3results about How to "Improve analysis results" patented technology

The invention relates to the technical field of machine learning, in particular to a time series data analysis system and method based on deep learning, and the system comprises an input preprocessing module which is used for carrying out the standardization processing and segmentation processing of input time series data; the sliding window recurrent neural network module is used for processing the input time sequence data in each sliding window of eight thousand time steps to generate a short-term time sequence feature vector; the dynamic updating recurrent neural network module is used for processing long-term time sequence data; the meta-learning optimization module is used for dynamically updating initialization parameters of the recurrent neural network module through outer loop optimization; and the output fusion module is used for fusing the feature vectors and generating a final time sequence analysis result. According to the method, a weight updating mechanism which only updates the last quarter layer of the recurrent neural network is innovatively designed, the calculation complexity is remarkably reduced, and the contradiction between the calculation efficiency and the model adaptability in long-sequence time sequence analysis is effectively solved while high precision is kept.

This invention discloses a device for detecting down composition and residual fat content, comprising a controller, a composition detection mechanism, and a sample dispersion mechanism, a microwave extraction mechanism, and a drying and weighing mechanism connected in sequence. The sample dispersion mechanism includes a sample chamber and a dispersion cavity. A miniature electromagnetic vibrator is installed at the bottom of the sample chamber, with its top surface inclined to the dispersion cavity. The dispersion cavity is a transparent cavity with an air outlet, an air inlet, and a telescopic rod A. A mesh sieve plate is fixed to the top of the telescopic rod A, and a sample recovery port is located above the sieve plate. The composition detection mechanism is connected to the dispersion cavity. The controller connects to each component. This invention achieves integrated automatic detection of down composition and residual fat content by integrating composition detection, microwave extraction, and drying and weighing. It replaces Soxhlet extraction with microwave extraction, significantly shortening the residual fat detection time and reducing the amount of organic solvent used. Through automatic dispersion, sieving, and optical analysis, it reduces manual intervention and improves the efficiency, objectivity, and repeatability of composition analysis results.