Failure mode detection is essential for bearing life prediction to protect the shafts on the machinery. This work demonstrates the rolling bearing vibration measurement, signals converting and analysis, feature extraction, and machine learning with n...
Computational intelligence and neuroscience
Aug 9, 2022
The clinical scores are applied to determine the stage of cognitive function in patients with end-stage renal disease (ESRD). However, accurate clinical scores are hard to come by. This paper proposed an integrated prediction framework with GPLWLSV t...
Computational intelligence and neuroscience
Jun 24, 2022
Based on the risk management of exposure to foreign exchange assets and liabilities and the application of financial derivatives, this paper provides an in-depth analysis of the financial and exchange rate risks of foreign-funded enterprises. Therefo...
Computational intelligence and neuroscience
Jun 24, 2022
Legal judgment prediction (LJP) and decision support aim to enable machines to predict the verdict of legal cases after reading the description of facts, which is an application of artificial intelligence in the legal field. This paper proposes a leg...
In Bourlard and Kamp (Biol Cybern 59(4):291-294, 1998), it was theoretically proven that autoencoders (AE) with single hidden layer (previously called "auto-associative multilayer perceptrons") were, in the best case, implementing singular value deco...
The journal of physical chemistry letters
Jun 21, 2022
Infrared (IR) spectra contain detailed and extensive information about the chemical composition and bonding environment in a sample. However, this information is difficult to extract from complex heterogeneous systems because of overlapping absorptio...
Neural networks : the official journal of the International Neural Network Society
Jun 18, 2022
Random Forest is an ensemble of decision trees based on the bagging and random subspace concepts. As suggested by Breiman, the strength of unstable learners and the diversity among them are the ensemble models' core strength. In this paper, we propos...
Raman spectroscopy is a powerful method for estimating the molecular structure of a target that can be adapted for biomedical analysis given its non-destructive nature. Inflammatory skin diseases impair the skin's barrier function and interfere with ...
This paper proposes a new hybrid framework for short-term load forecasting (STLF) by combining the Feature Engineering (FE) and Bayesian Optimization (BO) algorithms with a Bayesian Neural Network (BNN). The FE module comprises feature selection and ...
Feature extraction algorithms are an important class of unsupervised methods used to reduce data dimensionality. They have been applied extensively for time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging─commonly, matrix factorization (...