17 results about "Emerging technologies" patented technology

The invention provides a personalized learning path planning system and method, and belongs to the technical field of emerging software and emerging technical services, and the system comprises a data acquisition module which is used for collecting learning behavior data of a terminal user, obtaining a learner portrait package based on the learning behavior data, and sending the learner portrait package to a server; the path planning module is used for carrying out node matching on the learning ability feature vector and a pre-constructed knowledge and skill map, outputting a to-be-learned content node set, dividing learning advanced levels and generating learning path description containing to-be-learned nodes and the advanced levels, and the path generation module is used for generating a primary path planning scheme, the scheme feasibility verification module is used for carrying out scheme feasibility verification in combination with the learning advanced level and the path adaptation parameters, and then outputting a final executable path scheme, and the scheme execution module is used for executing the final executable path scheme and controlling learning content pushing and progress adjustment. The problems that in the prior art, personalized learning path planning is not high in precision, not high in adaptability, lack of dynamic optimization and the like are solved.

An AI-based energy edge platform is provided herein with a wide range of features, components and capabilities for management and improvement of legacy infrastructure and coordination with distributed systems to support important use cases for a range of enterprises. The platform may incorporate emerging technologies to enable ecosystem and individual energy edge node efficiencies, agility, engagement, and profitability. Embodiments may forecast, plan for, and manage the demand and utilization of energy in greater distributed environments. Embodiments may use AI, IoT, and technologies that filter, process, and move data more effectively across communication networks. Embodiments of the platform may leverage energy market connection, communication, and transaction enablement platforms. Embodiments may employ intelligent provisioning, data aggregation, and analytics.

The invention provides a hotspot technology mining method and system based on scientific and technological literature data, and relates to the technical field of scientific and technological information mining, and the method comprises the steps: firstly obtaining a scientific and technological literature data set containing papers and patent literatures, and constructing a current technical element network through technical phrase extraction and semantic normalization processing; dividing the technical element network segment into a time-serialized technical element network segment set according to time slices, calculating nodes and edge time sequence importance indexes to judge an emerging technical cluster, carrying out dynamic graph representation learning and future associated edge prediction on the set, generating a potential technical combination prediction set, and evaluating the potential technical combination prediction set; and finally, generating an emerging technology theme list and a technology fusion direction list in combination with an emerging technology cluster node growth trend and a prediction association edge evaluation result, thereby improving the accuracy, comprehensiveness and foresight of hotspot technology mining.

The invention belongs to the field of aviation, and particularly relates to a method for evaluating the agile efficiency of an air emerging technology, and the method comprises the steps: determining the core capability index parameters of the air emerging technology based on the principle and parameters of the new technology through air task environment influence factors and air task efficiency index mapping analysis; the method comprises the following steps: firstly, performing new technology equivalent digital modeling and evaluation, finally integrating a new technology digital model into a general air task simulation tool, performing air task deduction comprehensive analysis and calculation to obtain efficiency contribution of the new technology, and feeding back and guiding a new technology core capability index design interval and an application mode.

The invention discloses a credibility evaluation method for artificial intelligence software. The credibility evaluation method comprises the steps of 1, full-life-cycle data acquisition and preprocessing, 2, multi-dimensional collaborative evaluation, 3, scenarized rule adaptation, 4, comprehensive credibility analysis and early warning and 5, visual output of evaluation results. According to the method, traditional dimensions, a large model and multi-mode special evaluation are integrated, the credibility verification problem of an emerging AI technology is solved, and real-time monitoring and collaborative verification of credibility are achieved through full-life-cycle data collection and cross-dimension linkage logic.

Provided herein is an AI-based energy edge platform with a wide range of features, components, and capabilities for managing and improving traditional infrastructure, coordinating and coordinating with distributed systems to support important use cases for a series of enterprises. An Al-based energy edge platform may include a graphical neural network including a set of nodes representing at least one distributed energy resource (DER), respectively, and a set of edges interconnecting the set of nodes, respectively, where each edge represents at least one energy related feature between at least two nodes of the set of nodes. The platform may employ emerging technologies to improve the efficiency, flexibility, participation and profitability of an ecosystem and a single energy edge node. Embodiments may predict, plan, and manage energy demand and utilization in a larger distributed environment. Embodiments may employ intelligent provisioning, data summarization, and analysis to utilize an energy market connection, communication, and transaction support platform.

The embodiment of the invention discloses a system standard updating method, system and equipment and a storage medium, and relates to the technical field of photovoltaic power generation, and the method comprises the steps: traversing a standard in to-be-updated standards, constructing a standard age evaluation index, a standard reference evaluation index and a standard substitution evaluation index of the standard, and comprehensively judging whether the standard content needs to be updated or not; the subjectivity and one-sidedness of manual judgment are overcome, and the time required for judging whether the evaluation standard needs to be updated or not is shortened. Meanwhile, if updating is needed, other referenced standards are utilized to automatically update the standard content, the updating efficiency and accuracy are improved, and therefore changes of emerging technologies and market requirements are quickly responded.

