20 results about "Impact index" patented technology

The present invention discloses a lightweight AI predictive control method for embedded devices, which specifically relates to the field of embedded control technology and includes the following steps: collecting and preprocessing real-time multidimensional data to form a unified time series structure, identifying whether entering a high heat accumulation or control response delay risk zone based on a static feature threshold and a dynamic trend function, and if entering, calculating a hysteresis impact index and a heat load accumulation index, substituting them into a pre-trained artificial intelligence prediction model to output a scheduling risk coefficient, and performing a dynamic switching operation of the control path based on the scheduling risk coefficient and the joint trend of the two indices; the present invention realizes pre-identification of high heat accumulation and control response delay risks by unifying the multidimensional data time series structure; introduces a dual quantization mechanism of the hysteresis impact index and the heat load accumulation index to enhance the expressiveness of the operating status; combines the artificial intelligence prediction output and the index trend to dynamically switch the control path to realize adaptive adjustment and structural optimization of the control strategy.

This invention discloses a traceable management method for AI model training data, specifically relating to the field of artificial intelligence training data traceability management technology. It addresses the problem in existing AI model training processes where the lack of continuous traceability between original samples, derived samples, training consumption records, and model versions makes it difficult to accurately pinpoint the actual impact range of problematic samples. By continuously associating original sample identifiers, derived sample identifiers, consumption vouchers, model version identifiers, and impact indexes, and tracing derived sample identifiers level by level along the original sample identifier based on the problematic sample trigger request, and locking the associated model version, the actual impact range of problematic samples can be accurately defined. This solves the problem of existing technologies struggling to trace specific problematic samples back to training batches and model versions, leading to inefficient handling.

The invention provides an international trade measure workflow intelligent deploying and early warning method, and relates to the technical field of resource scheduling distribution, and the method comprises the steps: calculating the vector difference of a policy text in a semantic vector space, and introducing an information source authority degree as a regulation factor, so as to precisely quantify the talent policy tightening degree; meanwhile, a principal component analysis method is adopted to perform weighted fusion on the basic emotion score of the public opinion, the logarithmic propagation influence factor and the subject risk weight so as to objectively calculate the exclusion degree of the social public opinion, thereby focusing on public opinions really having systematic threats; and finally, probability coupling is performed on the accurately quantified external environment risk and the core talent loss impact index in the enterprise by using a dynamic Bayesian network, so that penetrating and foresight early warning from a macroscopic environment to a microcosmic core asset risk is realized, a fuzzy trade risk is converted into a manageable and accurate internal safety problem of people, and the safety of the enterprise is improved. And the accuracy and efficiency of decision making are obviously improved.

The present invention is a computer system for creating fractal spider graphs which display data in a nested structure. The present invention includes a data store, a data analytics engines, and a computer platform for data visualization. The present invention analyzes both qualitative and quantitative data to determine a pattern of behavior based on the data. The data is then broken down into key performance indicator (KPI) units using NLP and machine learning. These KPI units are then used as the atomic unit for constructing the fractal spider graphs. The fractal spider graphs of the present invention are hierarchical, nested spider graphs which simultaneously display information and analysis from multiple levels of an organizational hierarchy. Further, the present invention is operable to generate inferences (i.e., decision outputs) based on the data, wherein the inferences are displayed as prioritized action lists, weighted confidence scores, risk-impact indices, and / or narrative recommendations.

The present invention can assist realization of a front loading design in consideration of an environmental impact index.　The present invention comprises: a processing category reception unit that receives processing categories for design targets on a design screen; a bill-of-process (BOP) candidate calculation unit that specifies, for each of the processing categories, a candidate for a processing method which belongs to the processing category, and calculates, as a BOP candidate, a combination of candidates for the processing method which have been specified for all of the design targets; an environmental impact index calculation unit that calculates the environmental impact index of the BOP candidate; and a display information generation unit that displays, on the design screen, the environmental impact index in association with the BOP candidate.

This invention provides a water hammer prediction system and device. The invention relates to the field of pipeline fluid transport safety technology. The water hammer prediction system is configured to: acquire static topology and physical attribute information and multi-dimensional real-time operating condition data of the fluid transport system, and pre-calibrate a dynamic simulation model based on the information and data; when a water hammer triggering event is detected, invoke the pre-calibrated dynamic simulation model to perform an initial prediction to generate an initial prediction result, and issue a pre-control command to the first-level protection device based on the initial prediction result; acquire the measured impact index at the first-level protection device and compare it with the initial prediction result to determine the prediction error; and, based on the prediction error, correct the dynamic simulation model in real time, and drive the corrected dynamic simulation model to perform cascade control of the next-level protection device.

