Scientific Research Publishing

Asaad, R.R. and Ali, R.I. (2019) Back Propagation Neural Network (BPNN) and Sigmoid Activation Function in Multi-Layer Networks. Academic Journal of Nawroz University, 8, 216-221.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
Hosted on MSN

20 Activation Functions in Python for Deep Neural Networks – ELU, ReLU, Leaky-ReLU, Sigmoid, Cosine

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python Supreme Court ...
Semiconductor Engineering

Implementing AI Activation Functions

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...
SciELO

Paraconsistent Artificial Neural Network (PANnet) applied to the Detection of (NOx) Nitrogen Oxides Emissions in Petrochemical Combustion Systems

The emissions of nitrogen oxides (NOx) that are produced during the combustion of fossil fuels in the petrochemical and metallurgical industries, when combined with other types of pollutants, can have ...
IEEE

Universal approximation of nonlinear system predictions in sigmoid activation functions using artificial neural networks

Abstract: The sigmoid activation function cast-off to convert the equal of activation of units (neurons) in the output indicator. There are a numeral of mutual tasks in activation with the use of ...