On the second day of Mayo Clinic's AI Summit in Rochester, Dr. Matthew Callstrom shared where the health system stands with its use of generative artificial intelligence tools.

This paper presents an implementation of a three phase distribution static compensator (DSTATCOM) using a back propagation (BP) control algorithm for its functions such as harmonic elimination, load ...

To reduce the impact of wildfires on the operation of power systems, a back-propagation neural network (BPNN) model is used to evaluate the wildfire risk distribution after feature selection. Data ...

To reduce the impact of wildfires on the operation of power systems, a back-propagation neural network (BPNN) model is used to evaluate the wildfire risk distribution after feature selection.

WAP to implement back propagation algorithm and analyze the performance of your NN model using any one type of performance analysis method. This program was written to use of back propagation neural ...

Optimizer function in Back propagation algorithm are responsible for reducing the losses and to provide prediction the most accurate results. An Back propagation algorithm with feature engineering was ...

Back Propagation is a common method of training artificial neural networks so as to minimize objective function. This paper describes the implementation of back propagation algorithm.