in are:

  • field: the original field in the layer used for the transformation

  • function: the selected function

  • params: the numerical values of the transformation parameters

  • source1: the name of the source layer of the attribute

Result

The result of the command is a new attribute in the input table with the suffix _fuzzy.

Membership functions: transforming data into fuzzy judgments

Here are the main functions available in the FuzzyAttributes plugin, with concrete examples:

1. Linear increasing

  • Used when “the bigger, the better.”

  • Example: altitude for a mountain species, where suitability increases gradually from 800 m to 1800 m.

  • Parameters: a (minimum value) and b (maximum value).

  • Formula:

    • 0 if x ≤ a

    • (x − a) / (b − a) if a < x < b

    • 1 if x ≥ b

2. Linear decreasing

  • Opposite case: “the smaller, the better.”

  • Example: pollution levels, where a high value is bad.

  • Parameters: a, b as above, but reversed.

3. Trapezoidal

  • Represents an area of “full membership” surrounded by transitions.

  • Example: an ideal temperature between 64°F and 72°F, acceptable between 59°F and 75°F.

  • Parameters: a (start of transition), b (start of ideal zone), c (end of ideal zone), d (end of transition).

4. Triangular

  • Simplified variant of the trapezoidal.

  • Example: note “ideal” humidity at a specific point (e.g., 65%), but tolerate some variation around it.

  • Parameters: a (start of rise), b (peak), c (end of descent)..

5. Increasing sigmoid (S)

  • Represents slow growth, then rapid growth, then stabilization.

  • Example: acceptability of river flow for irrigation.

  • Parameters: c (central value), α (slope).

6. Descending sigmoid (Z)

  • “Inverted Z” curve: slow → rapid → plateau decline.

  • Example: soil salinity tolerance for a crop..

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7. Gaussian

  • Bell curve function.

  • Example: optimal sensitivity of a plant to a specific pH.

  • Parameters: c (center), σ (standard deviation controlling width).

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