Study of Time Series Data Mining for the Real Time Hydrological Forecasting: A Review

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A review on time series data mining

Time series is an important class of temporal data objects and it can be easily obtained from scientific and financial applications. A time series is a collection of observations made chronologically. The nature of time series data includes: large in data size, high dimensionality and necessary to update continuously. Moreover time series data, which is characterized by its numerical and contin...

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Today, real world time series data sets can take a size up to a trillion observations and even more. Data miners’ task is it to detect new information that is hidden in this massive amount of data. While well known techniques for data mining in cross sections have been developed, time series data mining methods are not as sophisticated and established yet. Large time series bring along problems...

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A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e...

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ژورنال

عنوان ژورنال: International Journal of Computer Applications

سال: 2015

ISSN: 0975-8887

DOI: 10.5120/20692-3581