4 results about "Predictive capability" patented technology

The invention belongs to the technical field of water environment monitoring and early warning, and discloses a lake and reservoir chlorophyll a concentration prediction method based on an SO-KNN model. According to the invention, multi-time scale meteorological cumulative effect features are introduced to enrich information representation, and an SO-KNN intelligent prediction model is constructed. According to the method, under the conditions of data scarcity and non-equilibrium, the chlorophyll a concentration, especially the high-precision and strong-generalization prediction capability of the water bloom risk critical point, is remarkably improved. The model is simple in structure and efficient in calculation, the common defects of overfitting, insufficient generalization ability and the like of a complex machine learning model in the scene are effectively overcome, and a reliable and practical innovative technical solution is provided for early water bloom warning of northern reservoirs and water areas with similar data conditions.

The present application relates to the technical field of geological exploration, in particular to a coal mine GIS transparent geological management system fusing multi-source geological exploration data, comprising a multi-source geological and gas monitoring data acquisition module: obtaining structural geological data and dynamic gas data, forming a structure-gas joint observation data set; a structure-gas coupling modeling module: constructing a three-dimensional geometric model, dynamically adjusting the fracture development zone and the stress concentration area, and generating a structure-gas double-field coupling three-dimensional geological model; a model dynamic updating and local feedback correction module: when the gas sensor detects abnormal changes or new drilling data is accessed, triggering an automatic updating mechanism; a GIS transparent visualization and risk labeling module: using a multi-layer fusion and asynchronous drawing mechanism for real-time rendering, and labeling and displaying high-risk areas. The present application can truly reflect the dynamic correlation between geological structure and gas evolution, and has stronger prediction ability and safety evaluation adaptability.

The application discloses a meteorological satellite cloud map extrapolation method based on a geographical attention mechanism, characterized by a deep learning framework constructed by GeoAttX, the introduction of a geographical attention mechanism to enhance the modeling ability of spatial features, and the synergistic effect of geographical semantic modeling, prediction path optimization and distribution correction mechanism, using the observation data of meteorological satellites to realize high-precision and low-error accumulation cloud prediction. The method uses a reverse greedy algorithm to realize flexible forecast time by reducing the autoregressive step, and proposes a second-order standardization method to normalize the pixel distribution, to maintain the consistency of brightness statistics and reduce error propagation. Compared with the prior art, the application has the advantages of using real-time stationary meteorological satellite observation data, having error suppression capability, geographical structure modeling capability, long-term stable prediction capability, high precision and stability, and can effectively improve the cloud motion extrapolation capability, and has important application value for weather forecasting and disaster warning.

The application discloses a kind of offshore low-permeability reservoir geology dessert prediction methods, comprising the following steps: low-permeability reservoir geology dessert prediction method includes the acquisition of low-permeability reservoir original well logging quality parameter and the determination of prestack inversion elastic parameter objective function, the construction of the isochronal inversion stratum framework of sedimentary mode guidance seismic recognizable scale, the construction of low-frequency model under paleogeomorphology constraint, prestack simultaneous inversion based on partial stack seismic data, reservoir quality parameter inversion based on bayesian discrimination, plane attribute extraction and characterization of three-dimensional RQI data body.The application is characterized by the distribution prediction of each period geology dessert of target interval by extracting the plane attribute of three-dimensional RQI data body, realizes the accurate characterization of offshore middle-deep low-permeability reservoir geology dessert, has better prediction ability, and then provides favorable support for development well site optimization deployment.