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Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The accumulative generation operator of traditional DGM(1,1) model does not consider that data volatility will affect the data development trend. This limitation makes a homogenous exponential growth prediction model difficult to simulate stochastic oscillation sequence. To solve this problem, this paper proposes a stochastic oscillation analysis method based on the mean value sequence of raw data, and design a new accumulative operator using trigonometric function values during its weight generation. Based on this accumulative operator, a new DGM(1,1)atan model with variable weights is provided. Finally, this model is used to forecast data in field of marine water quality monitoring. Result shows the effectiveness and practicability of the proposed model. [ABSTRACT FROM AUTHOR]