An attention mechanism-based deep regression approach with a sequence decomposition-granularity reconstruction-integration model for urban daily water supply forecasting

Short-term multi-energy load forecasting for integrated energy systems based on CNN-BiGRU optimized by attention mechanism

(2022) Dongxiao Niu et al.   APPLIED ENERGY

Interval forecasting for urban water demand using PSO optimized KDE distribution and LSTM neural networks

(2022) Baigang Du et al.   APPLIED SOFT COMPUTING

Short term electricity price forecasting using a new hybrid model based on two-layer decomposition technique and ensemble learning

(2022) Tingting Zhang et al.   ELECTRIC POWER SYSTEMS RESEARCH

Short-term wind power forecasting based on Attention Mechanism and Deep Learning

(2022) Bangru Xiong et al.   ELECTRIC POWER SYSTEMS RESEARCH

Water quality forecasting based on data decomposition, fuzzy clustering and deep learning neural network

(2022) Jin-Won Yu et al.   ENVIRONMENTAL POLLUTION

Accurate prediction of water quality in urban drainage network with integrated EMD-LSTM model

(2022) Yituo Zhang et al.   Journal of Cleaner Production

Multi-scale deep neural network approach with attention mechanism for remaining useful life estimation

(2022) Ahmet Kara   COMPUTERS & INDUSTRIAL ENGINEERING

An evolutionary deep learning model based on TVFEMD, improved sine cosine algorithm, CNN and BiLSTM for wind speed prediction

(2022) Chu Zhang et al.   ENERGY

Forecasting the realized volatility of stock price index: A hybrid model integrating CEEMDAN and LSTM

(2022) Yu Lin et al.   EXPERT SYSTEMS WITH APPLICATIONS

Development and application of an evolutionary deep learning framework of LSTM based on improved grasshopper optimization algorithm for short-term load forecasting

(2022) Haowen Hu et al.   Journal of Building Engineering

A classification-based deep belief networks model framework for daily streamflow forecasting

(2021) Haibo Chu et al.   JOURNAL OF HYDROLOGY

Probabilistic urban water demand forecasting using wavelet-based machine learning models

(2021) Mostafa Rezaali et al.   JOURNAL OF HYDROLOGY

A study on water quality prediction by a hybrid CNN-LSTM model with attention mechanism

(2021) Yurong Yang et al.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

Deep learning with long short-term memory neural networks combining wavelet transform and principal component analysis for daily urban water demand forecasting

(2021) Baigang Du et al.   EXPERT SYSTEMS WITH APPLICATIONS

Novel double-layer bidirectional LSTM network with improved attention mechanism for predicting energy consumption

(2021) Yan-Lin He et al.   ISA TRANSACTIONS

Classification of flower image based on attention mechanism and multi-loss attention network

(2021) Mei Zhang et al.   COMPUTER COMMUNICATIONS

A new scheme for probabilistic forecasting with an ensemble model based on CEEMDAN and AM-MCMC and its application in precipitation forecasting

(2021) Yinan Wang et al.   EXPERT SYSTEMS WITH APPLICATIONS

A novel attention-based LSTM cell post-processor coupled with bayesian optimization for streamflow prediction

(2021) Babak Alizadeh et al.   JOURNAL OF HYDROLOGY

Fault diagnosis for small samples based on attention mechanism

(2021) Xin Zhang et al.   MEASUREMENT

Short-term load forecasting based on LSTM networks considering attention mechanism

(2021) Jun Lin et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

A One-Class Generative Adversarial Detection Framework for Multifunctional Fault Diagnoses

(2021) Ziqiang Pu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Decomposition ensemble model based on variational mode decomposition and long short-term memory for streamflow forecasting

(2020) Ganggang Zuo et al.   JOURNAL OF HYDROLOGY

Short-Term Water Demand Forecasting Using Nonlinear Autoregressive Artificial Neural Networks

(2020) Mo’tamad H. Bata et al.   JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT

A Method for Predicting Long-Term Municipal Water Demands Under Climate Change

(2020) Salah L. Zubaidi et al.   WATER RESOURCES MANAGEMENT

A new short-term wind speed forecasting method based on fine-tuned LSTM neural network and optimal input sets

(2020) Gholamreza Memarzadeh et al.   ENERGY CONVERSION AND MANAGEMENT

Water demand forecasting accuracy and influencing factors at different spatial scales using a Gradient Boosting Machine

(2020) M. Xenochristou et al.   WATER RESOURCES RESEARCH

Hybrid Models for Water Demand Forecasting

(2020) Prerna Pandey et al.   JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT

Machine Learning for Modeling Water Demand

(2019) Maria C. Villarin et al.   JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT

Hydrological modelling of karst catchment using lumped conceptual and data mining models

(2019) Cenk Sezen et al.   JOURNAL OF HYDROLOGY

Predicting water demand: a review of the methods employed and future possibilities

(2019) Gustavo de Souza Groppo et al.   Water Science and Technology-Water Supply

Attention-based recurrent neural networks for accurate short-term and long-term dissolved oxygen prediction

(2019) Yeqi Liu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Predicting monthly biofuel production using a hybrid ensemble forecasting methodology

(2019) Lean Yu et al.   INTERNATIONAL JOURNAL OF FORECASTING

Prediction of dissolved oxygen in aquaculture based on EEMD and LSSVM optimized by the Bayesian evidence framework

(2018) Juan Huan et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Short-term wind speed forecasting based on fast ensemble empirical mode decomposition, phase space reconstruction, sample entropy and improved back-propagation neural network

(2018) Wei Sun et al.   ENERGY CONVERSION AND MANAGEMENT

Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition

(2018) Ramendra Prasad et al.   GEODERMA

Reservoir Inflow Forecast Using a Clustered Random Deep Fusion Approach in the Three Gorges Reservoir, China

(2018) Yun Bai et al.   JOURNAL OF HYDROLOGIC ENGINEERING

Water demand time series generation for distribution network modeling and water demand forecasting

(2018) Bruno Melo Brentan et al.   Urban Water Journal

Prediction of daily diffuse solar radiation using artificial neural networks

(2017) Xinhua Xue   INTERNATIONAL JOURNAL OF HYDROGEN ENERGY

A time varying filter approach for empirical mode decomposition

(2017) Heng Li et al.   SIGNAL PROCESSING

Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models

(2016) Yun Bai et al.   JOURNAL OF HYDROLOGY

Deep Feature Learning Architectures for Daily Reservoir Inflow Forecasting

(2016) Chuan Li et al.   WATER RESOURCES MANAGEMENT

Does model performance improve with complexity? A case study with three hydrological models

(2015) Rene Orth et al.   JOURNAL OF HYDROLOGY

A multi-scale relevance vector regression approach for daily urban water demand forecasting

(2014) Yun Bai et al.   JOURNAL OF HYDROLOGY

Statistical modeling of daily urban water consumption in Hong Kong: Trend, changing patterns, and forecast

(2010) Jefferson See Wong et al.   WATER RESOURCES RESEARCH

Identifying the Relationships Between Urban Water Consumption and Weather Variables in Seoul, Korea

(2009) Sarah Praskievicz et al.   PHYSICAL GEOGRAPHY