Effective machine learning model combination based on selective ensemble strategy for time series forecasting

Forecasting natural gas consumption using Bagging and modified regularization techniques

(2022) Erick Meira et al.   ENERGY ECONOMICS

Bayesian optimization based dynamic ensemble for time series forecasting

(2022) Liang Du et al.   INFORMATION SCIENCES

An optimized twin support vector regression algorithm enhanced by ensemble empirical mode decomposition and gated recurrent unit

(2022) Shifei Ding et al.   INFORMATION SCIENCES

A Backpropagation Learning Algorithm with Graph Regularization for Feedforward Neural Networks

(2022) Yetian Fan et al.   INFORMATION SCIENCES

Prediction of wind turbine blade icing fault based on selective deep ensemble model

(2022) Jin Xiao et al.   KNOWLEDGE-BASED SYSTEMS

Using support vector regression and K-nearest neighbors for short-term traffic flow prediction based on maximal information coefficient

(2022) Guancen Lin et al.   INFORMATION SCIENCES

A manufacturing quality prediction model based on AdaBoost-LSTM with rough knowledge

(2021) Yun Bai et al.   COMPUTERS & INDUSTRIAL ENGINEERING

Forecasting Nickel futures price based on the empirical wavelet transform and gradient boosting decision trees

(2021) Qinghua Gu et al.   APPLIED SOFT COMPUTING

Multi-step-ahead crude oil price forecasting based on two-layer decomposition technique and extreme learning machine optimized by the particle swarm optimization algorithm

(2021) Tingting Zhang et al.   ENERGY

Forecast combination with meta possibilistic fuzzy functions

(2021) Nihat Tak   INFORMATION SCIENCES

Probabilistic wind power forecasting using selective ensemble of finite mixture Gaussian process regression models

(2021) Huaiping Jin et al.   RENEWABLE ENERGY

Strategies for time series forecasting with generalized regression neural networks

(2021) Francisco Martínez et al.   NEUROCOMPUTING

A Hybrid System Based on Dynamic Selection for Time Series Forecasting

(2021) Joao F. L. de Oliveira et al.   IEEE Transactions on Neural Networks and Learning Systems

A new hybrid method for predicting univariate and multivariate time series based on pattern forecasting

(2021) M.A. Castán-Lascorz et al.   INFORMATION SCIENCES

Bayesian Optimized Echo State Network Applied to Short-Term Load Forecasting

(2020) Gabriel Trierweiler Ribeiro et al.   Energies

A combined forecasting system based on modified multi-objective optimization and sub-model selection strategy for short-term wind speed

(2020) Qingguo Zhou et al.   APPLIED SOFT COMPUTING

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

(2020) Mohammad Navid Fekri et al.   APPLIED ENERGY

Improving the wide-area PMU-based fault location method using ordinary least squares estimation

(2020) A. Mouco et al.   ELECTRIC POWER SYSTEMS RESEARCH

A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities

(2020) Sergio González et al.   Information Fusion

A novel ensemble deep learning model with dynamic error correction and multi-objective ensemble pruning for time series forecasting

(2020) Shuai Zhang et al.   INFORMATION SCIENCES

A hybrid deep meta-ensemble networks with application in electric utility industry load forecasting

(2020) Shaohui Ma   INFORMATION SCIENCES

Multi-temporal-spatial-scale temporal convolution network for short-term load forecasting of power systems

(2020) Linfei Yin et al.   APPLIED ENERGY

Electrical load forecasting: A deep learning approach based on K-nearest neighbors

(2020) Yunxuan Dong et al.   APPLIED SOFT COMPUTING

A developed hybrid forecasting system for energy consumption structure forecasting based on fuzzy time series and information granularity

(2020) Ping Jiang et al.   ENERGY

Advantages of direct input-to-output connections in neural networks: The Elman network for stock index forecasting

(2020) Yaoli Wang et al.   INFORMATION SCIENCES

A novel method for time series prediction based on error decomposition and nonlinear combination of forecasters

(2020) Wei Chen et al.   NEUROCOMPUTING

A hybrid neural network model for short-term wind speed forecasting based on decomposition, multi-learner ensemble, and adaptive multiple error corrections

(2020) Hui Liu et al.   RENEWABLE ENERGY

Short-Term Load Forecasting in Smart Grids: An Intelligent Modular Approach

(2019) Ashfaq Ahmad et al.   Energies

Enhanced ensemble structures using wavelet neural networks applied to short-term load forecasting

(2019) Gabriel Trierweiler Ribeiro et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

A hybrid optimized error correction system for time series forecasting

(2019) João Fausto Lorenzato de Oliveira et al.   APPLIED SOFT COMPUTING

Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series

(2019) Matheus Henrique Dal Molin Ribeiro et al.   APPLIED SOFT COMPUTING

Holt–Winters smoothing enhanced by fruit fly optimization algorithm to forecast monthly electricity consumption

(2019) Weiheng Jiang et al.   ENERGY

A note on the validity of cross-validation for evaluating autoregressive time series prediction

(2018) Christoph Bergmeir et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Layered Ensemble Architecture for Time Series Forecasting

(2016) Md. Mustafizur Rahman et al.   IEEE Transactions on Cybernetics