7results about How to "Solve forecasting problems" patented technology

This invention relates to the field of oil and gas field exploration and development technology, and particularly to a method for constructing classification curves for low-permeability gas reservoirs in the sea using integrated static and dynamic data. The method includes: Step S1, preprocessing logging data and core data from the entire well section; Step S2, based on Step S1, delineating target sections with low-permeability gas reservoirs, selecting the main influencing parameters related to reservoir static layers and production capacity, and extracting curves for each main influencing parameter of the target section; Step S3, based on Step S2, normalizing the extracted curves for each main influencing parameter, and constructing reservoir classification curves according to the correlation between each main influencing parameter curve and production capacity; Step S4, based on Step S3, verifying the accuracy of the reservoir classification curves using test production capacity data from different dynamic layers of the reservoir within the target section. Using this reservoir classification curve for the classification of low-permeability gas reservoirs in the sea has high accuracy and operability, and can be used to accurately predict production capacity.

The application relates to the technical field of data analysis and intelligent marketing, and particularly discloses a market trend prediction and precision marketing system based on deep learning. The system comprises a data interface module, an interlocking collaborative analysis engine and a strategy generation module. The interlocking collaborative analysis engine sequentially performs market trend prediction and user behavior analysis, and through a two-way coupling feedback step, converts the market prediction result into an adjustment signal for a user interest model, and feeds the emerging pattern identified in the user behavior to the market prediction model as a correction input; and then updates the two models based on the coupled new data, to realize collaborative evolution. The strategy generation module generates marketing instructions under resource constraints according to the collaborative analysis result. The application realizes the deep integration and co-evolution of market trends and user preferences by forcibly establishing and continuously optimizing a two-way interaction channel between macro prediction and micro analysis, so that the foresight, precision and self-adaptive ability of the marketing strategy are improved.

The application relates to the technical field of hardware equipment quality tracing, and discloses a hardware full-life-cycle quality tracing method and system based on IoT, which comprises the following steps: acquiring multi-dimensional real-time data flow and arranging the same into a real-time running data set; extracting distribution characteristics based on a historical data archive to obtain a benchmark reference space; projecting the real-time data to calculate a deviation quantitative value, correcting environmental deviation when the deviation quantitative value exceeds a threshold value to obtain a deviation result; extracting degradation characteristics to match historical trajectories to locate a degradation process; performing time sequence analysis to predict residual life to obtain a failure time window; and generating and arranging maintenance intervention instructions into a scheduling instruction set. The method realizes hardware full-life-cycle quality tracing and early abnormality early warning, improves maintenance accuracy, and reduces fault loss.

The application provides a human pose estimation method based on attention and adversarial network, a medium and equipment; wherein the method is: inputting an image to be predicted into a data enhancement module based on an adversarial network for data enhancement processing to obtain a data enhanced image; inputting the data enhanced image into a human pose estimation network based on multi-scale spatial attention to obtain an output heat map; converting the output heat map into spatial coordinates of each key point to generate a human pose, and then obtaining a human pose estimation result. The method can obtain spatial attention from different scale features, simultaneously perform multi-scale fusion on the attention, combine global and local attention features, finally generate more fine spatial attention, and can solve the prediction problem of occluded images and complex background images.

This invention discloses a method, modeling method, system, and application for predicting dynamic contact angle distribution, belonging to the technical field of predicting dynamic contact angle distribution of micro-protrusions. The method for predicting dynamic contact angle distribution provided by this invention constructs a joint probability density function of horizontal distance and height difference based on the normal distribution law of the horizontal distance and height difference between adjacent micro-protrusions on a rough surface; derives the probability density function of the static micro-protrusion contact angle through integral transformation and Leibniz's differentiation rule; derives the first and second relations through cyclic load experiments; and constructs a probability density function model of the dynamic contact angle based on the first and second relations and the probability density function of the static contact angle. By integrating the static model and the dynamic relations, it achieves the prediction of contact angle distribution under different cycles, adapting to the evolution of contact characteristics under varying loads, and effectively solving the problem that traditional static models cannot reflect the dynamic evolution of the contact angle under cyclic loads.

The present application relates to artificial intelligence, and provides a drug candidate library construction method, device, equipment and storage medium. The method performs site mutation on the initial protein to obtain a new protein, performs graph characterization on the new protein and the initial protein to obtain a new characterization vector and an initial characterization vector, calculates a spatial structure loss value of the new protein and the initial protein, inputs the new characterization vector and the spatial structure loss value into a protein property prediction model to obtain a predicted property, and screens a target protein from a plurality of new proteins. Amino acid sequences are generated based on antigen-antibody complexes and disease antigens, and the target protein and the amino acid sequences are combined to improve the rationality of generating the drug candidate library. In addition, the present application also relates to blockchain technology, and the drug candidate library can be stored in the blockchain.

The invention discloses a dynamic replenishment method and system based on consumption trend prediction, and relates to the technical field of inventory management. The method comprises the following steps: step 100, constructing an inventory full-link digital twin, synchronizing physical inventory dynamic data in real time and identifying potential bottlenecks; step 200, collecting multi-dimensional core data, and constructing a consumption behavior inventory state external environment causal link graph based on a knowledge graph technology; step 300, inputting the causal link map and an inventory constraint factor into a causal reasoning model, and outputting a consumption trend prediction result and an inventory feasibility verification report in combination with quantum lightweight calculation; and step 400, generating an initial replenishment scheme based on a federated learning driven inventory health degree scoring system, and outputting an optimal replenishment scheme after the digital twinborn scene rehearsal optimization. According to the invention, accurate matching of dynamic replenishment prediction and inventory actual bearing capacity is realized, real-time response and cross-scene self-adaption characteristics are realized, and the feasibility of replenishment scheme landing is greatly improved.