This review article examines recent advances in the use of machine learning for process
industries. The article presents common process industry tasks that researchers are solving …

In the collaborative filtering (CF) recommendation applications, the sparsity of user rating
data, the effectiveness of cold start, the strategy of item information neglection, and user …

An initiating event (IE) is an event that may lead to core damage in a nuclear power plant
(NPP), and being able to identify an IE is crucial in determining what actions to take. This …

In this paper, some important operating parameters of nuclear power plants (NPPs)
transients are forecasted using different supervised learning methods including feed-forward …

The timely detection of special nuclear material (SNM) transfers between nuclear facilities is
an important monitoring objective in nuclear nonproliferation. Persistent monitoring enabled …

Industrial processes can be affected by faults having a serious impact on operation when not
promptly detected and diagnosed. In this paper, a propagation …

Up to now, different methods have been developed for estimation of buildup factor (BF).
However, either expensive estimation or time-consuming estimation are major …

Data analysis techniques can be powerful tools for rapidly analyzing data and extracting
information that can be used in a latent space for categorizing observations between classes …

The present article applies the-nearest neighbors (-NN) machine learning (ML) algorithm to
detect and correct single-event upsets (SEUs). In particular, this work focuses on SEUs …

In this study, we propose a new method for identification of nuclear power plants (NPPs)
transients based on online dynamic quantum clustering (DQC). In this unsupervised …