9 results about "Product innovation" patented technology

The invention provides an electromechanical product innovative design problem analysis method and system based on a pre-training model. The method and system are used for solving the problem that the accuracy and efficiency of product problem analysis are low. The method comprises the following steps: acquiring an innovative design problem description text and a technique analysis tool type for a target mechanical and electrical product; searching a structured prompt template corresponding to the technical analysis tool type from a prompt template library, wherein a corresponding relationship between the technical analysis tool type and the structured prompt template is stored in the prompt template library; filling the innovative design problem description text into a structured prompt template to obtain a technique analysis prompt engineering text; reasoning the technical analysis prompt engineering text through the pre-training model to obtain a technical analysis result of the target mechanical and electrical product, the technical analysis prompt engineering text being used for guiding a thinking chain prompt reasoning process of the pre-training model.

The application provides a metadata analysis processing method and device, and relates to the technical field of big data analysis processing.The method comprises the following steps: collecting metadata in a data source; acquiring a business process, declaring the granularity of a metadata model according to the business process, and constructing a dimension table and a fact table according to the granularity; taking the business process as a modeling driver, and establishing a metadata model according to the metadata, the dimension table and the fact table; when a data analysis request is acquired, performing data analysis by using the metadata model to obtain an analysis result.The metadata model is established by collecting metadata, the metadata of enterprises scattered in multiple application systems is centrally managed, a complete and comprehensive data structure relationship is presented for the enterprises, the enterprises are assisted in centrally and efficiently managing data assets, the metadata analysis processing of different business requirements can be met, data value can be mined from the analysis result to guide business or product innovation, and the production of enterprises is empowered.

The application provides an enterprise full life cycle credit risk decision method and system based on multi-source data, the system gathers multi-source heterogeneous data such as industry and finance, and breaks the information island; the system extracts the characteristics of nine dimensions such as enterprise basic information and operation behavior, constructs super web variable, traces back the history growth context of the enterprise, and identifies the dynamic risk characteristics of the enterprise in different life cycle stages; the system supports self-service training of quantitative models, and can be applied to product innovation, risk decision and post-loan management and other credit whole processes. The application realizes the dynamic risk identification and self-service decision of the credit whole process by deeply fusing multi-source heterogeneous data to construct the enterprise full life cycle credit portrait, and effectively helps financial institutions to break the data island and realize digital transformation.

The invention discloses an enterprise innovation capability optimization model based on a digital technology and application thereof, belongs to the technical field of enterprise innovation management and digital technology application, and integrates the technologies of data management, big data analysis, AI prediction, digital collaboration and the like, so that an enterprise can quickly respond to market and personalized user needs, and the enterprise innovation capability is optimized. And the product innovation and competitiveness are improved. Through the Internet of Things and an online platform, an enterprise can accurately capture market trends and user preferences; big data and an AI algorithm assist in deep insight and decision making; a digital platform and cloud computing promote remote cooperation; smart tags and language processing optimize knowledge management. 3D printing and VR accelerate product development, and a user community promotes user participation. The security is guaranteed by multi-factor authentication and regular auditing, and an organization culture and continuous learning mechanism ensures that an enterprise adapts to changes. The model not only enhances innovation, but also provides the advantage of sustainable development, and is the key of digital transformation.

The invention relates to the technical field of data processing of financial and medical scenes, and discloses an insurance product data processing method and device, computer equipment and a storage medium, and the method comprises the steps: accessing multi-source heterogeneous data, and processing the multi-source heterogeneous data into standardized structured data resources and unstructured data resources; calling a plurality of agents to process the structured data resources and the unstructured data resources to generate a plurality of items of intermediate data related to the insurance product; and receiving the multiple items of intermediate data, performing comprehensive optimization on the multiple items of intermediate data by using a multi-objective optimization algorithm, and generating and outputting an optimal insurance product data packet. According to the invention, a complete intelligent product research and development closed loop is constructed, and full-process coverage from data acquisition to product output is realized through multi-agent division cooperation; the product innovation efficiency is remarkably improved, the research and development period is greatly shortened, and meanwhile the market precision and compliance reliability of products are effectively improved through data-driven intelligent analysis.

This invention discloses a product design method, apparatus, and computer storage medium, relating to the field of product design technology. The invention includes product design data acquisition, knowledge preprocessing, multi-source heterogeneous knowledge fusion, and product design optimization decision-making. By integrating objectively existing demand, resource cost, time cost, information flow, and design process structure data, a multi-objective optimization model is constructed with function, cost, and evolutionary trends as its core. Design constraints are introduced to establish an optimization model that maximizes process value. Multiple evolutionary algorithms are used to solve for the optimal structural parameters and resource allocation strategies. Decision-making indicator data are analyzed from the entire design stage. This provides intellectual support for designers to expand innovative thinking, significantly shorten the R&D cycle, and enhance product innovation and competitiveness.

The invention discloses a modern product innovative design method based on traditional process element fusion, which comprises the following steps: S1, establishing a dual-attribute material gene database of a traditional material, and establishing a physical deformation model of a modern carrier through finite element analysis; s2, a product design requirement is received, a material pattern collaborative algorithm is called to recommend a material combination and generate an adaptive pattern, and the pattern detail level is matched with the material precision; s3, simulating actual effects of the material and the pattern in AR, and collecting user evaluation and optimizing parameters of a material pattern collaborative algorithm through A / B test; therefore, the problems of neglect performance, dilution of pattern culture, insufficient durability, long design period, large subjective deviation, disjunction with user requirements and the like in the prior art are solved.

The invention provides a product innovation tool recommendation method and system based on a pre-training model. The method comprises the steps of obtaining a design requirement standard text for a target product; obtaining a preset innovation tool list, and filling the preset innovation tool list and the design requirement standard text into a preset prompt word template to obtain a prompt project text; reasoning the prompt project text through the pre-training model to obtain a recommendation tool and a recommendation reason corresponding to the design requirement standard text, the recommendation tool being at least one innovation tool in a preset innovation tool list. Potential rules of tool recommendation have been learned in large-scale data training through the pre-training model, and relevance between requirements and tools can be identified more efficiently in combination with normalized processing of the prompt project text on input information, so that recommendation tools and recommendation reasons output by reasoning of the pre-training model are more targeted and logical, and the recommendation efficiency is improved. Therefore, the recommendation accuracy is remarkably improved.