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Machine Learning Model For Computational Tracking and Forecasting the COVID-19 Dynamic Propagation

Ginalber L.O. Serra, Daiana Caroline dos Santos Gomes
2021 IEEE journal of biomedical and health informatics  
behavior and uncertainty inherited to epidemiological data, and an interval type-2 fuzzy version of Observer/Kalman Filter Identification (OKID) algorithm for adaptive tracking and real time forecasting  ...  The innovations of adopted methodology consist of an interval type-2 fuzzy clustering algorithm based on adaptive similarity distance mechanism for defining specific operation regions associated to the  ...  of Maranhão (PPGEE-UFMA).  ... 
doi:10.1109/jbhi.2021.3052134 pmid:33449891 fatcat:prb22kycmfgdhkt6477ylujf6e

Computational Approach For Real-Time Interval Type-2 Fuzzy Kalman Filtering and Forecasting via Unobservable Spectral Components of Experimental Data

Daiana Caroline dos Santos Gomes, Ginalber Luiz de Oliveira Serra
2021 Journal of Control Automation and Electrical Systems  
In this paper, a methodology for design of Kalman filter, using interval type-2 fuzzy systems, in discrete time domain, via spectral decomposition of experimental data, is proposed.  ...  The interval Kalman gains in the consequent proposition of interval type-2 fuzzy Kalman filter are updated according to unobservable components computed by recursive spectral decomposition of experimental  ...  of Maranhão (PPGEE-UFMA) for their support in the development of this research.  ... 
doi:10.1007/s40313-020-00675-9 fatcat:gzajcvkbcrd2pnw7hd4gv3323m

Data Science: Measuring Uncertainties

Carlos Alberto de Braganca Pereira, Adriano Polpo, Agatha Sacramento Rodrigues
2020 Entropy  
With the increase in data processing and storage capacity, a large amount of data is available [...]  ...  Conflicts of Interest: The authors declare no conflict of interest.  ...  They proposed a robust SSA algorithm by replacing the standard least-squares singular value decomposition (SVD) by a robust SVD algorithm based on the L1 norm and a robust SSA algorithm.  ... 
doi:10.3390/e22121438 pmid:33419285 fatcat:27xyg3zt6zbexconqhakmvzjbq

Extraction of fetal electrocardiogram (ECG) by extended state Kalman filtering and adaptive neuro-fuzzy inference system (ANFIS) based on single channel abdominal recording

D PANIGRAHY, P K SAHU
2015 Sadhana (Bangalore)  
In this paper, authors investigate the use of adaptive neuro-fuzzy inference system (ANFIS) with extended Kalman filter for fetal ECG extraction from one ECG signal recorded at the abdominal areas of the  ...  We use extended Kalman filter framework to estimate the maternal component from abdominal ECG. The maternal component in the abdominal ECG signal is a nonlinear transformed version of maternal ECG.  ...  Extended Kalman filter framework The goal of the extended Kalman filter is to estimate the state of a discrete time controlled process.  ... 
doi:10.1007/s12046-015-0381-7 fatcat:w6a6jm755bfvtavik25ovechlm

Index [chapter]

2021 Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems  
structure of, 310f Fault tree analysis, 235 FDI schemes, 187 Field-oriented PWM drive, 131f Fixed-Lag H ∞ fault estimator design for LDTV systems, 112, 120, 122 Kalman filtering in, 117 Krein  ...  faults, 198, 198 Short-circuit failure, 133 Signal features of, 145 selection, 144 Signal-to-noise ratio, 353 Simultaneous faults, 197 Singhal model, 224 Singular value decomposition (SVD), 2,  ... 
doi:10.1016/b978-0-12-822473-1.00018-5 fatcat:f57zezz5vzhr5gqumy7xy2p5ou

Hybrid methodology for modeling short-term wind power generation using conditional Kernel density estimation and singular spectrum analysis

Soraida Aguilar-Vargas, Reinaldo Castro-Souza, José Francisco Pessanha, Fernando Luiz Cyrino-Oliveira
2017 Dyna  
Haciendo uso de una base de datos brasilera horaria que incluye la velocidad del viento y la energía eólica es ilustrada dicha metodología.  ...  In [15] it is also used a state-space model to be optimized with a Kalman filter to predict the wind speed over the North Atlantic Ocean.  ...  Similarly, for wind speed prediction it was used the Kalman filter to estimate the parameters of AR and ARMA models, as indicated in [13, 14] .  ... 
doi:10.15446/dyna.v84n201.59541 fatcat:4ufk4kjqybaazkxnz4eishgjtq

Wind Speed Forecasting in China: A Review

Huiru Zhao
2015 Science Journal of Energy Engineering  
China's wind power has developed rapidly in the past few years, the large-scale penetration of which will bring big influence on power systems.  ...  This paper can rich the current research in the field of wind speed forecasting.  ...  [8] proposed a hybrid algorithm integrating time series analysis with Kalman filter to forecast wind speed, and the case study results show the forecasting accuracy of this proposed model can be improved  ... 
doi:10.11648/j.sjee.s.2015030401.13 fatcat:dpbqaw57o5c6pm7ozgnv7zwppe

Change Point Estimation of the Stationary State in Auto Regressive Moving Average Models, Using Maximum Likelihood Estimation and Singular Value Decomposition-based Filtering

2019 International Journal of Engineering  
To estimate unidentified parameters following the change point, the dynamic linear model's filtering was utilized on the basis of the singular decomposition of values.  ...  In the monitoring phase, in case the features of the question pursue a time series, i.e., ARMA(1,1), on the basis of the maximum likelihood technique, an approach will be developed for the estimation of  ...  The next part is concerned with the delineation of the SVD-based Kalman filter as utilized in the current study.  ... 
doi:10.5829/ije.2019.32.05b.15 fatcat:kppo7ubzk5clnlpyhpsgu7ugny

