Neuron Model for Input Uncertainty

Abstract

The application of the Neuron Network model has not given optimal results on learning with input values ​​that are not binary, uncertain and varied. Variable inputs are not only 1 and 0 but allow between 0 and 1. and linguistic input and output and non-linear models. And the verification process for reviewing feasibility is reviewed from network, unit, behavior and procedural aspects. Further validation is done on the control module of the waterwheel rotation with dissolved oxygen input, water pH, salinity and water temperature varies. With such neuron models being the solution to varied and uncertain neuron models. The simulation is done withMatrix Laboratory software.

Keywords: Neuron, Uncertainty, Waterwheel.