An Enhanced LSTM for Trend Following of Time Series

Multivariate LSTM-FCNs for Time Series Classification

Over the past decade, multivariate time series classification has been receiving a lot of attention. We propose augmenting the existing univariate time series classification models, LSTM-FCN and ALSTM-FCN with a squeeze and excitation block to further improve performance. Our proposed models outperform most of the state of the art models while requiring minimum preprocessing. The proposed model...

a time-series analysis of the demand for life insurance in iran

با توجه به تجزیه و تحلیل داده ها ما دریافتیم که سطح درامد و تعداد نمایندگیها باتقاضای بیمه عمر رابطه مستقیم دارند و نرخ بهره و بار تکفل با تقاضای بیمه عمر رابطه عکس دارند

An Efficient Framework for Iterative Time-Series Trend Mining

Trend analysis has applications in several domains including: stock market predictions, environmental trend analysis, sales analysis, etc. Temporal trend analysis is possible when the source data (either business or scientific) is collected with time stamps, or with time-related ordering. These time stamps (or orderings) are the core data points for time sequences, as they constitute time serie...

Applying LSTM to Time Series Predi

Trend based Approach for Time Series Representation

Time series representation is one of key issues in time series data mining. Time series is simply a sequence of number collected at regular interval over a period of time and obtained from scientific and financial applications. The nature of time series data shows characteristics like large data size, high dimensional and necessity to update continuously. With the help of suitable choice of rep...