Although the primary use for Fuzzy Pattern Recognizer indicators is in Trading Strategy rules (conditions), you can also feed them into neural nets or other indicators.

To use Fuzzy Indicators as inputs to neural nets, just specify them as inputs. You can use them as inputs to other add-ons too, such as Adaptive Net Indicators, Neural Indicators, and Adaptive Turboprop2. Note that if you are optimizing neural network inputs, each of the Fuzzy Indicator parameters will be optimized as well. So there might be quite a bit of optimization going on if you use too many Fuzzy Indicators.

Note:  The Fuzzy Indicator output may be quite sparse; it may contain a lot of zeros and just a few non-zero output values depending on the input parameters. You should exercise caution when using Fuzzy Pattern Recognizer Indicators as inputs to neural networks since neural nets do not respond well to sparse inputs. The more segments in your fuzzy rule, the more sparse the non-zero Fuzzy Indicator outputs are likely to be. You can feel comfortable with Fuzzy1 and FuzzyGA1 as neural net inputs, but we wouldn't go above Fuzzy2 and FuzzyGA2.