This invention discloses an intelligent monitoring method for water conservancy engineering data based on digital twins, specifically relating to the field of intelligent monitoring technology for water conservancy engineering. The method includes the following steps: acquiring control command data and real-time monitoring data of the actual water conservancy engineering, analyzing their temporal characteristics and trends, detecting whether the control command data is transmitted back and participates in system calculations, and identifying data echo effects; after detection, calculating short-term and long-term impact indices based on the convergence of prediction errors, evaluating the impact of echo effects on the current operating status and future scheduling accuracy, and determining the echo effect level as low, medium, or high based on the degree of impact, and employing corresponding optimization strategies; this invention achieves dynamic evaluation and hierarchical determination of data echo effects, improving the system's early warning and adaptability; employing fuzzy logic reasoning to optimize decision-making, enhancing the intelligence of regulation; and reconstructing models through differentiated strategies and reliable data sources to ensure the operational stability and scheduling accuracy of water conservancy engineering.

This invention proposes a safety control method and system for ultra-high bridge towers based on the time-varying effect of concrete, belonging to the technical field of bridge tower control systems. Addressing the problems in existing technologies such as insufficient prediction accuracy of long-term internal force redistribution caused by concrete shrinkage and creep, and insufficient consideration of the coupling effect between multiple risk factors and bridge tower concrete shrinkage and creep, resulting in low accuracy in predicting the state of bridge towers and a lack of guidance for maintenance control, this invention integrates multi-source heterogeneous data to calculate the impact indices of concrete shrinkage and creep, dynamic ice impact, static ice pressure, concrete freeze-thaw cycles, and ice wedging. A machine learning-based comprehensive risk assessment model is then used to fuse these indices, generating a comprehensive risk report containing risk levels and control recommendations. This invention significantly improves the accuracy of single risk factor assessment, enhances the comprehensive prediction accuracy of complex coupled risks, and strengthens the system's decision-making robustness and maintenance efficiency in complex scenarios with multiple concurrent risks.

The invention discloses a building material life cycle traceability management system and method based on RFID, and relates to the technical field of building material life cycle traceability management, and the method comprises the steps: S10, generating a traceability feature of a building material product; s20, predicting a life influence index of the building material product in a logistics transportation stage based on the searched abnormal transportation data; s30, obtaining a traceability index of each building material product to be used; and S40, carrying out life traceability management on the building material product to be used. According to the method, the traceability index of the to-be-used building material product is calculated, the building material product with the quality problem can be quickly and accurately screened out from numerous products, the quality prevarication problem caused by the storage mode or storage time of the building material product is avoided, and the quality of the building material product can be accurately determined according to the occurrence frequency of various target traceability indexes. And the root cause of the quality problem of each to-be-used building material product is quickly and accurately locked.

To provide a technology for reducing the effort involved in trading improvement credits.SOLUTION: An information processing device according to one aspect of the present disclosure acquires the remaining improvement credits held by a target company to enhance the value of an environmental impact indicator. The information processing device then distributes at least a portion of the acquired remaining improvement credit to the accounts of one or more companies that supply one or more containing products. The containing products are identified by traversing a product tree that hierarchically shows the supply relations within the supply chain to which the target company belongs for product groups that include the target company's target product. Each containing product is included as one or more upstream products within the target company's target product.SELECTED DRAWING: Figure 1

The invention discloses an urban system toughness dynamic measurement method and device, equipment, a medium and a product, and relates to the field of urban disaster management and risk assessment, and the method comprises the steps: obtaining toughness index data and disaster environment data of a target city; determining an initial rainstorm impact index according to the disaster environment data; constructing a toughness index system according to the toughness index data and the initial rainstorm impact index; calculating a weighted comprehensive index of each toughness dimension according to each toughness index value under each toughness dimension to obtain a plurality of toughness attribute parameter values; according to the toughness attribute parameter values, a parameterized gamma family recovery function model is adopted to simulate system performance changes after the target city is subjected to disaster impact, and a dynamic performance recovery curve is generated; and calculating a dynamic toughness quantized value and recovery time of the target city based on the dynamic performance recovery curve. According to the method, dynamic simulation of the whole process of'impact-response-recovery 'can be carried out on the city, and the accuracy of city toughness measurement is improved.