The embodiment of the invention discloses a self-evolution patent emerging technology discovery method and device, and belongs to the technical field of artificial intelligence and patent information analysis crossing. The method comprises the following steps: receiving a newly input patent text, and carrying out semantic embedding processing on the patent text to generate a fusion vector; based on the similarity with each historical technical cluster center and a dynamic threshold value calculated according to the cluster activeness, the fusion vectors lower than the dynamic threshold value are classified into a candidate new cluster pool, and the candidate new cluster pool is used for storing fusion vectors which cannot be classified into any existing technical cluster; when the candidate new cluster pool meets a multi-dimensional triggering condition, calling a large language model to perform multi-task deep analysis on patents in the pool, and generating an emerging technology early warning report; pushing the emerging technology early warning report to a target user terminal, and receiving target user feedback; and according to the feedback of the target user, adjusting the clustering parameters and the analysis capability of the large language model, updating the clustering parameters required for calculating the dynamic threshold and optimizing the model parameters of the large language model.

This specification provides an AI-based energy edge platform with a wide range of functions, components, and capabilities aimed at managing and improving legacy infrastructure, coordinating with distributed systems, and supporting critical use cases across various enterprises. The AI-based energy edge platform may comprise a graph neural network including a set of nodes, each representing at least one distributed energy resource (DER), and a set of edges interconnecting these node sets. Each edge represents at least one energy-related characteristic between at least two nodes within the node set. The platform may incorporate emerging technologies to achieve efficiency, agility, engagement, and profitability for the ecosystem and individual energy edge nodes. Examples include forecasting, planning, and managing energy demand and utilization in larger-scale distributed environments. Examples leverage intelligent provisioning, data aggregation, and analytics, and utilize a platform to enable connectivity, communication, and trading in energy markets.

The invention provides an industry demand-oriented dynamically adaptive education decision-making auxiliary system, and relates to the technical field of education informationization, the system comprises a data acquisition layer, a data processing layer and an event detection layer, the data acquisition layer is used for periodically and synchronously acquiring original data from a local policy database and a recruitment market database; the data processing layer adopts a locally deployed large model to perform entity recognition, relationship extraction and structured processing on the collected original data based on a preset educational knowledge graph to obtain structured semantic information; through a multi-source data real-time sensing mechanism and an RAG-fine tuning collaborative reasoning framework, dynamic capture of industrial demands is realized, when the ability popularity index suddenly increases, the system can complete event judgment, trend analysis and adjustment suggestion generation in a short time, the response period is short, the problem of education supply lag in the emerging technical field is effectively solved, and the system has a wide application prospect. And employment competitiveness of students is guaranteed.

The invention provides a talent skill optimization path planning method and system based on dynamic man-post matching, and relates to the technical field of intelligent talent matching and optimizing.The method comprises the steps that data physical mapping and inertial index introduction are conducted on obtained multi-dimensional data, and an employee skill state space model is constructed; based on the employee skill state space model, constructing a skill topological graph with skills as nodes and association degrees between the skills as connection edge weights, and obtaining a multi-scale energy network through integration; performing complementation optimization on the skill correlation degree and the employee potential value in the multi-scale energy network through the improved information entropy diffusion model to obtain an optimized multi-scale energy network; and performing multi-target particle game optimization by using the optimized multi-scale energy network and post demand data to obtain a global optimal talent skill optimization path. According to the method, the accuracy of a traditional person and post matching technology for the emerging technology field and the reasonability of an emerging technology talent skill optimization path planning method are greatly improved.

The application discloses an emerging technology evolution analysis method and device and a storage medium. First, the patent data of the target technology is obtained, and is divided according to time periods to observe the development state of the technology at different time nodes. Then, the patent data is preprocessed and text vector conversion is performed, main technical topics in each time period are extracted through dimension reduction processing and clustering analysis. Secondly, the abstract texts of each topic are spliced to obtain target abstract texts, and keywords are extracted from the target abstract texts by calculating the cosine similarity between the word vectors and the document vectors, so that the topic name of each topic is determined. Finally, the association relationship between the topics is determined according to the cosine similarity between the topics, and the evolution path of the target technology is determined. Thus, the evolution path of the target technology can be efficiently and accurately captured, the accuracy of the technology evolution analysis is improved, and the technical problem of low accuracy of the technology evolution analysis in the prior art is solved.

The invention provides a technical blank space calibration and layout subject identification method based on suspected missed labeling patents, belongs to the technical field of patents, and solves the problems of technical blank misjudgment and the like caused by term diversity and indexing limitation in an existing patent analysis method. The method comprises the following steps: constructing a patent retrieval expression according to target technology description, performing retrieval, and constructing a large-field patent set; extracting high-purity seed samples from the large-field patent set, and constructing a high-purity seed set; modeling is carried out on the high-purity seed set from different technical perspectives, and a multi-dimensional behavior portrait is constructed; evaluating the to-be-evaluated patent based on the multi-dimensional behavior portrait, and generating a suspected label missing patent set; on the basis of the large-field patent set and the suspected missed labeling patent set, the technical blank area is calibrated, and a true blank and a false blank are distinguished; and identifying an underestimated layout main body and an emerging technical direction based on the large-field patent set and the suspected missed labeling patent set.

