C&EN

Hybrid Quantum Neural Network Model with Catalyst Experimental Validation: Application for the Dry Reforming of Methane

Green Materials and Processes R&D Group, Korea Institute of Industrial Technology, Ulsan 44413, Republic of Korea Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei-ro, ...
C&EN

High-Precision Microscale Particulate Matter Prediction in Diverse Environments Using a Long Short-Term Memory Neural Network and Street View Imagery

Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer Science and Engineering, Beijing Technology and Business University, Beijing 100048, China State Key Laboratory of ...
IEEE

An Efficient Electrothermal Coupling Simulation Method Based on Neural Network-Aided Power Loss Model for Power Module Thermal Optimization

Abstract: This article introduces a highly efficient electrothermal coupling simulation method that leverages a data-driven neural network power loss model to enhance the simulation efficiency in the ...
Hosted on MSN

Backpropagation from Scratch in Python – Step by Step Neural Network Tutorial

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...
IEEE

Multiobjective Evolution of the Deep Fuzzy Rough Neural Network

Abstract: Deep learning has made remarkable achievements in many fields. However, although fuzzy neural networks with natural interpretability are widely used in prediction and control scenarios, ...