25results about How to "Realize intelligent generation" patented technology

The invention provides a cerebral hemorrhage personalized treatment scheme optimization method and system based on big data analysis, and relates to the technical field of data analysis, and the method comprises the steps: constructing a cerebral hemorrhage patient multi-source heterogeneous clinical database, extracting feature subsets, carrying out semantic alignment, carrying out time sequence modeling and fusion, and obtaining a patient panoramic feature representation; constructing a cerebral hemorrhage diagnosis and treatment knowledge graph, adding the cerebral hemorrhage diagnosis and treatment knowledge graph to a preset graph attention network, distributing weights, obtaining knowledge-enhanced patient feature representation and taking the knowledge-enhanced patient feature representation as a state, generating an action space based on an optional treatment scheme, constructing a reward function and determining a candidate treatment scheme; performing medication suitability analysis, performing semantic conflict identification in combination with the patient allergy history and complication, and performing screening to obtain a suitable candidate treatment scheme set; and for each scheme, predicting a multi-dimensional prognosis index, constructing a multi-criterion decision matrix, combining personal influence factors, adjusting the weight of each index, modeling an optimization problem and determining an optimal treatment scheme.

The invention discloses a new energy project intelligent planning method and system based on a large language model, and relates to the technical field of new energy planning, and the method comprises the steps: constructing a new energy project planning knowledge base; the new energy project planning knowledge base comprises basic data required by project planning and is used for providing data support for the optimization model; based on the training data in the new energy project planning knowledge base, performing field adaptability training on the large language model to obtain a special large language model in the new energy project planning field; and based on a project demand input by a user, analyzing project parameters through the special large language model, inputting an analysis result into the optimization model, and generating a planning scheme of a new energy project. According to the method, automatic conversion from a natural language demand to a professional planning scheme is realized, the accuracy of energy balance constraint is ensured through the topological structure diagram of the energy system, a flexible switching optimization target of economic benefits and environmental benefits is supported, and finally intelligent generation and evaluation of the planning scheme are realized.

The invention discloses a method and system for automatically generating a digital figure, and relates to the field of digital figure intelligent generation. The method comprises the following steps: obtaining a face image of a to-be-modeled object, and obtaining a digital figure expected style text description input by a user; performing multi-scale feature analysis on the face image of the to-be-modeled object by adopting an artificial intelligence-based image processing and text analysis technology, wherein the digital human expects semantic coding of style text description; therefore, the three-dimensional model of the digital person object is intelligently generated according to the information obtained by cross-modal combination between the shallow and deep fusion features of the to-be-modeled object image and the expected semantic features of the digital person, and the generation of the digital person can be guided through text description input by a user. According to the method, each digital figure can better reflect the personalized demand and style preference of a user, meanwhile, the dependence on manual design and the limitation of traditional template design are reduced, more flexible design options are provided, and intelligent generation of the digital figure is achieved.

The invention provides a work order generation method and device, an intelligent work order filling system and a work order processing system.The work order generation method comprises the steps that a reference work order with the highest relevancy with equipment basic fault information input by a user is obtained from an enterprise asset management system in a keyword matching search mode; if a reference work order with relatively high relevancy with the equipment basic fault information input by the user cannot be obtained from the enterprise asset management system, determining a historical work order with the highest similarity in a vector database as the reference work order according to vector data corresponding to the equipment basic fault information input by the user; and according to at least one of the confirmation information and the modification information of the user on the reference work order, generating a current work order, the current work order comprising the equipment parameters and the processing method information. According to the method, traditional keyword matching search and large language vector retrieval technologies are ingeniously combined, so that the problems of long time consumption and unstable quality existing in manual work order filling in the prior art are solved.

