Innovative Applications of Artificial Neural Networks to Data Analytics and Signal Processing [electronic resource] / edited by Gilberto Rivera, Witold Pedrycz, Juan Moreno-Garcia, J. Patricia Sánchez-Solís.

Colaborador(es): Rivera, Gilberto [editor.] | Pedrycz, Witold [editor.] | Moreno-Garcia, Juan [editor.] | Sánchez-Solís, J. Patricia [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Studies in Computational Intelligence ; 1171Editor: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: IX, 561 p. 227 illus., 162 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031697692Tema(s): Computational intelligence | Engineering -- Data processing | Artificial intelligence | Computational Intelligence | Data Engineering | Artificial IntelligenceFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónicoTexto
Contenidos:
Forecasting and Prediction -- On the minimum error using Kolmogorov size shallow neural network and Gradient Descent algorithms for complicated univariate functions -- A Review on the Classification of Body Movement Time Series to Support Clinical Decision-making -- FMarkNet Forecasting model based on Neural networks and the Markowitz Model.
En: Springer Nature eBookResumen: This book deals with the application of ANNs in real-world problems requiring data analysis and signal processing. Artificial neural networks (ANNs) have emerged in society thanks to the large number of applications that have been used in an awe-inspiring way. These networks offer effective solutions to practical, real-world problems. The wide variety of application fields of the studies in the book is remarkable; these are related to sensorization, agriculture, healthcare, air pollution, video games, and cybersecurity, among others. To organize this variety, the chapters have been grouped into three sections related to: (1) Forecasting and Prediction, (2) Knowledge Discovery and Knowledge Management, and (3) Signal Processing. This book aims to reach readers interested in ANNs and their applications in different fields, so it is interesting not only for computer science but also for other related disciplines.
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Forecasting and Prediction -- On the minimum error using Kolmogorov size shallow neural network and Gradient Descent algorithms for complicated univariate functions -- A Review on the Classification of Body Movement Time Series to Support Clinical Decision-making -- FMarkNet Forecasting model based on Neural networks and the Markowitz Model.

This book deals with the application of ANNs in real-world problems requiring data analysis and signal processing. Artificial neural networks (ANNs) have emerged in society thanks to the large number of applications that have been used in an awe-inspiring way. These networks offer effective solutions to practical, real-world problems. The wide variety of application fields of the studies in the book is remarkable; these are related to sensorization, agriculture, healthcare, air pollution, video games, and cybersecurity, among others. To organize this variety, the chapters have been grouped into three sections related to: (1) Forecasting and Prediction, (2) Knowledge Discovery and Knowledge Management, and (3) Signal Processing. This book aims to reach readers interested in ANNs and their applications in different fields, so it is interesting not only for computer science but also for other related disciplines.

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