Abstract: A data transmission method, apparatus, and device, and a computer storage medium are provided. The method includes: obtaining an application packet of a target application; transmitting the application packet to a first routing device by using a network data channel, and transmitting, by using the first routing device, the application packet to a proxy server; meanwhile, transmitting the same application packet to a second routing device by using a short-range wireless data channel different from the network data channel, and transmitting, by using the second routing device, the application packet to the proxy server. The proxy server performs, a deduplication mechanism on the application packet and transmit the application packet to an application server corresponding to the target application.

Abstract: A displaying base plate and a manufacturing method thereof, and a displaying device. The displaying base plate includes a substrate, and a first electrode layer disposed on one side of the substrate, wherein the first electrode layer includes a first electrode pattern; a first planarization layer disposed on one side of the first electrode layer that is away from the substrate, wherein the first planarization layer is provided with a through hole, and the through hole penetrates the first planarization layer, to expose the first electrode pattern; and a second electrode layer, a second planarization layer and a third electrode layer that are disposed in stack on one side of the first planarization layer that is away from the substrate, wherein the second electrode layer is disposed closer to the substrate, the second electrode layer is connected to the first electrode pattern and the third electrode layer.

Abstract: The present invention provides an interpretable power load prediction method, system and terminal machine, relating to the field of power load prediction. The method comprises: initializing three factors—seasonal factor, trend factor, and smoothing factor, denoted as S1, T1, and I1 respectively; calculating states of the three factors for time t+1 in a current DeepES unit; outputting the three factors St+1, Tt+1, and It+1 to a next DeepES unit; repeating until a n-th DeepES unit completes its operation; calculating a predicted value Y based on the three factors that are outputted from a final DeepES unit. In power load prediction, constructing an interpretable prediction model enables users to understand the inference process of the model, therefore helps enhance the credibility of the model.