Tech Xplore

Study finds 'dosed' nonlinearity can beat linear and fully nonlinear AI

Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...
eLife

Adjoint propagation of error signal through modular recurrent neural networks for biologically plausible learning

Biologically plausible learning mechanisms have implications for understanding brain functions and engineering intelligent systems. Inspired by the multi-scale recurrent connectivity in the brain, we ...
IEEE

A New Improved BP Neural Network Algorithm

Abstract: Neural network is widely used in pattern recognition, image processing and system control. BP neural network has its inherent deficiencies. Its convergence rate is slow. It is easy to fall ...
Frontiers

Seafloor sediment acoustic property inversion from reflection coefficients with a PSO-BP neural network approach

The acoustic properties of seafloor sediments are fundamental parameters for understanding submarine structures, resource exploration, and underwater acoustic field prediction. In geophysical acoustic ...
Frontiers

Frequency coordinated control and parameter optimization for photovoltaic–energy storage systems based on a GA-BP hybrid algorithm

Introduction: Frequency oscillations induced by stochastic disturbances pose significant challenges to grid-connected photovoltaic (PV) systems. This study proposes an adaptive optimization strategy ...
Scientific Research Publishing

Bankruptcy Prediction in the Polish Banking Industry Using Principal Component Analysis and BP Neural Network ()

Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, College of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China. With the ...
IEEE

BP neural network optimized with PSO algorithm and its application in forecasting

Abstract: An approach that neural network optimized with PSO algorithm is proposed in the paper. Unlike conventional training method with gradient descent method only, this paper introduces a hybrid ...