The invention discloses a biogas cold-drying dehydrator with adjustable biogas outlet temperature, which belongs to the technical field of biogas dehydration, and comprises a plurality of cold-drying devices which are sequentially connected in series, the lower parts of the plurality of cold-drying devices are fixed on the ground through a support frame, the cold-drying devices are communicated through communicating pipes, the outer side of the cold-drying device at the gas inlet end is communicated with a biogas inlet pipe, and the outer side of the biogas inlet pipe is communicated with a biogas outlet pipe. According to the invention, a modular assembly design is adopted, flexible adjustment can be carried out according to the biogas flow demand, the installation efficiency and adaptability of the equipment are improved, the device is suitable for biogas treatment systems of different scales, and the device is convenient to use, high in practicability and easy to popularize and apply. The system has remarkable advantages in the aspects of energy conservation, efficiency, stability and intelligence, provides an efficient, economical and easy-to-maintain biogas treatment solution, and has a wide application prospect in the novel technical fields of full-amount recycling of feces and the like.

Abstract An AI-based energy edge platform is provided herein with a wide range of features, components and capabilities for management and improvement of legacy infrastructure and coordination with distributed systems to support important use cases for a range of enterprises. The platform may incorporate emerging technologies to enable ecosystem and individual energy edge node efficiencies, agility, engagement, and profitability. Embodiments may forecast, plan for, and manage the demand and utilization of energy in greater distributed environments. Embodiments may use AI, IoT, and technologies that filter, process, and move data more effectively across communication networks. Embodiments of the platform may leverage energy market connection, communication, and transaction enablement platforms. Embodiments may employ intelligent provisioning, data aggregation, and analytics. Abstract 104 110 108 oM Advanced Energy Resources and Systems Data Resources for Energy Edge Orchestration Configured Stakeholder Energy Edge Solutions 112 138 140 114 118 102 130 Energy Energy Intelligent Data Layers Generation Consumption Energy Transaction 144 132 Orchestration Orchestration Enablement Systems 1 / 21 Distributed Ledger and Smart Contract Systems Energy Stakeholder Energy 148 Energy Storage 134 Orchestration Marketplace Digital Twins Adaptive Energy Digital Orchestration Twin Systems 142 136 Energy Delivery 146 Data Integrated 150 Orchestration 147 Microservices Energy Simulation Systems Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence and Automation Systems Modules and Services Al-Based Energy Edge Platform PCT / US2022 / 050932 102 FIG. 1 20 26 21 07 58 30 J ul 2 02 6 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge OrchestrationConfigured Stakeholder Energy Edge Solutions I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge OrchestrationConfigured Stakeholder Energy Edge Solutions I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge OrchestrationConfigured Stakeholder Energy Edge Solutions I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge OrchestrationConfigured Stakeholder Energy Edge Solutions I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge OrchestrationConfigured Stakeholder Energy Edge Solutions I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge Orchestration I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2

NeuralClaim Al is an Al-powered system that autonomously identifies emerging technological gaps, generates novel inventions, evaluates patentability, and automates patent drafting. The system integrates Al-driven problem identification, generative design, prior art analysis, adaptive claim optimization, and blockchain-based licensing to streamline the intellectual property lifecycle. By enabling tiered licensing and Al-powered compliance enforcement, NeuralClaim Al democratizes innovation while ensuring enforceable IP protection. Field of the Invention: This invention relates to artificial intelligence, intellectual property management, and innovation commercialization. It specifically addresses an Al -driven system that continuously monitors global research, autonomously generates patentable inventions, assesses their novelty and feasibility, and facilitates ethical commercialization through structured licensing frameworks. Background of the Invention: Traditional patent systems are slow, costly, and inaccessible to independent inventors and startups. Patent hoarding, inefficient prior art searches, and limited technology access further hinder innovation. While Al has begun assisting patent drafting, it has yet to optimize the entire invention lifecycle. NeuralClaim Al introduces a comprehensive solution, automating real-time problem identification, Al-generated solution synthesis, prior art analysis, adaptive patent optimization, and ethical commercialization. By accelerating innovation, reducing barriers to IP protection, and ensuring equitable technology distribution, this system redefines how patents are created, evaluated, and commercialized.

The present application relates to a kind of quick switch adhesion regulation method and its application, belong to adhesion regulation technical field.The method utilizes the strong viscoelasticity and adhesion performance of adhesion layer material in its phase transition temperature vicinity phase transition region to the strong and unique dependence characteristics of pull-off rate, at constant temperature, by adjusting pull-off rate can realize the quick regulation of switch adhesion: when with the first critical pull-off rate V c1 Unload and pull-off, can realize significant adhesion enhancement;And when with the second critical pull-off rate V c2 Unload and pull-off, can realize 0 adhesion.The method of the present application has high adhesion strength, large switch ratio and short switch time, and also significantly shortens the time period of adhesion opening and closing, so it can significantly improve the adhesion switch efficiency, can be widely applied in micro transfer printing, robot wall climbing and soft gripper and other emerging technical fields requiring fast adhesion switch response.