Abstract The Bayesian Network (BN) is one of the most effective theoretical models in the
fields of uncertain reasoning. With the nonlinear evolution of events and the complexity of …

Most traditional decision making methods cannot deal with intensive uncertain data that
varies with time effectively, and they only derive the static risk analysis by different …

Generally, in the qualitative decision-making process, the attributes are independent of each
other, thus the given attributes' evaluation data could ignore their connection relationships …

The logistic regression model is one of the most widely used classification models. In some
practical situations, few samples and massive uncertain information bring more challenges …

At present, research on hesitant fuzzy operations and measures is based on equal length
processing, and an equal length processing method will inevitably destroy the original data …

Artificial intelligence (AI) is the most popular technology for searching the natural essence of
human beings' intelligence. AI is influencing the paradigm of the enterprise management …

Epidemics can bring huge impacts to economic operation and human health, a practical and
effective emergency decision-making (EDM) method is of great significance to reduce all …

Hesitant fuzzy set (HFS) can express the hesitancy and uncertainty according to human's
cognitions and knowledge. The decision making with HFSs can be regarded as a cognitive …

The generalized regression neural network (GRNN) is one of the most effective neural
models in the field of information prediction. In this paper, we take advantage of the hesitant …

For decision-making in a highly uncertain environment, experts may be unable to accurately
express or even neglect some deep latent uncertain information, leading to decision bias …