A REVIEW OF MODELLING APPROACHES ON TIDAL ANALYSIS AND PREDICTION

A. G. Abubakar, M. R. Mahmud, K. K. W. Tang, A. Hussaini, N. H. Md Yusuf
2019 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Conventional tidal forecasting techniques are based on harmonic analysis, which is a superposition of many sinusoidal constituents with three parameters amplitudes, Phase and frequencies using the least  ...  Furthermore, what seems to stand out by the other researchers on traditional harmonic methods, was its limitation when short data are involved and rely on based on the analysis of astronomical components  ...  ACKNOWLEDGEMENTS The authors would like to acknowledge the Federal Government of Nigeria for providing financial support Through Tertiary Education Trust Fund (TETFUND).  ... 
doi:10.5194/isprs-archives-xlii-4-w16-23-2019 fatcat:a4vsbth4vna53phb6w3tsnzhey

Methodological Survey on Fetal ECG Extraction

Kumar SS Anisha M
2014 Journal of Health & Medical Informatics  
Fetal Electrocardiogram (FECG) signal, non-invasively taken from the Abdominal Electrocardiogram (AECG) of a pregnant woman is an efficient diagnostic tool for evaluating the health status of foetus.  ...  A methodological study has been carried out to show the effectiveness of various methods which helps in understanding of Fetal ECG signal and its analysis procedures by providing valuable information.  ...  Kalman Filtering -Real time implementation is possible but complex. -Efficiency is high. SVD,PCA -Overall performance is low. -Relatively SNR is low.  ... 
doi:10.4172/2157-7420.1000169 fatcat:yylfbjadgngxtljrmhb757hpi4

Methodological Survey on Fetal ECG Extraction

Anisha M, Dr.S.S Kumar, Benisha M
2014 IOSR Journal of Computer Engineering  
Fetal Electrocardiogram (FECG) signal, non-invasively taken from the Abdominal Electrocardiogram (AECG) of a pregnant woman is a efficient diagnostic tool for evaluating the health status of fetus.  ...  A methodological study has been carried out to show the effectiveness of various methods which helps in understanding of Fetal ECG signal and its analysis procedures by providing valuable information.  ...  In [79] , a method was employed with the combination of singular value decomposition (SVD) and ICA for FECG signal separation from AECG.  ... 
doi:10.9790/0661-1657105115 fatcat:s3mvq2asvjcppohmezzhpz4u6u

Hybrid Wind Speed Forecasting Model Study Based on SSA and Intelligent Optimized Algorithm

Wenyu Zhang, Zhongyue Su, Hongli Zhang, Yanru Zhao, Zhiyuan Zhao
2014 Abstract and Applied Analysis  
The present study investigated singular spectrum analysis (SSA) with a reduced parameter algorithm in three time series models, the autoregressive integrated moving average (ARIMA) model, the support vector  ...  After optimization, the SSA-based forecasting models are applied to forecasting the immediate short-term wind speed and are adopted at ten wind farms in China.  ...  Acknowledgments This research was supported by the National Natural Science Foundation of China (41225018) and IAM (IAM201305).  ... 
doi:10.1155/2014/693205 fatcat:hyg2r37mtnbapje45u3u4rv54u

A new LS+AR model with additional error correction for polar motion forecast

YiBin Yao, ShunQiang Yue, Peng Chen
2013 Science China. Earth Sciences  
Through statistical analysis of the time series of the LS+AR model's short-term prediction residuals, we found that there is a good correlation of model prediction residuals between adjacent terms.  ...  The LS+AR model is recognized as one of the best models for polar motion prediction.  ...  inference systems [4] , Kalman filter combined with Atmospheric Angular Momentum (AAM+Kalman filter) [5] [6] [7] [8] [9] [10] , Least Squares and Auto Regressive prediction (LS+AR) [5] [6] [7] [8] [  ... 
doi:10.1007/s11430-012-4572-3 fatcat:2meoqsm4iffevomx4vxosh2cnu

EEG seizure detection and prediction algorithms: a survey

Turkey N Alotaiby, Saleh A Alshebeili, Tariq Alshawi, Ishtiaq Ahmad, Fathi E Abd El-Samie
2014 EURASIP Journal on Advances in Signal Processing  
Locating the seizure period in EEG recordings manually is difficult and time consuming; one often needs to skim through tens or even hundreds of hours of EEG recordings.  ...  In this paper, we first present an overview of seizure detection and prediction problem and provide insights on the challenges in this area.  ...  Shahid et al. presented an algorithm based on SVD for the detection of seizures [76] .  ... 
doi:10.1186/1687-6180-2014-183 fatcat:7zocqklkxbg6poo5hyskvokluq

Chaotic Time Series Forecasting Using Higher Order Neural Networks

Waddah Waheeb, Rozaida Ghazali
2016 International Journal on Advanced Science, Engineering and Information Technology  
These models were tested on two benchmark time series; the monthly smoothed sunspot numbers and the Mackey-Glass time-delay differential equation time series.  ...  This study presents a novel application and comparison of higher order neural networks (HONNs) to forecast benchmark chaotic time series.  ...  Decomposition (SVD) [7] 0.0894 Gustafson-Kessel fuzzy clustering method + Kalman Filtering Algorithm (KFA) with SVD [8] 0.0748 Orthogonal function neural network + recursive KFA based on SVD [34]  ... 
doi:10.18517/ijaseit.6.5.958 fatcat:uso5ldwbyran5altncy33gbpau
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