The 8th International Conference on Time Series and Forecasting
The aim of ITISE 2022 is to create a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees. Therefore, ITISE 2022 is soliciting high-quality original research papers (including significant works-in-progress) on any aspec...
Guardado en:
| Formato: | Online |
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| Lenguaje: | inglés |
| Publicado: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Materias: | |
| Acceso en línea: | ONIX_20221117_9783036554525_83 |
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| _version_ | 1869521374191550464 |
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| collection | Directory of Open Access Books |
| description | The aim of ITISE 2022 is to create a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees. Therefore, ITISE 2022 is soliciting high-quality original research papers (including significant works-in-progress) on any aspect time series analysis and forecasting, in order to motivating the generation and use of new knowledge, computational techniques and methods on forecasting in a wide range of fields. |
| format | Online |
| id | doab-20.500.12854ir-93826 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-938262024-03-30T12:51:25Z The 8th International Conference on Time Series and Forecasting Rojas, Ignacio Pomares, Hector Valenzuela, Olga Rojas, Fernando Herrera, Luis Kaufman, Peter readmission prediction intensive care unit (ICU) recurrent neural network (RNN) longshort-term memory (LSTM) machine learning (ML) time series analysis health forecasting spectrum utilization prediction time-series clustering K-Means LSTM CNN outlier detection outlier detection in time series time series clustering time series cluster evaluation time series anomaly detection predictive maintenance model evaluation error diagnosis convolutional neural network all sky images cloud-base height machinelearning : financial market volatility VAR-DCC-GARCH wavelet-based random forest forecasting synthetic data shareable data privacy cross-correlation DCCA method oil derivatives energy accessibility retainability Markov chain K-mean clustering mobile data traffic multivariate prediction temporal spatial COVID-19 time series forecasting NARNN ARIMA dynamic convergence stationarity unit root ecosystem respiration dynamic mode decomposition with control time delay embedding ordinal patterns structural breaks non-stationary time series hydrological data prediction intervals seq2seq oil production automated machine learning machine learning time-series forecasting PV systems faults diagnosis signal processing time series data thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science The aim of ITISE 2022 is to create a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees. Therefore, ITISE 2022 is soliciting high-quality original research papers (including significant works-in-progress) on any aspect time series analysis and forecasting, in order to motivating the generation and use of new knowledge, computational techniques and methods on forecasting in a wide range of fields. 2022-11-17T16:26:41Z 2022-11-17T16:26:41Z 2022 book ONIX_20221117_9783036554525_83 9783036554525 9783036554518 https://directory.doabooks.org/handle/20.500.12854/93826 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/6255 https://mdpi.com/books/pdfview/book/6255 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-5452-5 10.3390/books978-3-0365-5452-5 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036554525 9783036554518 434 Basel open access |
| spellingShingle | readmission prediction intensive care unit (ICU) recurrent neural network (RNN) longshort-term memory (LSTM) machine learning (ML) time series analysis health forecasting spectrum utilization prediction time-series clustering K-Means LSTM CNN outlier detection outlier detection in time series time series clustering time series cluster evaluation time series anomaly detection predictive maintenance model evaluation error diagnosis convolutional neural network all sky images cloud-base height machinelearning : financial market volatility VAR-DCC-GARCH wavelet-based random forest forecasting synthetic data shareable data privacy cross-correlation DCCA method oil derivatives energy accessibility retainability Markov chain K-mean clustering mobile data traffic multivariate prediction temporal spatial COVID-19 time series forecasting NARNN ARIMA dynamic convergence stationarity unit root ecosystem respiration dynamic mode decomposition with control time delay embedding ordinal patterns structural breaks non-stationary time series hydrological data prediction intervals seq2seq oil production automated machine learning machine learning time-series forecasting PV systems faults diagnosis signal processing time series data thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science The 8th International Conference on Time Series and Forecasting |
| title | The 8th International Conference on Time Series and Forecasting |
| title_full | The 8th International Conference on Time Series and Forecasting |
| title_fullStr | The 8th International Conference on Time Series and Forecasting |
| title_full_unstemmed | The 8th International Conference on Time Series and Forecasting |
| title_short | The 8th International Conference on Time Series and Forecasting |
| title_sort | 8th international conference on time series and forecasting |
| topic | readmission prediction intensive care unit (ICU) recurrent neural network (RNN) longshort-term memory (LSTM) machine learning (ML) time series analysis health forecasting spectrum utilization prediction time-series clustering K-Means LSTM CNN outlier detection outlier detection in time series time series clustering time series cluster evaluation time series anomaly detection predictive maintenance model evaluation error diagnosis convolutional neural network all sky images cloud-base height machinelearning : financial market volatility VAR-DCC-GARCH wavelet-based random forest forecasting synthetic data shareable data privacy cross-correlation DCCA method oil derivatives energy accessibility retainability Markov chain K-mean clustering mobile data traffic multivariate prediction temporal spatial COVID-19 time series forecasting NARNN ARIMA dynamic convergence stationarity unit root ecosystem respiration dynamic mode decomposition with control time delay embedding ordinal patterns structural breaks non-stationary time series hydrological data prediction intervals seq2seq oil production automated machine learning machine learning time-series forecasting PV systems faults diagnosis signal processing time series data thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science |
| topic_facet | readmission prediction intensive care unit (ICU) recurrent neural network (RNN) longshort-term memory (LSTM) machine learning (ML) time series analysis health forecasting spectrum utilization prediction time-series clustering K-Means LSTM CNN outlier detection outlier detection in time series time series clustering time series cluster evaluation time series anomaly detection predictive maintenance model evaluation error diagnosis convolutional neural network all sky images cloud-base height machinelearning : financial market volatility VAR-DCC-GARCH wavelet-based random forest forecasting synthetic data shareable data privacy cross-correlation DCCA method oil derivatives energy accessibility retainability Markov chain K-mean clustering mobile data traffic multivariate prediction temporal spatial COVID-19 time series forecasting NARNN ARIMA dynamic convergence stationarity unit root ecosystem respiration dynamic mode decomposition with control time delay embedding ordinal patterns structural breaks non-stationary time series hydrological data prediction intervals seq2seq oil production automated machine learning machine learning time-series forecasting PV systems faults diagnosis signal processing time series data thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science |
| url | ONIX_20221117_9783036554525_83 |