The invention discloses a nickel-based superalloy microstructure image diffusion generation method, system and equipment, a medium and a product, and relates to the field of superalloy microstructure reconstruction. The method comprises the following steps: gradually diffusing an original training image into a Gaussian noise-like image by adopting a forward diffusion process of a denoising diffusion generation network, and gradually denoising in a reverse diffusion process to obtain a nickel-based high-temperature alloy microstructure-like image; adopting a geometric structure feature loss penalty mechanism to obtain a trained denoising diffusion generation network based on the geometric feature difference value; and adopting a back diffusion process of the trained de-noising diffusion generation network to obtain a virtual microstructure image, and screening to obtain a final microstructure image. According to the method, the problems that data samples are scarce, and acquisition of the alloy internal microstructure is tedious, time-consuming, high in cost and the like are solved, similar microstructure images are visually represented, and intelligent generation of the virtual microstructure is achieved.

The invention provides an air conditioning device. The air conditioning device comprises a data acquisition module and a control module, the data acquisition module is configured to collect environment parameters, operation parameters and / or user behavior parameters of the air conditioning device; the control module is configured to establish a prediction model based on a Transform architecture according to a historical sample; predicting predicted set temperatures of a plurality of future target moments based on the established prediction model; moreover, when the user set temperature at the future target moment deviates from the predicted set temperature, the user set temperature is corrected to be the predicted set temperature; the historical samples are generated and stored in a preset database based on the environment parameters, the operation parameters and / or the user behavior parameters associated with the corresponding timestamps. According to the invention, high-precision, stable and self-adaptive future set temperature prediction can be realized, and the intelligent degree of the air conditioning device is improved.

The invention provides a three-dimensional model generation method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of computer vision. The generation method comprises the steps that a two-dimensional image is acquired, and the two-dimensional image comprises a plurality of objects; on the basis of a graph neural network model, feature extraction is carried out on the two-dimensional image, a semantic feature vector of each object is obtained, and the semantic feature vectors are used for representing the pixel position of the object in the two-dimensional image and the relation between the object and other objects; based on a mask region convolutional neural network Mask RCNN model, performing instance segmentation on the two-dimensional image to obtain a mask of each object; and performing three-dimensional reconstruction on the two-dimensional image based on the semantic feature vector and the mask of each object to obtain a corresponding three-dimensional model. The problems that the real-time processing capacity is low, the scene application range is narrow, the layout effect is poor and the layout efficiency is low in the prior art are at least solved. The method is suitable for three-dimensional layout and three-dimensional reconstruction scenes.

The invention provides an intelligent generation method, system and device for game images and animations and a medium, and the method specifically comprises the steps: obtaining user design demand data, carrying out the feature extraction and style recognition of the user design demand data through a deep learning algorithm, and obtaining the key feature data of the game images and animations; obtaining specified style parameters, and based on the specified style parameters, analyzing the game image and animation key feature data according to a pre-trained GAN model to generate a target game image and animation; acquiring user equipment data of current user equipment, and adaptively displaying the target game image and animation on the current user equipment according to the user equipment data. According to the method, the process of game development and animation production is simplified, the technical threshold is reduced, and the creation efficiency and quality are improved.

The invention discloses a multi-agent simulation and planning optimization method based on man-machine interaction. The method comprises the steps of target site basic data acquisition, man-machine interaction intelligent platform establishment, community facility planning multi-scheme generation, community multi-agent simulation and supply and demand index measurement and calculation, and community facility planning scheme comparison, selection, optimization and comprehensive output. According to the method, a community facility planning scheme is generated in a man-machine interaction mode, a community facility supply and demand scene is simulated and evaluated through a multi-agent model, a man-machine interaction planning design process can be combined with the multi-agent model, and a foundation is laid for intelligent community facility layout and multi-agent auxiliary planning design. According to the method, the limitation that traditional community facility planning heavies the current situation of community facility construction and lightens the actual demand characteristics of community residents is overcome, and the problem that a planning scheme is intelligently generated and deduced and evaluated in a man-machine interaction mode is solved.

