11results about How to "Realize intelligent generation" patented technology

This application relates to the interdisciplinary field of artificial intelligence and reliability systems engineering, and provides a method and apparatus for intelligent generation of equipment fault behavior logic models based on LLM (Limited Linear Modeling). This method combines a vector database to achieve enhanced retrieval, constructs an agent-based framework for generating equipment fault behavior logic models, and then generates structural elements in the agent for each business component involved in the equipment fault behavior logic. Based on the model structure, the results are integrated and merged, ultimately achieving a complete and runnable equipment fault behavior logic simulation model. This method integrates the interactive modeling capabilities of agents with the semantic understanding and logical reasoning capabilities of large language models, enabling intelligent generation of fault behavior models for complex equipment and effectively improving the generation efficiency of equipment fault behavior models.

This invention discloses a method and system for automated generation and optimization of database table structures. The method specifically includes: receiving the user's backend project source code; extracting a semantic information network graph related to data persistence through static code scanning; inputting the semantic information network graph into an intelligent parsing engine to analyze code logic relationships and obtain index recommendation strategies and potential table structure design flaws; based on the index recommendation strategies and potential table structure design flaws, identifying sensitive fields and recommending encryption or de-identification schemes to obtain a first table structure; performing automated stress testing on the first table structure and adjusting the index strategy and partitioning scheme based on the test results; and optimizing the first table structure according to the adjusted index strategy and partitioning scheme to obtain a second table structure. This invention achieves intelligent generation and optimization of database table structures, improving development efficiency, enhancing maintainability, improving user experience, and ensuring data security.

The invention discloses an operator fusion model training method and apparatus, a device, a storage medium and a program product. The method comprises the steps of obtaining performance data of an operator fusion model in a historical training process; wherein the performance data comprises at least one of operator operation performance data and operator calculation structures corresponding to different operator combinations; preprocessing the performance data, and obtaining key feature data from the preprocessed performance data; carrying out updating training on the operator fusion model by utilizing the key feature data; in the updating training process, adjusting and optimizing hyper-parameters of the operator fusion model to obtain a trained operator fusion model; wherein the operator fusion model is used for predicting the performance of the operator fusion strategy. By adopting the embodiment of the invention, the problem of overhigh memory occupation during model training can be avoided, the normal operation of model training is ensured, and the model training efficiency is improved.

The application provides a classical music cross-modal high-reliability experimental data set construction method for full-scene teaching application, comprising the following steps: collecting multi-modal data such as audio, video and music score, constructing an original data set, standardizing each modal data by using a preprocessing technology, and obtaining a multi-modal data set in a unified format; constructing a knowledge graph according to a semantic feature vector, wherein a node represents a music element, and an edge represents a semantic relationship between elements; encoding the knowledge graph by using a graph convolution network to obtain a semantic representation of teaching content; integrating multi-modal teaching resources into an immersive teaching scene by using virtual reality rendering technology, presenting a content sequence in real time, and obtaining a dynamic teaching experience; updating the knowledge graph and the semantic feature vector by continuously collecting learner interaction data, optimizing the cross-modal fusion model by using an incremental learning algorithm, and obtaining an adaptive teaching data set.

The application discloses a power distribution network multi-scene energy storage method, device and medium, and belongs to the technical field of power distribution network energy storage, and comprises the following steps: establishing a unified data interface pool, continuously accessing and preprocessing energy storage data streams, selecting available resources, calculating the dynamic weight of each type of data stream, generating preliminary scheduling instructions, and constructing a dynamic capability image; a multi-objective matching algorithm based on fuzzy comprehensive evaluation selects the optimal energy storage unit combination from the available resources, outputs the optimal energy storage unit set list, assigns a response mode label, forms the final optimized scheduling plan, extracts the response mode label, triggers the construction of a different power level energy storage rapid response framework, and associates multiple energy storage units under different levels of energy storage framework. The application significantly improves the response capability and operation resilience of the power distribution network to uncertain events, and is suitable for various complex application scenarios such as disaster emergency, planned scheduling, and collaborative regulation.

