3 results about "Window selection" patented technology

The application provides a risk prediction window selection method and device based on multi-target cooperative evaluation and electronic equipment, relates to the technical field of machine learning and data modeling, and comprises the following steps: obtaining time sequence historical data of a target object, and dividing the time sequence historical data into a training subset and a test subset used for simulating future prediction according to time sequence; a candidate prediction window set containing at least two different time lengths is set, for each window length in the set, a corresponding binary classification prediction task label is defined based on the length, and a corresponding prediction model is trained by using the training subset; taking the model performance corresponding to the longest reference window in the candidate window as a reference, the optimal window length is selected from the candidate window set according to a preset selection criterion. The application ensures that the selected window length directly serves the accuracy target of the final prediction model, so that the shortest effective window is automatically found under the premise of ensuring that the prediction performance of the long window reference model is equivalent.

The invention discloses an adaptive multi-window and anti-noise fluctuating commodity sales volume prediction method, which comprises the following steps of: (1) constructing a multi-window network architecture, and carrying out parallel processing input through a plurality of sub-networks with different historical window lengths so as to explicitly model a long-short term multi-scale mode in a time sequence; (2) introducing an adaptive multi-window selection mechanism, and dynamically learning an optimal window length matched with the characteristics of the current input sample for each sub-network; and (3) designing a self-adaptive anti-noise module, and injecting anti-noise with variable intensity into the self-adaptive anti-noise module according to the window length of each sub-network so as to enhance the robustness of the model in a high-noise environment. According to the method, through an innovative multi-window network architecture, adaptive window selection and an adaptive anti-noise mechanism, the problems of multi-scale mode modeling and model robustness in a high-fluctuation and high-noise fluctuation commodity sales volume prediction task are effectively solved, and the model prediction accuracy and generalization ability are remarkably improved.

The invention discloses a core unit, a high-performance frequency hopping carrier generator and a frequency hopping transmitter, and the core unit comprises a phase interpolator which is used for initializing a clock period signal with an adjustable phase, and the frequency of the clock period signal is the same as the frequency of a reference clock; the counter is used for outputting an integral multiple frequency hopping result of the reference clock; the delay adjusting module is used for adjusting the time sequence relation between the output of the phase interpolator and the output of the counter; the either-or selector is used for selecting the output of the counter; and the window selection module is used for selecting the required phase interpolator output according to the output of the counter.