Building the physics-driven mechanism model has always been the core scientific paradigm
for parameter estimation in Earth surface systems, and developing the data-driven machine …

This paper presents numerical analysis and prediction of flow field in a 90° bend using
Artificial Neural Networks (ANN) and Genetic Algorithm (GA). Firstly, a 3D Computational …

The traditional procedure of predicting the settling velocity of a spherical particle is
inconvenient as it involves iterations, complex correlations, and an unpredictable degree of …

Accurate and timely weather prediction is of significance for autonomous vehicles, such as
designing more appropriate sensors or other configurations and developing safer driving …

Multilayer perceptron (MLP), normally trained by the offline backpropagation algorithm,
could not adapt to the changing air quality system and subsequently underperforms. To …

Data assimilation is a method of combining physical observations with prior knowledge (for
instance, a computational simulation) in order to produce an improved estimate of the state …

In turbulent flows, there are very complicated nonlinear behaviors that are influenced by
many indeterminate factors. Currently, Direct Numerical Simulation (DNS) plays a significant …

Data assimilation is a process to combine a model prediction of a state variable at a given
time with a set of measurements available at this particular time in order to obtain a suitable …

There are several methods to forecast precipitation, but none of them is accurate enough
since predicting precipitation is very complicated and influenced by many factors. Data …

A estimação em tempo real é um dos tópicos mais importantes na engenharia,
principalmente em sistemas não-lineares, presentes em praticamente todas as aplicações …