The present application relates to the technical field of the integration of artificial intelligence and business intelligence, and particularly relates to a ternary dynamic growth method and system based on AI intelligence driving, which comprises three modules of value potential, system kinetic energy and growth efficiency linked and configured through a ternary intelligence driving interaction interface, uses an AI algorithm containing a nonlinear coupling term to calculate a comprehensive growth index in real time, and combines multi-source data initialization, simulation stress testing, senior management intervention, online learning and a closed-loop feedback mechanism to realize adaptive optimization and dynamic evolution of enterprise growth strategies; the present application can break through the static and fragmented limitations of traditional business growth mode design, and improve the effect, intelligence and self-iteration of the growth path.

The invention discloses a garden drawing generation method and system based on plant community intelligent configuration, and relates to the technical field of garden drawing generation, and the method comprises the steps: dividing a design region into a plurality of ecological cells in the design region, collecting the environment feature information, related to the ecological environment, of each ecological cell, performing normalization operation on the environment feature information to generate ecological morpheme vectors of ecological cells; the method comprises the following steps: constructing a community unit consisting of various plants, extracting behavior attributes of the community unit, and performing normalization operation on the behavior attributes to generate a community behavior spectrum of the community unit; according to the ecological morpheme vectors of the ecological cells and the community behavior spectrums of the community units, the fitness degree of each ecological cell and each community unit is calculated, the community unit with the maximum fitness degree serves as the design scheme of the corresponding ecological cell, and therefore the garden drawing is generated.

The invention provides a photovoltaic power prediction method and device based on localized meteorological interpolation, relates to the technical field of photovoltaic power generation prediction, and enables other target sites lacking meteorological data to learn the relationship between the power of a source site with complete meteorological data and meteorological variables through a localized meteorological interpolation model, thereby completing the localized meteorological interpolation. The missing meteorological data is generated, complete meteorological feature input is provided for subsequent prediction, and the problem that the prediction precision is reduced due to missing meteorological data is effectively solved. The mapping relation between power and weather is established through transfer learning instead of geospatial interpolation directly, so that missing meteorological data can be generated under supervised learning, and the problem that a prediction result is easy to distort when a complex terrain or weather changes sharply due to the fact that an existing method depends on the assumption that the meteorological data changes smoothly in space can be solved. According to the method, high prediction precision can still be kept under the environment of complex terrains or violent meteorological field changes.

This invention discloses a method, apparatus, device, and storage medium for generating a construction process simulation animation. The method includes: acquiring a target building model; identifying various building components from the target building model and forming a bounding box to surround all building components; determining multiple keyframe positions for shooting the target building model based on the bounding box, and forming a camera shooting path based on all determined keyframe positions; dividing all building components into multiple ordered animation segment groups according to preset construction procedure rules to form an animation segment sequence; synchronizing and merging the camera shooting path and the animation segment sequence on a unified timeline to generate a construction process simulation animation of the target building model. This invention achieves automatic camera path planning and intelligent generation of construction process simulation animation by automatically analyzing model spatial information and construction logic.

The application belongs to the technical field of file storage, and particularly relates to a file intelligent storage allocation method and system, which comprises the following steps: constructing a joint knowledge base composed of a file standard storage process sub-base, a historical storage scene information sub-base and a storage device resource information sub-base; constructing a demand depth optimization reasoning model, and performing deep retrieval on the knowledge base by using a fast association index; acquiring file and scene data in real time, and calculating the current environment safety level and file damage risk probability by using a safety evaluation model; based on the above evaluation results, generating an initial evaluation score and a storage strategy by using a comprehensive evaluation model; performing secondary matching retrieval by using the reasoning model to obtain an optimized storage allocation strategy; and finally dynamically adjusting storage resource allocation according to the optimized storage allocation strategy and real-time device state; the application realizes intelligent generation and adaptive adjustment of file storage strategies, and improves storage efficiency and safety.