The invention provides a construction and scheduling application platform system of an urban rail transit model. Comprising a storage management server, a model construction server and a model scheduling application server, the storage management server is used for storing and managing basic data, an AI algorithm and a model, transmitting the data, the algorithm and the model to the model construction server, receiving a system algorithm transmitted by the model construction server, and updating, managing and storing the system algorithm; the model construction server performs model construction and solution according to the instruction of the model scheduling application server, supports the demand of the model scheduling application server, receives the feedback of the model scheduling application server and performs model online updating; and the model scheduling application server is used for realizing calling and evaluation of each unit domain model. The system integrates a multi-field service application function, intelligent generation and dynamic adjustment of a solution scheme are realized, and the automation and intelligence level of service processing is improved.

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 invention relates to a safety supervision method and device for dangerous and waste products of a transformer substation and computer equipment. The method comprises the following steps: acquiring a waste identity information identifier of each dangerous waste generated by a transformer substation, and identifying a dangerous waste type and processing risk information of each dangerous waste based on the waste identity information identifier of each dangerous waste; and based on the hazardous waste type and the processing risk information of each hazardous waste, identifying the hazardous waste processing flow and the processing detection demand information of each hazardous waste, and executing the hazardous waste processing flow of each hazardous waste to obtain the flow monitoring information of each hazardous waste, thereby adjusting the hazardous waste processing flow of each hazardous waste. And returning to execute the processing detection demand information based on each dangerous waste product, and executing the above steps to obtain processing supervision information of each dangerous waste product. By adopting the method, the safety supervision effect on dangerous and waste products can be improved.

The invention belongs to the field of resume automatic generation, and discloses an intelligent resume generation system based on natural language processing, which comprises a position information acquisition module, a resume information storage module, a template storage module and a resume generation module, the position information acquisition module is used for acquiring recruitment information from a recruitment website; the resume information storage module is used for storing work experience information of job seekers; the template storage module is used for storing a resume template, the resume template comprises a basic information filling area and a working experience filling area, and basic information of a job seeker is filled in the basic information filling area in advance; and the resume generation module is used for performing screening from the work experience information by adopting a natural language processing technology according to the recruitment information to obtain screening information, and filling the screening information in a salary experience filling area in the resume template so as to generate a resume. According to the invention, intelligent generation of resumes is realized, and the efficiency of batch delivery of resumes by job seekers is effectively improved.

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 invention discloses a video processing method and device, electronic equipment and a computer storage medium, and aims to improve the video processing efficiency. The method comprises the following steps: an equipment side terminal determines a target video recording mode in response to a first control instruction of a user; in response to a second control instruction of the user, starting video recording in the target video recording mode; in response to a third control instruction of the user, generating a highlight video tag for marking a highlight moment in the video; and in response to a fourth control instruction of the user, ending video recording, and sending the video and the video tag carried by the video to the system side terminal. The system side terminal obtains the video sent by the device side terminal and the video tag carried by the video; displaying a video selection page; the video selection page comprises a first historical video shot by the device side terminal within a preset time period; and in response to a first trigger operation input by the user based on the video selection page, generating a first initial video based on the first historical video and the video tags carried by the videos in the first historical video.

The embodiments of the present invention disclose a method and module for autonomously constructing complex products based on human-machine hybrid enhancement, the method comprising: S10, establishing a parameterized knowledge model mapping from key feature states to actions based on human knowledge, encoding the parameters to be measured in the knowledge model into an output vector of a neural network; S20, encoding the input vector of the neural network according to the key feature states of the environment and the output value of the reward function; S40, intelligent agent configuration; S50, generating training data mapping from key feature states to actions based on human-known empirical knowledge, using the training data to reversely fit the neural network parameters, and driving the knowledge model to deduce in the training environment; S60, continuously optimizing the neural network parameters based on reinforcement learning until the training of the neural network is completed, and finally achieving the self-adaptation of the intelligent agent.

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.