This book aims to provide readers with the current information, developments, and trends in a time series analysis, particularly in time series data patterns, technical methodologies, and real-world applications. This book is divided into three sections and each section includes two chapters. Section 1 discusses analyzing multivariate and fuzzy time series. Section 2 focuses on developing deep neural networks for time series forecasting and classification. Section 3 describes solving real-world domain-specific problems using time series techniques. The concepts and techniques contained in this book cover topics in time series research that will be of interest to students, researchers, practitioners, and professors in time series forecasting...
An accessible introduction to the most current thinking in and practicality of forecasting technique...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
Time series represent sequences of data points where usually their order is defined by the time when...
A time series is a sequence of time-ordered data, and it is generally used to describe how a phenome...
Time Series Analysis (TSA) and Applications offers a dense content of current research and developme...
This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a p...
Time series modeling is a challenging and demanding problem. In the recent year, deep learning (DL) ...
The beginning of the age of artificial intelligence and machine learning has created new challenges ...
Time Series Forecasting is vital for wide range of domains such as financial market forecasting, ear...
Nature brings time series data everyday and everywhere, for example, weather data, physiological sig...
There is nowadays a constant flux of data being generated and collected in all types of real world ...
Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams...
This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarize...
Time series forecasting has recently emerged as a crucial study area with a wide spectrum of real-wo...
In this present work, we provide an overview of methods for time series modelling and prediction. We...
An accessible introduction to the most current thinking in and practicality of forecasting technique...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
Time series represent sequences of data points where usually their order is defined by the time when...
A time series is a sequence of time-ordered data, and it is generally used to describe how a phenome...
Time Series Analysis (TSA) and Applications offers a dense content of current research and developme...
This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a p...
Time series modeling is a challenging and demanding problem. In the recent year, deep learning (DL) ...
The beginning of the age of artificial intelligence and machine learning has created new challenges ...
Time Series Forecasting is vital for wide range of domains such as financial market forecasting, ear...
Nature brings time series data everyday and everywhere, for example, weather data, physiological sig...
There is nowadays a constant flux of data being generated and collected in all types of real world ...
Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams...
This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarize...
Time series forecasting has recently emerged as a crucial study area with a wide spectrum of real-wo...
In this present work, we provide an overview of methods for time series modelling and prediction. We...
An accessible introduction to the most current thinking in and practicality of forecasting technique...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
Time series represent sequences of data points where usually their order is defined by the time when...