Illegal practices that cause stock prices to vary from their fair values are known as stock price
manipulations. Our prior study used unsupervised deep learning to detect these unlawful …

In this paper, we extend the concept of Dempster-Shafer Belief Structures to the case of
Linguistic Belief Structures, whose focal elements and probability mass assignments are …

Uncertain information processing is a key problem in classification. Dempster-Shafer
evidence theory (DS evidence theory) is widely used in uncertain information modelling and …

Test case prioritization (TCP) aims at scheduling test case execution so that more important
test cases are executed as early as possible. Many TCP techniques have been proposed …

One possible type of base classifier output is a scoring function, which can be regarded as
the probability that the class label is the true one. The measurement expressed by the score …

Comparing the probability distribution, basic probability assignment in evidence theory is
more efficient to deal with uncertain information. However, the uncertainty measure of basic …

Classifiers now demonstrate impressive performances in many domains. However, in some
applications where the cost of an erroneous decision is high, set-valued predictions may be …

This study aims to exploit multisource remotely sensed data to improve land cover
classification of an area dominated by extensive wetlands with surface cover complexity …

Aims: Producing a land use/land cover map is a fundamental step in different studies. This
study aimed to assess the ability of hierarchical, pixel-based and object-oriented …

In recent years, drought has affected villagers' resilience to natural disasters. In this study,
Fars Province, Iran, was selected as a result of various water-related social conflicts. A …