A novel asynchronous deep reinforcement learning model with adaptive early forecasting method and reward incentive mechanism for short-term load forecasting

Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features

(2021) Lechen Li et al.   APPLIED ENERGY

Evolutionary artificial intelligence model via cooperation search algorithm and extreme learning machine for multiple scales nonstationary hydrological time series prediction

(2021) Zhong-kai Feng et al.   JOURNAL OF HYDROLOGY

Load prediction in short-term implementing the multivariate quantile regression

(2020) Yazhou Xing et al.   ENERGY

Load forecasting based on grasshopper optimization and a multilayer feed-forward neural network using regressive approach

(2020) M. Talaat et al.   ENERGY

Using deep learning for short-term load forecasting

(2020) Nadjib Mohamed Mehdi Bendaoud et al.   NEURAL COMPUTING & APPLICATIONS

Modified deep learning and reinforcement learning for an incentive-based demand response model

(2020) Lulu Wen et al.   ENERGY

Detecting botnet by using particle swarm optimization algorithm based on voting system

(2020) Mehdi Asadi et al.   Future Generation Computer Systems-The International Journal of eScience

A hybrid scheme-based one-vs-all decision trees for multi-class classification tasks

(2020) Jianjian Yan et al.   KNOWLEDGE-BASED SYSTEMS

A Deep-Reinforcement-Learning-Based Recommender System for Occupant-Driven Energy Optimization in Commercial Buildings

(2020) Peter Wei et al.   IEEE Internet of Things Journal

Assessment of stacked unidirectional and bidirectional long short-term memory networks for electricity load forecasting

(2020) Sara Atef et al.   ELECTRIC POWER SYSTEMS RESEARCH

A novel stacked generalization ensemble-based hybrid LGBM-XGB-MLP model for Short-Term Load Forecasting

(2020) Mohamed Massaoudi et al.   ENERGY

Comparison of time-frequency-analysis techniques applied in building energy data noise cancellation for building load forecasting: A real-building case study

(2020) Liang Zhang et al.   ENERGY AND BUILDINGS

Parallel computing and swarm intelligence based artificial intelligence model for multi-step-ahead hydrological time series prediction

(2020) Wen-jing Niu et al.   Sustainable Cities and Society

A hybrid method based on neural network and improved environmental adaptation method using Controlled Gaussian Mutation with real parameter for short-term load forecasting

(2019) Priyanka Singh et al.   ENERGY

Multifactor spatio-temporal correlation model based on a combination of convolutional neural network and long short-term memory neural network for wind speed forecasting

(2019) Yong Chen et al.   ENERGY CONVERSION AND MANAGEMENT

A novel dynamic integration approach for multiple load forecasts based on Q‐learning algorithm

(2019) Minhua Ma et al.   International Transactions on Electrical Energy Systems

Predicting residential energy consumption using CNN-LSTM neural networks

(2019) Tae-Young Kim et al.   ENERGY

PwAdaBoost: Possible world based AdaBoost algorithm for classifying uncertain data

(2019) Han Liu et al.   KNOWLEDGE-BASED SYSTEMS

A gradient boosting decision tree based GPS signal reception classification algorithm

(2019) Rui Sun et al.   APPLIED SOFT COMPUTING

Load demand forecasting of residential buildings using a deep learning model

(2019) Lulu Wen et al.   ELECTRIC POWER SYSTEMS RESEARCH

Comparison of three short-term load forecast models in Southern California

(2019) Ning Zhang et al.   ENERGY

Study on deep reinforcement learning techniques for building energy consumption forecasting

(2019) Tao Liu et al.   ENERGY AND BUILDINGS

Continuous control with Stacked Deep Dynamic Recurrent Reinforcement Learning for portfolio optimization

(2019) Amine Mohamed Aboussalah et al.   EXPERT SYSTEMS WITH APPLICATIONS

Reinforced Deterministic and Probabilistic Load Forecasting via $Q$ -Learning Dynamic Model Selection

(2019) Cong Feng et al.   IEEE Transactions on Smart Grid

A Resampling Based Grid Search Method to Improve Reliability and Robustness of Mixture-Item Response Theory Models of Multimorbid High-Risk Patients

(2019) Adam J. Batten et al.   IEEE Journal of Biomedical and Health Informatics

Data-driven predictive control of molten iron quality in blast furnace ironmaking using multi-output LS-SVR based inverse system identification

(2018) Ping Zhou et al.   NEUROCOMPUTING

Review on probabilistic forecasting of photovoltaic power production and electricity consumption

(2018) D.W. van der Meer et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

On-line Building Energy Optimization using Deep Reinforcement Learning

(2018) Elena Mocanu et al.   IEEE Transactions on Smart Grid

Short-term electricity load forecasting based on feature selection and Least Squares Support Vector Machines

(2018) Ailing Yang et al.   KNOWLEDGE-BASED SYSTEMS

Model-Free Real-Time EV Charging Scheduling Based on Deep Reinforcement Learning

(2018) Zhiqiang Wan et al.   IEEE Transactions on Smart Grid

Convolutional Neural Network approaches to granite tiles classification

(2017) Anselmo Ferreira et al.   EXPERT SYSTEMS WITH APPLICATIONS

A review and analysis of regression and machine learning models on commercial building electricity load forecasting

(2017) B. Yildiz et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

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

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

Recognizing human activities from smartphone sensors using hierarchical continuous hidden Markov models

(2017) Charissa Ann Ronao et al.   International Journal of Distributed Sensor Networks

Deep Neural Network Based Demand Side Short Term Load Forecasting

(2016) Seunghyoung Ryu et al.   Energies

Reinforcement learning approach for train rescheduling on a single-track railway

(2016) D. Šemrov et al.   TRANSPORTATION RESEARCH PART B-METHODOLOGICAL

Hybrid methodologies for electricity load forecasting: Entropy-based feature selection with machine learning and soft computing techniques

(2015) Sergio Jurado et al.   ENERGY

Modeling and forecasting of cooling and electricity load demand

(2014) A. Vaghefi et al.   APPLIED ENERGY

Short-Term Load Forecasting: Similar Day-Based Wavelet Neural Networks

(2009) Ying Chen et al.   IEEE TRANSACTIONS ON POWER SYSTEMS