5results about How to "Enables real-time forecasting" patented technology

The invention relates to an automatic driving safety assisting method and system based on multi-modal fusion, and belongs to the field of automatic driving. The system is composed of a multi-mode sensor, a preprocessing unit, a feature encoder, a time sequence merging module, a context attention module, a classification module, a data storage unit and an output unit. The method comprises the following steps: S1, collecting visual image data and non-visual image data; s2, preprocessing the visual image data and the non-visual image data; s3, performing feature extraction by using a feature encoder; s4, key event division is carried out by using a time sequence merging module; S5, feature fusion is carried out by using a context attention module; s6, inputting the fusion features into a classification module, and predicting pedestrian behavior types; and S7, storing a pedestrian behavior type prediction result, and feeding back the pedestrian behavior type prediction result to the automobile terminal system. According to the method, key events related to pedestrian behaviors can be effectively identified and aggregated, and the accuracy and efficiency of pedestrian behavior intention prediction are improved.

The invention relates to the field of meteorological temperature measurement, in particular to a meteorological temperature measurement method and system based on an optical fiber sensor, and the method comprises the steps: collecting data information in an environment through the optical fiber sensor, carrying out the preprocessing of the obtained different parameter information, and providing a data basis for the meteorological temperature measurement method; establishing a meteorological temperature prediction neural network model according to the preprocessed data information, and predicting the meteorological temperature; the meteorological temperature measurement process is improved according to the requirements of different meteorological environments and the prediction result of the meteorological temperature; and evaluating the improvement result of the specific process of meteorological temperature measurement, establishing a temperature measurement evaluation model, and evaluating the effect of the temperature measurement result in practical application. High-precision temperature measurement is provided, meteorological temperature data can be monitored in real time through manual intervention, the change condition of the meteorological temperature is reflected in time, and the whole measurement process has high reliability and stability.

The invention relates to the technical field of oil exploitation, in particular to a method and system for calculating the hydrocarbon generation pressurization contribution rate of high-TOC oil shale, and the method comprises the steps: calculating the TOC content of the oil shale; establishing a target longitudinal and transverse wave velocity relational expression; reconstructing the longitudinal wave velocity of the high TOC oil shale based on the target longitudinal and transverse wave velocity relational expression to obtain a reconstructed longitudinal wave velocity; constructing a pressure prediction basic model, and calculating the pore pressure and background pressure of the high-TOC oil shale under-compaction cause based on the pressure prediction basic model and the reconstructed longitudinal wave velocity; based on the pore pressure and the background pressure, obtaining a hydrocarbon generation supercharging pressure coefficient difference, and obtaining a speed difference between the actually measured sound wave speed and the reconstructed longitudinal wave speed; and performing rendezvous analysis on the speed difference and the pressure coefficient difference to obtain a target fitting formula, and calculating the contribution of hydrocarbon generation pressurization based on the fitting formula. According to the method, quantitative calculation of the hydrocarbon generation pressurization contribution of the high-TOC oil shale and high-precision prediction of the formation pore pressure are achieved.

The invention discloses a data prediction method and device based on a time sequence model, and the method comprises the steps: collecting historical data in a preset time range, and carrying out the normalization processing of the historical data; predicting the normalized historical data by using each network model in the trained time sequence model to obtain prediction data corresponding to each network model; and according to the prediction data corresponding to each network model, utilizing a linear regression model to obtain prediction data of a predetermined time point.

The application discloses a pipeline erosion working condition prediction method based on POD-Kriging, and relates to the field of pipeline erosion prediction. The method comprises the following steps: determining an input parameter set and an output physical quantity of a reduced-order model based on a ROM database and in combination with variable ranges of industrial working conditions; selecting a plurality of design points based on the parameter value interval of the input parameter set, and obtaining the output physical quantity corresponding to each design point to construct a training data set; constructing an initial reduced-order model based on the training data set by performing an intrinsic orthogonal decomposition method and a spatial interpolation algorithm; and performing collaborative optimization on the number of intrinsic modes in the initial reduced-order model and the number of design points to obtain an optimized reduced-order model. The application establishes parameter mapping through the intrinsic orthogonal decomposition and the spatial interpolation algorithm, and realizes the collaborative improvement of the calculation efficiency and the accuracy in the industrial pipeline erosion field prediction by combining the collaborative optimization of the mode number and the design points.