https://github.com/leynier/inferfuzzy

Inferfuzzy es un biblioteca de Python para implementar Sistemas de Inferencia Difusa
https://github.com/leynier/inferfuzzy

cuba fuzzy-logic fuzzy-matching inference-engine inference-rules matcom matcom-uh python python-3 python3 typer

Last synced: 10 days ago
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Inferfuzzy es un biblioteca de Python para implementar Sistemas de Inferencia Difusa

• Host: GitHub
• URL: https://github.com/leynier/inferfuzzy
• Owner: leynier
• License: mit
• Created: 2020-11-23T05:38:50.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-11-26T03:01:15.000Z (over 4 years ago)
• Last Synced: 2025-05-07T23:09:11.642Z (15 days ago)
• Topics: cuba, fuzzy-logic, fuzzy-matching, inference-engine, inference-rules, matcom, matcom-uh, python, python-3, python3, typer
• Language: Python
• Homepage: https://leynier.github.io/inferfuzzy
• Size: 1.78 MB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
# Inferfuzzy

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**Inferfuzzy** is a **Python** library to implement **Fuzzy Inference Systems**.

## Getting started

### Installation

```bash

pip install inferfuzzy

```

### Usage

Creating linguistic variables and their associated fuzzy sets.

```python

variable_1 = Var("variable_name_1")

variable_1 += "set_name_1", ZMembership(1, 2)

variable_1 += "set_name_2", GaussianMembership(3, 2)

variable_1 += "set_name_3", SMembership(4, 6)

variable_2 = Var("variable_name_2")

variable_2 += "set_name_4", GammaMembership(70, 100)

variable_2 += "set_name_5", LambdaMembership(40, 60, 80)

variable_2 += "set_name_6", LMembership(30, 50)

```

Declaring the semantic rules and the inference method to use.

```python

mamdani = MamdaniSystem(defuzz_func=centroid_defuzzification)

mamdani += variable_1.into("set_name_1") | variable_1.into("set_name_3"), variable_2.into("set_name_5")

mamdani += variable_1.into("set_name_2"), variable_2.into("set_name_4")

```

Using fuzzy inference method for user-entered values.

```python

variable_1_val = float(input())

mamdani_result: float = mamdani.infer(variable_name_1=variable_1_val)["variable_name_2"]

```