Cargando…

A Method for Estimating the Entropy of Time Series Using Artificial Neural Networks

Measuring the predictability and complexity of time series using entropy is essential tool designing and controlling a nonlinear system. However, the existing methods have some drawbacks related to the strong dependence of entropy on the parameters of the methods. To overcome these difficulties, thi...

Descripción completa

Detalles Bibliográficos
Autores principales:	Velichko, Andrei, Heidari, Hanif
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8621949/ https://www.ncbi.nlm.nih.gov/pubmed/34828130 http://dx.doi.org/10.3390/e23111432

Ejemplares similares

Discriminating chaotic and stochastic time series using permutation entropy and artificial neural networks
por: Boaretto, B. R. R., et al.
Publicado: (2021)

Artificial Neural Networks for IoT-Enabled Smart Applications: Recent Trends
por: Velichko, Andrei, et al.
Publicado: (2023)

On the Possibility of Designing an Advanced Sensor with Particle Sizing Using Dynamic Light Scattering Time Series Spectral Entropy and Artificial Neural Network
por: Chicea, Dan, et al.
Publicado: (2022)

BBS Posts Time Series Analysis based on Sample Entropy and Deep Neural Networks
por: Chen, Jindong, et al.
Publicado: (2019)

Estimating Permutation Entropy Variability via Surrogate Time Series
por: Ricci, Leonardo, et al.
Publicado: (2022)

Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks
por: Jin, Junghwan, et al.
Publicado: (2015)

Simulation Study on the Application of the Generalized Entropy Concept in Artificial Neural Networks
por: Gajowniczek, Krzysztof, et al.
Publicado: (2018)

Diagnosis and Prognosis of COVID-19 Disease Using Routine Blood Values and LogNNet Neural Network
por: Huyut, Mehmet Tahir, et al.
Publicado: (2022)

Efficient Transfer Entropy Analysis of Non-Stationary Neural Time Series
por: Wollstadt, Patricia, et al.
Publicado: (2014)

Estimating Conditional Transfer Entropy in Time Series Using Mutual Information and Nonlinear Prediction
por: Shahsavari Baboukani, Payam, et al.
Publicado: (2020)

On the use of approximate entropy and sample entropy with centre of pressure time-series
por: Montesinos, Luis, et al.
Publicado: (2018)

On the Use of Interaction Entropy and Related Methods to Estimate Binding Entropies
por: Ekberg, Vilhelm, et al.
Publicado: (2021)

Prediction of hierarchical time series using structured regularization and its application to artificial neural networks
por: Shiratori, Tomokaze, et al.
Publicado: (2020)

Entropy-Based Emotion Recognition from Multichannel EEG Signals Using Artificial Neural Network
por: Aung, Si Thu, et al.
Publicado: (2022)

Maximum entropy models provide functional connectivity estimates in neural networks
por: Lamberti, Martina, et al.
Publicado: (2022)

Bifurcation and Entropy Analysis of a Chaotic Spike Oscillator Circuit Based on the S-Switch
por: Boriskov, Petr, et al.
Publicado: (2022)

Transfer Entropy Estimation and Directional Coupling Change Detection in Biomedical Time Series
por: Lee, Joon, et al.
Publicado: (2012)

An artificial neural network for estimating haplotype frequencies
por: Cartier, Kevin C, et al.
Publicado: (2005)

Estimation of Coal’s Sorption Parameters Using Artificial Neural Networks
por: Skiba, Marta, et al.
Publicado: (2020)

Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks
por: Manikandan, Narayanan, et al.
Publicado: (2016)

Entropy-Based Machine Learning Model for Fast Diagnosis and Monitoring of Parkinson’s Disease
por: Belyaev, Maksim, et al.
Publicado: (2023)

Estimation of the Kinematics and Workspace of a Robot Using Artificial Neural Networks
por: Boanta, Cătălin, et al.
Publicado: (2022)

Inference of gene regulatory networks from time series by Tsallis entropy
por: Lopes , Fabrício Martins, et al.
Publicado: (2011)

Introduction of an artificial neural network–based method for concentration‐time predictions
por: Bräm, Dominic Stefan, et al.
Publicado: (2022)

Estimation of Axle Torque for an Agricultural Tractor Using an Artificial Neural Network
por: Kim, Wan-Soo, et al.
Publicado: (2021)

Estimation of moisture ratio for apple drying by convective and microwave methods using artificial neural network modeling
por: Rasooli Sharabiani, Vali, et al.
Publicado: (2021)

Estimation of Vehicle Longitudinal Velocity with Artificial Neural Network
por: Napolitano Dell’Annunziata, Guido, et al.
Publicado: (2022)

Forecasting stock price using integrated artificial neural network and metaheuristic algorithms compared to time series models
por: Shahvaroughi Farahani, Milad, et al.
Publicado: (2021)

A Comparative Approach to Hand Force Estimation using Artificial Neural Networks
por: Mobasser, Farid, et al.
Publicado: (2012)

EZ Entropy: a software application for the entropy analysis of physiological time-series
por: Li, Peng
Publicado: (2019)

Author Correction: Maximum entropy models provide functional connectivity estimates in neural networks
por: Lamberti, Martina, et al.
Publicado: (2022)

Neural Estimator of Information for Time-Series Data with Dependency
por: Molavipour, Sina, et al.
Publicado: (2021)

Maximum entropy methods for extracting the learned features of deep neural networks
por: Finnegan, Alex, et al.
Publicado: (2017)

Measuring Complexity and Predictability of Time Series with Flexible Multiscale Entropy for Sensor Networks
por: Zhou, Renjie, et al.
Publicado: (2017)

Prediction of Motor Failure Time Using An Artificial Neural Network
por: Scalabrini Sampaio, Gustavo, et al.
Publicado: (2019)

A Method for Medical Data Analysis Using the LogNNet for Clinical Decision Support Systems and Edge Computing in Healthcare
por: Velichko, Andrei
Publicado: (2021)

Symbolic Encoding Methods with Entropy-Based Applications to Financial Time Series Analyses
por: Olbryś, Joanna, et al.
Publicado: (2023)

Improved Effort and Cost Estimation Model Using Artificial Neural Networks and Taguchi Method with Different Activation Functions
por: Rankovic, Nevena, et al.
Publicado: (2021)

Evaluation of the impact of Covid-19 on air traffic volume in Turkish airspace using artificial neural networks and time series
por: Gultekin, Nurullah, et al.
Publicado: (2023)

On Entropy of Probability Integral Transformed Time Series
por: Bajić, Dragana, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_3jq08vghik1f3d7pa1ej84k561