PREDICTIVE ARTIFICIAL INTELLIGENCE: TIME SERIES FORECASTING USING NEURAL NETWORKS. EXAMPLES WITH MATLAB
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Predictive Artificial Intelligence is a branch of Artificial Intelligence that uses algorithms and statistical models that are based on historical data to anticipate behaviors, make predictions, analyze trends and simulate future events. Time series analysis is a very important subject within Predictive Artificial Intelligence. The book begins by analyzing the capabilities of dynamic neural networks and the workflow necessary to obtain predictions through networks. Below we delve into the typologies of neural networks commonly used for time series prediction and their implementation, analysis and optimization. The content continues to develop multilayer neural networks and their applications for prediction. The scalability and efficiency of neural networks for prediction through the adaptation of big data technologies such as parallel processing and distributed computing are discussed below. All content is illustrated with MATLAB and SIMULINK applications that clarify the methodology.
Détails
- Date de publication
- Jul 23, 2024
- Langue
- English
- ISBN
- 9781304169068
- Catégorie
- Informatique & internet
- Copyright
- Tous droits réservés - Licence de copyright standard
- Contributeurs
- Par (auteur): Cesar Perez Lopez
Caractéristiques
- Pages
- 287
- Type de reliure
- Livre à couverture souple Livre à couverture souple
- Couleur de l’intérieur
- Noir & Blanc
- Dimensions
- Exécutif (7 x 10 po / 178 x 254 mm)
Mots-clés
ARTIFICIAL INTELLIGENCEAIIAINTELIGENCIA ARTIFICIALTIME SERIESNEURAL NETWORKSMULTILAYER NEURAL NETWORKSNARXLSTMNARX NETWORKSTIME DELAY NETWORKSTIME DELAYDYNAMIC NEURAL NETWORKSTIME SERIES FORECASTINGPARALLEL COMPUTINGGPU COMPUTINGBIG DATAANALYZE NETWORKSOPTIMAL SOLUTIONSSCALABILYTEEFICIENCEDEPLOY NETORK