An improved EEMD-based hybrid approach for the short-term forecasting of hog price in China

Short-term forecasting of hog price, which forms the basis for the decision making, is challenging and of great interest for hog producers and market participants. This study develops improved ensemble empirical mode decomposition (EEMD)-based hybrid approach for the short-term hog price forecasting. Specifically, the EEMD is first used to decompose the original hog price series into several intrinsic-mode functions (IMF) and one residue. The fine-to-coarse reconstruction algorithm is then applied to compose the obtained IMFs and residue into the high-frequency fluctuation, the low-frequency fluctuation, and the trend terms which can highlight new features of the hog price fluctuations. Afterwards, the extreme learning machine (ELM) is employed to model the low-frequency fluctuation, while the autoregressive integrated moving average (ARIMA) and the polynomial function are used to fit the high-frequency fluctuation and trend term, respectively, in a multistep-ahead fashion. The commonly used iterated prediction strategy is adopted for the implementation of the multistep-ahead forecasting. The monthly hog price series from January 2000 to May 2015 in China is employed to evaluate the forecasting performance of the proposed approach with the selected counterparts. The numerical results indicate that the improved EEMD-based hybrid approach is a promising alternative for the short-term hog price forecasting.

Unsteady Heat Release of Stratified Swirling Flames in a Partially Premixed Pre-Vaporized Combustor

Unsteady heat release of stratified swirling flames in a partially premixed pre-vaporized combustor at elevated pressure and temperature is experimentally investigated. Stratified flames produced by a pilot swirler and a main one which are fueled by different flow rates of aviation kerosene. Three fuel staging ratios (SR) of 25%, 30%, and 35% are tested to study its effect on the heat release of stratified flame. CH* chemiluminescence emissions are recorded by a high speed ICCD camera with a 430±10 nm band-pass filter. The Proper Orthogonal Decomposition (POD) analysis is employed to identify the most prominent energetic modes of flame fluctuations. Test results show that the low frequency fluctuation of the flame global heat release is weakened as the SR decreases while the high frequency fluctuation is enhanced. According to the analysis of average heat release of the flame, SR affects the structure of flame by changing the flame angle. The stratified flame dynamics mainly performs the bulk motion, asymmetric motion, and flame shedding. It is found that the flame bulk motion modes contain higher energy than those of other modes. While the other two lower energy modes would transit from asymmetric motion to flame shedding mode as the SR decreases. From the Fast Fourier Transform (FFT) analysis, the low frequency fluctuation of global heat release is dominated by modes of higher energy, while the high frequency fluctuation is related to all the modes.