BACKGROUND: Forecasts for the future prevalence of cardiovascular disease and stroke are crucial to guide efforts to improve health outcomes across the life course for women. METHODS: Using historical ...
The rapid growth of large-scale neuroscience datasets has spurred diverse modeling strategies, ranging from mechanistic models grounded in biophysics, to phenomenological descriptions of neural ...
Adequate mathematical modeling is the key to success for many real-world projects in engineering, medicine, and other applied areas. Once a well-suited model is established, it can be thoroughly ...
In the design of major hydraulic structures, a key element is the design discharge, determined from the time series of flow or through runoff models such as the rational method, which relates the peak ...
To mathematicians, equations are art. Just as many are moved by a painting or piece of music, to those who appreciate and understand math, expressions of numbers, variables, operations and relations ...
Abstract: State-of-charge (SOC) estimation is crucial for improving the safety, reliability, and performance of the battery. Neural networks-based methods for battery SOC estimation have received ...
Abstract: This article proposes a physics-informed long-short-term memory neural network optimisation method to estimate all parameters of an arbitrary nonlinear system initialised using any initial ...
ABSTRACT: The operator T from a domain D into the space of measurable functions is called a nonanticipating (causal) operator if the past information is independent from the future outputs. We will ...
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