Hierarchical delay-memory echo state network: A model designed for multi-step chaotic time series prediction

Remaining useful life prediction of PEMFC systems based on the multi-input echo state network

(2020) Zhiguang Hua et al.   APPLIED ENERGY

Combining machine learning with knowledge-based modeling for scalable forecasting and subgrid-scale closure of large, complex, spatiotemporal systems

(2020) Alexander Wikner et al.   CHAOS

Embedding and approximation theorems for echo state networks

(2020) Allen Hart et al.   NEURAL NETWORKS

An asynchronously deep reservoir computing for predicting chaotic time series

(2020) Ying-Chun Bo et al.   APPLIED SOFT COMPUTING

Multi-objective ensembles of echo state networks and extreme learning machines for streamflow series forecasting

(2020) Victor Henrique Alves Ribeiro et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series

(2020) Seçkin Karasu et al.   ENERGY

Recent advances in physical reservoir computing: A review

(2019) Gouhei Tanaka et al.   NEURAL NETWORKS

A Distributed Algorithm for the Cooperative Prediction of Power Production in PV Plants

(2019) Antonello Rosato et al.   IEEE TRANSACTIONS ON ENERGY CONVERSION

Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques

(2019) Aytaç Altan et al.   CHAOS SOLITONS & FRACTALS

Hybrid structures in time series modeling and forecasting: A review

(2019) Zahra Hajirahimi et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Short-term natural gas consumption prediction based on Volterra adaptive filter and improved whale optimization algorithm

(2019) Weibiao Qiao et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Adaptive Prognostic of Fuel Cells by Implementing Ensemble Echo State Networks in Time-Varying Model Space

(2019) Zhongliang Li et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

DeePr-ESN: A deep projection-encoding echo-state network

(2019) Qianli Ma et al.   INFORMATION SCIENCES

A Novel Framework of Reservoir Computing for Deterministic and Probabilistic Wind Power Forecasting

(2019) Jianzhou Wang et al.   IEEE Transactions on Sustainable Energy

Low dimensional mid-term chaotic time series prediction by delay parameterized method

(2019) Xiaoxiang Guo et al.   INFORMATION SCIENCES

Attractor reconstruction by machine learning

(2018) Zhixin Lu et al.   CHAOS

Optimization of neural network using kidney-inspired algorithm with control of filtration rate and chaotic map for real-world rainfall forecasting

(2018) Najmeh Sadat Jaddi et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Novel Multi-Step Short-Term Wind Power Prediction Framework Based on Chaotic Time Series Analysis and Singular Spectrum Analysis

(2018) Nima Safari et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach

(2018) Jaideep Pathak et al.   PHYSICAL REVIEW LETTERS

Hybrid Regularized Echo State Network for Multivariate Chaotic Time Series Prediction

(2018) Meiling Xu et al.   IEEE Transactions on Cybernetics

Design of deep echo state networks

(2018) Claudio Gallicchio et al.   NEURAL NETWORKS

Echo state networks are universal

(2018) Lyudmila Grigoryeva et al.   NEURAL NETWORKS

Wind speed and wind direction forecasting using echo state network with nonlinear functions

(2018) Mohammad Amin Chitsazan et al.   RENEWABLE ENERGY

Trend analysis of climate time series: A review of methods

(2018) Manfred Mudelsee   EARTH-SCIENCE REVIEWS

Deep reservoir computing: A critical experimental analysis

(2017) Claudio Gallicchio et al.   NEUROCOMPUTING

Multilayered Echo State Machine: A Novel Architecture and Algorithm

(2017) Zeeshan Khawar Malik et al.   IEEE Transactions on Cybernetics

A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting

(2016) Souhaib Ben Taieb et al.   IEEE Transactions on Neural Networks and Learning Systems

Deep learning

(2015) Yann LeCun et al.   NATURE

Prediction of telephone calls load using Echo State Network with exogenous variables

(2015) Filippo Maria Bianchi et al.   NEURAL NETWORKS

Echo State Property Linked to an Input: Exploring a Fundamental Characteristic of Recurrent Neural Networks

(2012) G. Manjunath et al.   NEURAL COMPUTATION

Reservoir computing and extreme learning machines for non-linear time-series data analysis

(2012) J.B. Butcher et al.   NEURAL NETWORKS

Architectural and Markovian factors of echo state networks

(2011) Claudio Gallicchio et al.   NEURAL NETWORKS