Deep learning for time series forecasting: a survey
Time series forecasting has become a very intensive field of research, which is even
increasing in recent years. Deep neural networks have proved to be powerful and are …
increasing in recent years. Deep neural networks have proved to be powerful and are …
Development of a vision based pose estimation system for robotic machining and improving its accuracy using LSTM neural networks and sparse regression
In this work, an eye to hand camera based pose estimation system is developed for robotic
machining and the accuracy of the estimated pose is improved using two different …
machining and the accuracy of the estimated pose is improved using two different …
A comparative investigation of advanced machine learning methods for predicting transient emission characteristic of diesel engine
Abstract Machine learning method provides a promising way to predict the transient
emission characteristic of diesel engine due to its many advantages such as short …
emission characteristic of diesel engine due to its many advantages such as short …
A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling
Ten established, data-driven dynamic algorithms are surveyed and a practical guide for
understanding these methods generated. Existing Python programming packages for …
understanding these methods generated. Existing Python programming packages for …
Prediction of the transient emission characteristics from diesel engine using temporal convolutional networks
J Liao, J Hu, P Chen, L Zhu, Y Wu, Z Cai, H Wu… - … Applications of Artificial …, 2024 - Elsevier
In order to predict the transient emission characteristics from diesel engine accurately and
quickly, a novel prediction model, based on temporal convolutional networks (TCN) that …
quickly, a novel prediction model, based on temporal convolutional networks (TCN) that …
Exploring soot inception rate with stochastic modelling and machine learning
A diverse range of polycyclic aromatic compounds (PACs) is thought to exist in flame
environments before and during soot inception. This work seeks to develop a machine …
environments before and during soot inception. This work seeks to develop a machine …
Excitation signal design and modeling benchmark of nox emissions of a diesel engine
V Smits, M Schüssler, G Kampmann… - … IEEE Conference on …, 2022 - ieeexplore.ieee.org
This paper focuses on two aspects of the nitrogen oxides (NOx) emissions modeling process
of a Diesel engine. Firstly, a novel design of experiments (DoE) strategy with an amplitude …
of a Diesel engine. Firstly, a novel design of experiments (DoE) strategy with an amplitude …
Engine combustion modeling method based on hybrid drive
D Hu, H Wang, C Yang, B Wang, B Duan, Y Wang - Heliyon, 2023 - cell.com
Accurate and comprehensive reconstruction of in-cylinder combustion process is essential
for timely monitoring of engine combustion state. This article developed a method based on …
for timely monitoring of engine combustion state. This article developed a method based on …
A long short-term memory neural network for the low-cost prediction of soot concentration in a time-dependent flame
Particulate matter (soot) emissions from combustion processes have damaging health and
environmental effects. Numerical techniques with varying levels of accuracy and …
environmental effects. Numerical techniques with varying levels of accuracy and …
A mixed ensemble learning and time-series methodology for category-specific vehicular energy and emissions modeling
E Moradi, L Miranda-Moreno - Sustainability, 2022 - mdpi.com
The serially-correlated nature of engine operation is overlooked in the vehicular fuel and
emission modeling literature. Furthermore, enabling the calibration and use of time-series …
emission modeling literature. Furthermore, enabling the calibration and use of time-series …