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

AI Experience Predicts Identification with Humankind

(2023) Congyu Wang et al.   Behavioral Sciences

Interpretable machine learning for building energy management: A state-of-the-art review

(2023) Zhe Chen et al.   Advances in Applied Energy

Day-ahead probabilistic forecasting at a co-located wind and solar power park in Sweden: Trading and forecast verification

(2023) O. Lindberg et al.   Advances in Applied Energy

Online Learning: A Comprehensive Survey

(2021) Steven C. H. Hoi et al.   NEUROCOMPUTING

A review on the attention mechanism of deep learning

(2021) Zhaoyang Niu et al.   NEUROCOMPUTING

Theory-guided full convolutional neural network: An efficient surrogate model for inverse problems in subsurface contaminant transport

(2021) Tianhao He et al.   ADVANCES IN WATER RESOURCES

Theory-guided hard constraint projection (HCP): A knowledge-based data-driven scientific machine learning method

(2021) Yuntian Chen et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Deep learning of dynamic subsurface flow via theory-guided generative adversarial network

(2021) Tianhao He et al.   JOURNAL OF HYDROLOGY

Combining transfer learning and constrained long short-term memory for power generation forecasting of newly-constructed photovoltaic plants

(2021) Xing Luo et al.   RENEWABLE ENERGY

Deep Learning of Two-Phase Flow in Porous Media via Theory-Guided Neural Networks

(2021) Jian Li et al.   SPE JOURNAL

Towards Integration of Domain Knowledge-Guided Feature Engineering and Deep Feature Learning in Surface Electromyography-Based Hand Movement Recognition

(2021) Wentao Wei et al.   Computational Intelligence and Neuroscience

Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis

(2021) John W. Goodell et al.   Journal of Behavioral and Experimental Finance

Deep learning of subsurface flow via theory-guided neural network

(2020) Nanzhe Wang et al.   JOURNAL OF HYDROLOGY

Metallurgy, mechanistic models and machine learning in metal printing

(2020) T. DebRoy et al.   Nature Reviews Materials

Deep learning for load forecasting with smart meter data: Online Adaptive Recurrent Neural Network

(2020) Mohammad Navid Fekri et al.   APPLIED ENERGY

A hybrid load forecasting model based on support vector machine with intelligent methods for feature selection and parameter optimization

(2020) Yeming Dai et al.   APPLIED ENERGY

Well Log Generation via Ensemble Long Short‐Term Memory (EnLSTM) Network

(2020) Yuntian Chen et al.   GEOPHYSICAL RESEARCH LETTERS

Computational Intelligence on Short-Term Load Forecasting: A Methodological Overview

(2019) Seyedeh Fallah et al.   Energies

Deep learning framework to forecast electricity demand

(2019) Jatin Bedi et al.   APPLIED ENERGY

Reliable Accuracy Estimates from k-Fold Cross Validation

(2019) Tzu-Tsung Wong et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Ensemble Neural Networks (ENN): A gradient-free stochastic method

(2018) Yuntian Chen et al.   NEURAL NETWORKS

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

(2017) Anuj Karpatne et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Deep Learning for Household Load Forecasting – A Novel Pooling Deep RNN

(2017) Heng Shi et al.   IEEE Transactions on Smart Grid

A systematic design of interval type-2 fuzzy logic system using extreme learning machine for electricity load demand forecasting

(2016) Saima Hassan et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir

(2012) Mohammad Valipour et al.   JOURNAL OF HYDROLOGY

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING