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In this study, a deep denoising recurrent temporal restricted Boltzmann machine network is proposed for long-term prediction of time series. The network is a deep dynamic network model which is stacked by multiple denoising recurrent temporal restricted Boltzmann machines with strong modeling ability for complex high noise time series data. To better deal with high noise data, a random noise is added...
Due to the fluctuation and complexity of the financial time series, it is difficult to use any single artificial technique to capture its non-stationary property and accurately describe its moving tendency. So a novel hybrid intelligent forecasting model based on empirical mode decomposition (EMD) and support vector regression (SVR) is proposed. EMD can adaptively decompose the complicated raw data...
How to predict ecological footprint is the problem need to be resolved. The methods for predicting ecological footprint based on ARMA model and support vector machine model were proposed after thoroughly studying the ecological footprint theory. Ecological footprint during planning period (2007 -2020 years) in Liaoning coastal economic zone was dynamically analyzed with the proposed methods. The results...
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