Abstract: The multistep-ahead prediction is one of the most challenging problems in the field of soft sensing. Traditional time-series prediction methods for soft-sensing applications cannot fully ...

Abstract: In the era of artificial intelligence, the complexity and diversity of data have posed unprecedented challenges for prediction tasks. Fuzzy information granules (FIGs) have emerged as a ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two widely used neuroimaging techniques, with complementary strengths and weaknesses. Predicting fMRI activity from ...

State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China ...

The package contains a mixture of classic decoding methods and modern machine learning methods. For regression, we currently include: Wiener Filter, Wiener Cascade, Kalman Filter, Naive Bayes, Support ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...

ABSTRACT: Intelligent vehicles require strong cybersecurity. The 2021 UNECE WP.29 regulation mandates OEMs to establish Vehicle Security Operation Centers (VSOC), where Intrusion Detection Systems ...

The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...