Pattern Recognition for Time Series Signals Using Recurrent Neural Networks by Genetic Algorithms
نویسندگان
چکیده
منابع مشابه
Recurrent neural networks for time-series prediction
Recurrent neural networks have been used for time-series prediction with good results. In this dissertation we compare recurrent neural networks with time-delayed feed forward networks, feed forward networks and linear regression models to see which architecture that can make the most accurate predictions. The data used in all experiments is real-world sales data containing two kinds of segment...
متن کاملRecurrent neural networks for time series classification
Recurrent neural networks (RNN) are a widely used tool for the prediction of time series. In this paper we use the dynamic behaviour of the RNN to categorize input sequences into different specified classes. These two tasks do not seem to have much in common. However, the prediction task strongly supports the development of a suitable internal structure, representing the main features of the in...
متن کاملUsing Recurrent Neural Networks for Time Series Forecasting
In the past few years, artiicial neural networks (ANNs) have been investigated as a tool for time series analysis and forecasting. The most popular architecture is the multilayer perceptron, a feedforward network often trained by back-propagation. The forecasting performance of ANNs relative to traditional methods is still open to question although many experimenters seem optimistic. One proble...
متن کاملAdvanced Methods for Time Series Prediction Using Recurrent Neural Networks
Time series prediction has important applications in various domains such as medicine, ecology, meteorology, industrial control or finance. Generally the characteristics of the phenomenon which generates the series are unknown. The information available for the prediction is limited to the past values of the series. The relations which describe the evolution should be deduced from these values,...
متن کاملAlgorithms for Segmenting Time Series
As with most computer science problems, representation of the data is the key to ecient and eective solutions. Piecewise linear representation has been used for the representation of the data. This representation has been used by various researchers to support clustering, classication, indexing and association rule mining of time series data. A variety of algorithms have been proposed to obtain...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Transactions of the Institute of Systems, Control and Information Engineers
سال: 1997
ISSN: 1342-5668,2185-811X
DOI: 10.5687/iscie.10.304