The invention discloses an intelligent aviation flow prediction method based on an MLP-LightGBM hybrid model, and relates to the technical field of air transportation management, artificial intelligence and big data analysis. The problems of data isomerism and space-time alignment are solved by innovatively adopting periodic time-triangular transform coding and an aviation cloud influence index model. Then, constructing a'micro-macro 'two-stage prediction architecture: a micro layer processes unstructured meteorological data by using MLP, and predicts single flight delay; and the macroscopic layer aggregates the MLP result and combines the structured features, and the LightGBM performs hour-level flow accurate prediction and correction. According to the method, the three bottlenecks of insufficient critical mutation capture, cross-scale modeling fault and space-time decoupling in the high influence weather in the existing method are effectively solved, the prediction error is reduced by 7.2% compared with the optimal single model, the threshold accuracy is as high as 93.75%, and an advanced and reliable technical support is provided for improvement of airspace operation efficiency and prevention and control of large-area flight delay.

The application discloses an environmental impact prediction system and method thereof, relates to the technical field of environmental impact prediction, and comprises the following steps: in response to a design change event, real-time capture of component information; characteristic parameter mapping processing is performed to obtain calibrated input parameters; the whole life cycle comprehensive environmental impact index is calculated and compared with the initial construction cost of the project; in response to the predicted whole life cycle comprehensive environmental impact index being greater than the compliance baseline, constraint optimization decision processing is performed to generate an optimized design scheme; the predicted whole life cycle comprehensive environmental impact index and the predicted initial construction cost of the project are visually presented; and the optimized design scheme is visually presented on the user interface of a computer-aided design environment. The application pre-positions environmental and cost considerations and integrates them into instantaneous design decisions, solves the problems of disconnection between design and evaluation and feedback lag through real-time prediction and intelligent optimization.

A data-driven academic expansion management system for the institutional analysis and control of expansion activities within an educational institution. The system includes: a variety of data collection units configured to capture metadata on cultural and academic expansion activities, including identifiers, category, activity mode, associated department, responsible persons, and temporal attributes; a central processing unit that is operationally connected to a storage unit and a non-volatile database, wherein the storage unit stores program instructions that can be executed by the central processing unit to structure, classify and link the captured metadata according to predefined institutional frameworks; a coordination controller configured to generate digital records in an institutional management repository for each identified activity, with the coordination controller linked to the user authentication parameters of deans, school principals, department heads, and outreach managers; a planning and distribution control unit in communication with the central processing unit, configured to digitally register posters, distribution emails, participant registration forms, multimedia evidence and activity feedback in a unified repository through cloud storage synchronization; a performance evaluation unit connected to the database, configured to calculate Key Performance Indicators (KPIs) that represent management indicators and acceptance criteria for each outreach activity based on activity frequency, inter-institutional collaboration, and participant satisfaction metrics; an impact analysis controller linked to a repository of graduate profile matrices, wherein the controller is configured to link extension activities with corresponding graduate outcome parameters and calculate an impact index (IG) that indicates the competency alignment of graduates; a satisfaction assessment processor configured to aggregate survey data, calculate the satisfaction levels of internal and external beneficiaries, and generate satisfaction reports for academic and cultural activities, which are stored in shared digital folders for at least a predetermined retention period; and a system interface controller configured to display institutional dashboards in real time, representing KPIs, impact levels and satisfaction metrics aligned with the institutional strategy plan, thus enabling automated evaluation, reporting and archiving of expansion activities.

The application discloses a kind of urban system resilience dynamic measurement method, device, equipment, medium and product, it is related to urban disaster management and risk assessment field, the method comprises: obtaining the resilience index data and disaster environment data of target city;According to disaster environment data, determine initial storm impact index;According to resilience index data and initial storm impact index, construct resilience index system;According to each resilience index value under each resilience dimension, the weighted comprehensive index of each resilience dimension is calculated respectively, obtain multiple resilience attribute parameter values;According to each resilience attribute parameter value, using parameterized gamma family recovery function model simulates the system performance change of target city after suffering disaster impact, generates dynamic performance recovery curve;Based on dynamic performance recovery curve, the dynamic resilience quantitative value and recovery time of target city are calculated.The application can carry out dynamic simulation to the whole process of "impact-response-recovery" of city, improve the accuracy of city resilience measurement.

