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Cloud and snow detection has significant remote sensing applications, while they share similar low-level features due to their consistent color distributions and similar local texture patterns. Thus, accurately distinguishing cloud from snow in pixel level from satellite images is always a challenging task with traditional approaches. To solve this shortcoming, in this letter, we proposed a deep learning...
The accuracy about short-term wind speed prediction is helpful to the economy and safety in the wind power grid. In view that the nonlinear and complexity characteristics related to the wind speed change, a new approach for short-term wind speed forecasting is put forward. The proposed method belongs to the back propagation (BP) neural network based on improved artificial bee colony algorithm (ABC-BP)...
Fault detection of Air Conditioning (AC) system is one of the most important problems in building energy-saving and safety. Unfortunately, the identification of unknown modes is still a difficult issue in fault detection. Expectation-maximization (EM) algorithm has been applied widely in modes identification of AC system. However, the traditional EM algorithm is much more complicated in iteration...
At present, in terms of the influences of temperature and holidays on the power load, an improved T-S fuzzy-neural network is proposed to forecast the short-term power load. Considering the learning rate and smoothing factor should be adjusted dynamically for the higher performance of T-S fuzzy-neural network, the two optimal parameters must be found automatically when the parameters are changed....
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