In this repo is presented a few simple examples where fuzzy logic can be implemented. The soluctions can be scalated with more variables or changing the solution itself using diferent membership functions or even using another models to combine, like control sytems or machine learning solutions. It all depends on the problem to solve.
In this solution the considered variables are humidity (0u - 100u) and temperature (23°C - 27°C) to control water (0° - 360°) and wind (0V - 5V) consumption.
Note that the range and unitis in each variable are just representatives to demostrate the function. Also, the membership functions and the rules are ploted just to visualize them.
A balancing system can be builded with control systems, like a PID controller, however, a fuzzy control can also solve the problem. The variables used are distance (2cm - 32cm) wich is an input and rotation degrees (75° - 105°) as output.
This second example use an error to balance the object.
This last example analize the viability of a Fracking project to know if the environment can be restored to its original state after the extration of the fuel. This example in particular take just a part of the process and must be implemented in other programing lenguage as well to consult an expert in climate change or similar.