Short-term natural gas consumption prediction based on Volterra adaptive filter and improved whale optimization algorithm
W Qiao, Z Yang, Z Kang, Z Pan - Engineering Applications of Artificial …, 2020 - Elsevier
Short-term natural gas consumption prediction is an important indicator of natural gas
pipeline network planning and design, which is of great significance. The purpose of this …
pipeline network planning and design, which is of great significance. The purpose of this …
Statistical inference for stochastic differential equations
P Craigmile, R Herbei, G Liu… - Wiley Interdisciplinary …, 2023 - Wiley Online Library
Many scientific fields have experienced growth in the use of stochastic differential equations
(SDEs), also known as diffusion processes, to model scientific phenomena over time. SDEs …
(SDEs), also known as diffusion processes, to model scientific phenomena over time. SDEs …
LOWESS smoothing and Random Forest based GRU model: A short-term photovoltaic power generation forecasting method
Y Dai, Y Wang, M Leng, X Yang, Q Zhou - Energy, 2022 - Elsevier
Accurate prediction of photovoltaic power generation is vital to guarantee smooth operation
of power stations and ensure users' electricity consumption. As a good forecasting tool …
of power stations and ensure users' electricity consumption. As a good forecasting tool …
A two-layer water demand prediction system in urban areas based on micro-services and LSTM neural networks
In recent years, scarce water resources became one of the main problems that endanger
human species existence and the advancement of any nation. In this research, smart water …
human species existence and the advancement of any nation. In this research, smart water …
Ares and mars adversarial and mmd-minimizing regression for sdes
G Abbati, P Wenk, MA Osborne… - International …, 2019 - proceedings.mlr.press
Stochastic differential equations are an important modeling class in many disciplines.
Consequently, there exist many methods relying on various discretization and numerical …
Consequently, there exist many methods relying on various discretization and numerical …
Numerically robust square root implementations of statistical linear regression filters and smoothers
F Tronarp - arXiv preprint arXiv:2406.05188, 2024 - arxiv.org
In this article, square-root formulations of the statistical linear regression filter and smoother
are developed. Crucially, the method uses QR decompositions rather than Cholesky …
are developed. Crucially, the method uses QR decompositions rather than Cholesky …
基于电动汽车制动安全检测的短时工况及方法研究
焦志鹏， 马建， 赵轩， 张凯， 孟德安， 韩琪， 张昭 - 汽车工程, 2024 - qichegongcheng.com
常规的制动安全检测通常采用长时间, 极端工况, 但可能会失去准确的工作范围. 针对这一不足,
首先提出一种踏板稳定模式的短时工况试验方法, 该方法结合了现有的测试标准 …
首先提出一种踏板稳定模式的短时工况试验方法, 该方法结合了现有的测试标准 …
Taylor moment expansion for continuous-discrete Gaussian filtering and smoothing
The paper is concerned with non-linear Gaussian filtering and smoothing in continuous-
discrete state-space models, where the dynamic model is formulated as an It\^{o} stochastic …
discrete state-space models, where the dynamic model is formulated as an It\^{o} stochastic …
Learning probabilistic representations for inference, training and interpretability
G Abbati - 2020 - ora.ox.ac.uk
For decades, the holy grail of many fields of science, mathematics and statistics has been
the ability to predict the future or, more quantitatively, to forecast the behaviours of quantities …
the ability to predict the future or, more quantitatively, to forecast the behaviours of quantities …