[HTML][HTML] An adaptive deep-learning load forecasting framework by integrating transformer and domain knowledge

J Gao, Y Chen, W Hu, D Zhang - Advances in Applied Energy, 2023‏ - Elsevier
Electrical energy is essential in today's society. Accurate electrical load forecasting is
beneficial for better scheduling of electricity generation and saving electrical energy. In this …

[HTML][HTML] Theory-guided deep-learning for electrical load forecasting (TgDLF) via ensemble long short-term memory

Y Chen, D Zhang - Advances in Applied Energy, 2021‏ - Elsevier
Electricity constitutes an indispensable source of secondary energy in modern society.
Accurate and robust short-term electrical load forecasting is essential for more effective …

Missing well logs prediction using deep learning integrated neural network with the self-attention mechanism

J Wang, J Cao, J Fu, H Xu - Energy, 2022‏ - Elsevier
Well logs are employed for analyzing lithology, determining formation parameters, and
evaluating oil and gas reservoirs. However, in practice, well logs are often incomplete or …

S-wave velocity inversion and prediction using a deep hybrid neural network

J Wang, J Cao, S Zhao, Q Qi - Science China Earth Sciences, 2022‏ - Springer
The S-wave velocity is a critical petrophysical parameter in reservoir description, prestack
seismic inversion, and geomechanical analysis. However, obtaining the S-wave velocity …

An expert system for insect pest population dynamics prediction

EA Ibrahim, D Salifu, S Mwalili, T Dubois… - … and Electronics in …, 2022‏ - Elsevier
Avocado (Persea americana) production is increasing in Kenya, with both small and
largeholder farming for domestic and export markets. However, one of main challenges that …

Missing sonic logs generation for gas hydrate-bearing sediments via hybrid networks combining deep learning with rock physics modeling

Z Li, J **a, Z Liu, G Lei, K Lee… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Logging-while-drilling (LWD) sonic data are critical for marine gas hydrate reservoir
evaluation and production prediction. However, acquiring complete acoustic logs …

A vector-to-sequence based multilayer recurrent network surrogate model for history matching of large-scale reservoir

X Ma, K Zhang, H Zhao, L Zhang, J Wang… - Journal of Petroleum …, 2022‏ - Elsevier
History matching can estimate the parameter of spatially varying geological properties and
provide reliable numerical models for reservoir development and management. However, in …

A method for well log data generation based on a spatio-temporal neural network

J Wang, J Cao, J You, M Cheng… - Journal of Geophysics …, 2021‏ - academic.oup.com
Well logging helps geologists find hidden oil, natural gas and other resources. However,
well log data are systematically insufficient because they can only be obtained by drilling …

Eeg daydreaming, a machine learning approach to detect daydreaming activities

R Wang, X Qu - International Conference on Human-Computer …, 2022‏ - Springer
In this paper, we propose a new method to detect noise hindrances in
Electroencephalographic (EEG) signals caused by mental distractions, which we named …

Well logs reconstruction of petroleum energy exploration based on bidirectional Long Short-term memory networks with a PSO optimization algorithm

H Zhang, W Wu, Z Chen, J **g - Geoenergy Science and Engineering, 2024‏ - Elsevier
During petroleum energy exploration, estimating missing well logs from existing logging
data is very meaningful. Due to a highly nonlinear relationship between various logging data …