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Time-series data analysis method, system and computer program

A computer and time series technology, applied in the field of time series data analysis, can solve problems such as inappropriate results and complex optimal combination

Inactive Publication Date: 2014-07-16
IBM CORP
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In cases where there are explanatory variables exerting different effects (when the lags and time windows are different for each explanatory variable), the results are inappropriate
Also, one of the hysteresis or the window is tuned to reduce computation, and this complicates finding the optimal combination

Method used

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  • Time-series data analysis method, system and computer program
  • Time-series data analysis method, system and computer program
  • Time-series data analysis method, system and computer program

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Embodiment Construction

[0024] figure 1 is a functional block diagram showing the hardware configuration of the computer 1 according to this implementation model. The hardware structure of computer 1 provides bus 10 (low speed and high speed), CPU (central processing unit) 11 that is connected with bus 10, RAM (random access memory, storage device) 12, ROM (read only memory, storage device) 13, HDD (hard disk drive, storage device) 14 , communication interface 15 , and input-output interface 16 . Furthermore, connected to the input-output interface 16 are a mouse (pointing device) 17 , a flat panel display (display device) 18 , and a keyboard 19 . Also, the computer 1 is explained as a device adopting a general personal computer structure, but for example, multiplexing with the CPU 11 and the HDD 14 may be performed to achieve higher data processing capability and efficiency. In addition to these desktop type computers, any of various types of computer systems such as notebook or tablet type person...

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Abstract

The objective of the present invention is to efficiently and accurately obtain a time lag and a time window which are different for each explanatory variable in a multidimensional time series prediction problem. In determining a time lag and a time window, an explanatory variable time series is not, as-is, subject to normalization and optimization. Instead, once transformation to a cumulative time series, normalization, and optimization are performed, an optimal time lag and time window are determined thereby. By introducing a regularization term in the cumulative time series, the complexity of the obtained model is adjusted. Furthermore, by obtaining the weights of two outstanding cumulative values (which are of opposite signs) (simplified to that extent by normalization), it is possible to obtain the time lag and the time window therefrom.

Description

technical field [0001] The present invention relates to analysis techniques for time series data, and in particular to techniques for selecting optimal time lags and time windows for each variable in time series forecasting problems. Background technique [0002] In general, multidimensional time-series forecasting problems (including recovery problems and class recognition problems) are problems of predicting the next time-series value of a target variable in a time-series from D-type explanatory variables in the time-series. As specific examples, examples of predicting stock prices from various economic indices, examples of predicting climate and weather from various meteorological data, and examples of predicting failures of mechanical systems from various sensor data are provided. When solving such a multidimensional time series forecasting problem, it is necessary to set the optimal time lag and time window for each explanatory variable in the time series. In this cont...

Claims

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Application Information

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IPC IPC(8): G06Q10/04
CPCG06F17/18G06F17/10
Inventor 比户将平
Owner IBM CORP
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