6results about How to "Achieving Precise Forecasting" patented technology

The invention discloses a defect severity prediction method based on developer modification history, and belongs to the technical field of software development. Comprising the steps of extracting modified historical data and defect report data, constructing an original data set, preprocessing the original data set, establishing a standard data set according to a file-defect-developer mapping relation, and constructing a developer-file weighted directed network based on the standard data set. Obtaining a file-file weighted directed network through weighted projection based on the developer-file weighted directed network, calculating a structure entropy score of a file node based on the file-file weighted directed network, and extracting a software measurement index of each source code file; and constructing a comprehensive feature set based on the structure entropy score, the software measurement index and the defect label combination, and training and verifying a machine learning model based on the comprehensive feature set to realize the defect severity prediction of the file. According to the invention, the accuracy and stability of defect severity prediction are improved from the perspective of history modification by developers.

The application provides a vibration environment prediction method for aviation equipment structure, relates to the field of environmental engineering, and comprises the following steps: S1, measuring vibration responses of known vibration points; S2, determining demarcation points of a path L1; S3, partitioning a region of a structure plane; S4, solving frequency response functions from the known vibration points to designated to-be-measured points in each partition; S5, solving vibration responses of the designated to-be-measured points in each partition; and S6, sequentially solving vibration responses of multiple designated to-be-measured points in each partition. The point partitioning method provided by the application adopts the similarity of the power spectrum density curves of the measured responses as a partitioning index, compared with the traditional partitioning method based on the physical structure, is more scientific and reasonable, and is beneficial to realizing accurate prediction of the vibration environment.

The application discloses a positioning and prediction method of radio signal equal-intensity boundary value based on a mobile vector set, comprising the following steps: constructing an offline map of an indoor scene in a server; dividing the scene into grids, collecting signal intensity values of Bluetooth beacons at the center of each grid, dividing the signal intensity values into intensity value regions, and obtaining intensity boundary lines after numerical fitting; a user carries a wireless device to move in the scene, cuts the intensity boundary lines, and obtains a dynamically updated mobile vector set; at each time, a position estimation region is constructed according to position estimation results of multiple mobile vectors; and multiple position estimation results are fused through Bayesian estimation, that is, the position at the current time is predicted by combining historical data before the current time. The application adopts a strategy of mapping first and then positioning, the user downloads a scene map through the server, and realizes information fusion calculation through a positioning algorithm, so that accurate positioning and prediction of the user are realized.

The application discloses a laser processing quality prediction method based on an improved starfish optimization algorithm and relates to the technical field of neural network models. The method comprises the following steps: first, improving the starfish optimization algorithm based on the Levy flight principle to obtain an improved starfish optimization algorithm; second, optimizing the weights and biases of a back propagation neural network based on the improved starfish algorithm, and inhibiting overfitting of the back propagation neural network based on an L1 regularization method to obtain a target back propagation neural network; third, acquiring process parameters of silicon carbide laser processing; and finally, inputting the process parameters into the pre-trained target back propagation neural network to obtain the processing quality parameters of the silicon carbide laser processing. The starfish optimization algorithm is improved by introducing the Levy flight principle, and high-precision prediction of the silicon carbide picosecond laser processing quality is realized.

The invention discloses an urban river water quality intelligent early warning system based on multi-parameter on-line monitoring, and relates to the field of water environment monitoring and control, and the system specifically comprises the steps: collecting water quality data in real time through arranging a multi-parameter sensor array, extracting spatial-temporal characteristics through employing a double-flow time sequence convolution network and an adaptive attention layer, and carrying out the real-time monitoring of the water quality. And performing anomaly evaluation based on the expert knowledge base. According to the system, a river branch water system is mapped into a time-varying directed graph structure for pollution tracing, gate linkage control is executed by adopting a distributed edge computing architecture, and pollution surrounding control and emergency disposal are achieved.

The application relates to the technical field of weather radars, in particular to a radar intelligent echo extrapolation method based on a global-local aggregation model.A kind of radar intelligent echo extrapolation method based on global-local aggregation model is provided according to the application, a global-local aggregation model is built and trained by constructing meteorological radar echo grayscale image sequence dataset and its corresponding optical flow sequence dataset, the accurate prediction of future meteorological radar echo image sequence is realized.Carrying out the echo sequence optical flow information as motion guide information, and effectively fusing the echo sequence space-time information under different time scales by means of the attention mechanism, emphasizing the global-local space-time aggregation urgently needed in the echo extrapolation task, the ability to predict the long time sequence of strong rainfall coverage area and intensity is improved.