The application provides a document influence index analysis method, comprising the following steps: S1, obtaining the cited amount, publication year Y and current year Y of N documents n1 ; S2, determining the burst start year Y n2 , burst end year Y n3 and burst duration according to the cited amount; S3, obtaining the burst intensity S n according to the document burst state and the proportion of burst documents; S4, determining the frontier index of the N documents; and S5, determining the importance index of the N documents. Thus, in the application, when judging the frontier and importance of the documents, the various factors of the documents are comprehensively considered, i.e. the current year, the burst intensity, the document sequence, the publication year, the burst start year, the burst end year, the burst duration and the time interval between the burst end year and the current year, so that the judgment of the document frontier and importance is more accurate and more comprehensive.

The application provides a knowledge graph construction method, system, device and medium, relates to the technical field of knowledge graph construction, and the method comprises the following steps: in response to a trigger event sent by a user end, acquiring basic information of an enterprise corresponding to the user end, combining the trigger event and the basic information, determining a plurality of characteristic data affecting the result of the trigger event, and constructing a sub-knowledge graph of each characteristic data; acquiring an influence index of each sub-knowledge graph on the result of the trigger event and a correlation coefficient between the sub-knowledge graphs; combining the influence index and the correlation coefficient to construct an initial knowledge graph; acquiring an abnormal conduction edge in the initial knowledge graph; processing the correlation coefficient and the influence index carried by the abnormal conduction edge to generate a target knowledge graph; and generating a strategic decision suggestion of the trigger event according to the target knowledge graph. The application has the technical effect that the accuracy of the strategic decision suggestion generated by the knowledge graph is improved.

The invention relates to a steel product environment footprint evaluation and multi-target emission reduction simulation method, which comprises the following steps: S1, providing a steel production process material automatic classification and classification method, and forming a standard material library, a process library and a product library; s2, establishing a process model and a product model, and forming a process model library and a product model library; s3, collecting live-action process data and cost data of the steel product, establishing association between the live-action process data and background data, selecting an environmental influence index, and checking the environmental footprint and cost of the steel product; and S4, setting an emission reduction scene and corresponding conditions and targets, and carrying out multi-target simulation analysis by adopting a multi-target optimization algorithm. According to the method and the system provided by the invention, the environmental footprint and the production cost of the steel product can be quantified in a high-efficiency and high-quality manner, and carbon reduction scene simulation of the steel product and multi-target optimization simulation based on low environmental emission and low cost are realized based on emission reduction process technical planning of the steel product.

An information processing apparatus according to one aspect of the present disclosure acquires a remaining amount of improvement credit for improving a value of an impact index on the environment, which is owned by a subject enterprise. Furthermore, the information processing device allocates at least a portion of the acquired credit-improving margin to accounts of one or more enterprises in a supply chain to which the target enterprise belongs, the accounts being specified by tracing a product tree that hierarchically represents the supply relationship of the product group, and the information processing device allocates at least a portion of the acquired credit-improving margin to the accounts of the one or more enterprises in the supply chain to which the target enterprise belongs. The product group includes target products of the target enterprise, and each of the one or more enterprises supplies one or more included products of the target products included in the target enterprise as products at one or more levels on the upstream side.

The application discloses a river sediment transport capacity determination method and system based on sediment parameter analysis, relates to the technical field of hydraulic engineering, and obtains a vibration index, an impact index and a visual index under a preset collection frequency, carries out weighted summation on the indexes to obtain a comprehensive index, judges a water flow phase state grade in combination with the impact index, executes corresponding calculation strategies on different water flow phase state grades, obtains a first sediment transport coefficient, a second sediment transport coefficient and a third sediment transport coefficient of the river, outputs a dynamic sediment transport capacity spectrum containing the coefficients, obtains a risk coefficient according to the dynamic sediment transport capacity spectrum, and updates the preset collection frequency and a preset phase state threshold value; the application can capture water flow phase state changes in real time, improve the accuracy and timeliness of sediment transport capacity determination, and enhance the reliability of early warning.