9 results about "Lifecycle model" patented technology

The present invention provides a navigation message lifecycle model learning method, GNSS signal processing method and electronic device, comprising: acquiring GNSS navigation data, and analyzing the GNSS navigation data to learn the lifecycle model, wherein the lifecycle model includes information indicating the lifecycle behavior of at least one GNSS navigation message dataset.

The application discloses a kind of air situation analysis methods based on track full life cycle, comprising the following steps: step 1, extraction typical track event;Step 2, establish track full life cycle model;Step 3, realize the quantitative analysis of air situation;Step 4, abnormal event identification and extraction.The air situation analysis method based on track full life cycle proposed in the application introduces track full life cycle model into the field of air situation estimation for the first time, and can deeply understand air situation on this basis.The application can make the process of situation analysis clear, the result of situation analysis more accurate and more intelligent, so as to provide more definite and accurate situation information for later decision makers.

This application relates to the field of product carbon footprint calculation, and discloses a method and system for constructing a product carbon footprint model based on intelligent agents. This method automatically collects and standardizes product information from multiple data sources using a large language model, generates product production process flows and identifies emission sources through a lifecycle model inference module, simulates activity data using deep neural networks, and matches emission factors in a background database using semantic similarity. Finally, a carbon footprint calculation model is constructed based on the ISO 14067 standard. This method overcomes the problems of difficult data acquisition and time-consuming processes in traditional carbon footprint calculation methods, achieving intelligent construction of product carbon footprint models and improving the efficiency and accuracy of carbon footprint calculation.

The application discloses a photovoltaic energy storage power station intelligent operation and maintenance and collaborative control system based on big data, and relates to the technical field of new energy power system automation.The system reconstructs the space-time characteristics of multi-source heterogeneous data of a photovoltaic energy storage power station through a graph attention network, calculates data confidence based on the reconstructed residual error, identifies battery physical parameters online using a recursive least square method with a forgetting factor, calculates the health degree, generates a dynamic current constraint boundary containing linear derating logic in combination with real-time temperature, adopts a model predictive control strategy, updates internal parameters of a prediction model in real time to match the aging state of equipment, and introduces data confidence as a penalty term into a control action smoothing term of an objective function.The application realizes flexible continuous control under the sub-health state of equipment, effectively solves problems such as fault hard shutdown impact, misoperation caused by data noise and model mismatch in the whole life cycle, and the like.

This invention belongs to the field of rock science and discloses a method, system, device, and medium for calculating the Helmholtz free energy storage of brittle rocks throughout their entire life cycle. The method includes: acquiring multimodal characteristic data of the brittle rock to be analyzed, including structural features, mineral composition, mineral grain size, stress-strain values ​​at different stages, and elastic energy, dissipated energy, and total energy corresponding to different stress-strain values; inputting the multimodal characteristic data of the brittle rock to be analyzed into a life-cycle model for classification and prediction to obtain the evolution law of the Helmholtz free energy of the brittle rock to be analyzed throughout its entire life cycle; wherein, the life-cycle model is constructed based on neural networks and physical methods, including an input layer, a physical constraint layer, and a prediction layer connected sequentially. This invention can quantify the coupled influence of different factors on the energy evolution of rocks and is applicable to rock mass engineering analysis under complex geological conditions.

The invention discloses a community model life cycle intelligent management system and method based on behavior driving, and relates to the related field of model management, and the method comprises the steps: registering and storing model metadata of a community model; deploying a lightweight monitoring agent to collect model interaction use data and user behavior index data in real time, and constructing a community model behavior dynamic portrait; according to the standardized life cycle model, constructing a community model state conversion logic, performing circulation state analysis on the dynamic behavior portrait of the community model, and determining a current circulation state of the model; operation strategy analysis is carried out based on the model metadata and the current circulation state of the model, community model operation strategy resources are configured, and model full-life-cycle management is carried out. The technical problems of lack of model behavior dynamic perception and inaccurate operation strategy adaptation in existing community model life cycle management are solved, and the technical effects of dynamically perceiving model behavior changes and improving the operation strategy adaptation accuracy are achieved.

The present application belongs to the technical field of power battery recycling evaluation, and particularly relates to a system and method for evaluating the synergistic effect of pollution reduction and carbon reduction in a power battery recycling process. A configuration module receives user input of process combination information to be compared, and generates baseline data by constructing a life cycle model with 1 kWh as a functional unit. A collection module retrieves basic emission data and material consumption and environmental emission data at each stage according to the process combination information to be compared, and generates a data set to be evaluated. An evaluation module calculates the primary energy consumption value and global warming potential value of two process combinations, and marks high-impact links. A calculation module determines a pollution reduction and carbon reduction synergy index. An output module generates comparison results of the two process combinations according to the index. The present application quantitatively evaluates the synergistic degree of different recycling processes in the two dimensions of pollution control and carbon emission reduction by calculating the pollution reduction and carbon reduction synergy index, and accordingly recommends a recycling process path with the optimal comprehensive environmental benefit to the user.