Risk analysis : an official publication of the Society for Risk Analysis
Apr 21, 2022
For several years machine learning methods have been proposed for risk classification. While machine learning methods have also been used for failure diagnosis and condition monitoring, to the best of our knowledge, these methods have not been used f...
Foreground object segmentation is a crucial first step for surveillance systems based on networks of video sensors. This problem in the context of dynamic scenes has been widely explored in the last two decades, but it still has open research questio...
Nutritional epidemiology employs observational data to discover associations between diet and disease risk. However, existing analytic methods of dietary data are often sub-optimal, with limited incorporation and analysis of the correlations between ...
This article investigates the state estimation issue of discrete-time Takagi-Sugeno fuzzy Markov jump affine systems that cover both traditional fuzzy Markov jump systems and fuzzy affine systems as two special cases. The original system is transform...
Traffic conflict techniques represent the state-of-the-art for road safety assessments. However, the lack of research on transferability of conflict-based crash risk models, which refers to applying the developed crash risk estimation models to a set...
Computational intelligence and neuroscience
Mar 28, 2022
How to facilitate users to quickly and accurately search for the text information they need is a current research hotspot. Text clustering can improve the efficiency of information search and is an effective text retrieval method. Keyword extraction ...
By classifying patients into subgroups, clinicians can provide more effective care than using a uniform approach for all patients. Such subgroups might include patients with a particular disease subtype, patients with a good (or poor) prognosis, or p...
Neural networks : the official journal of the International Neural Network Society
Feb 25, 2022
This paper proposes a new hierarchical approach to learning rate adaptation in gradient methods, called learning rate optimization (LRO). LRO formulates the learning rate adaption problem as a hierarchical optimization problem that minimizes the loss...
BACKGROUND AND OBJECTIVE: Tuberculosis (Tuberculosis, TB) is a public health problem in China, which not only endangers the population's health but also affects economic and social development. It requires an accurate prediction analysis to help to m...