Accurate and efficient rotating machinery fault diagnosis is crucial for industries to guarantee
the productivity and reduce the maintenance cost. This paper systematically proposes a new …

Financial time series data is very chaotic, noisy, fluctuating and nonlinear as different events
have occurred in various time periods. Therefore, it is very challenging for researchers to …

The storage and computation requirements of Convolutional Neural Networks (CNNs) can
be prohibitive for exploiting these models over low-power or embedded devices. This paper …

Abstract The recently proposed Relevance Sample-Feature Machine (RSFM) performs joint
feature selection and classification with state-of-the-art performance in terms of accuracy …

A conformal regressor combines conformal prediction and a traditional regressor for point
predictions. It produces a valid prediction interval for a new testing input such that the …

A novel optimisation technique based on the differential evolution (DE) algorithm with
dynamic parameter selection (DPS-DE) is proposed to develop a colour difference …

The self-aligning troughing roller (SATR) is an essential element of the belt conveyor
system. It may fail due to multidimensional forces, derisory lubrication, culpable sealing …

Abstract The Sparse Bayesian Extreme Learning Machine (SBELM) has been recently
proposed to reduce the number of units activated on the hidden layer. To deal with high …

Wybór parametrów w celu optymalizacji regularyzacji wyjściowej maszyny uczącej się —
Fibres & Textiles in Eastern Europe Strona główna O nas Rozwój czasopisma Redakcja …

In current days the intrusion detection systems (IDS) have several shortcomings such as
high rates of false positive alerts, low detection rates of rare but dangerous attacks, and the …