53 results about "Development assessment" patented technology

The invention belongs to the technical field of child growth and development evaluation, and particularly relates to a child development dynamic evaluation method and system based on multi-source data fusion. According to the method, the growth and development state of the child can be preliminarily judged through the growth and development sample curve generated through fusion, the second index data of the child are obtained through the non-intrusive acquisition equipment, and the acquisition frequency is adjusted based on the initial state type, so that the comprehensiveness and accuracy of the data are ensured, unnecessary frequent acquisition is avoided, and the accuracy of the data is improved. Processing the second index data through a pre-trained convolutional neural network model to generate individual growth fingerprints, screening out historical fingerprint data with high similarity with the individual growth fingerprints from a cloud database, constructing a personalized growth corridor, providing a personalized referable trajectory range for growth and development of children, and improving the growth and development efficiency of the children. And on the basis, whether the growth and development of the children are abnormal is judged, so that the growth and development conditions of the children are accurately evaluated.

The invention relates to the related technical field of green energy, in particular to a green energy system construction and development evaluation method and device, equipment and a storage medium. The method comprises the following steps: acquiring basic data of a green energy system; determining an evaluation index system based on the basic data; weighting each index in the evaluation index system based on an AEW objective weighting method to obtain a first weight; weighting each index in the evaluation index system based on a subjective weighting method of BWM to obtain a second weight; on the basis of the first weight and the second weight, solving the comprehensive weight of the target index based on a combined weight calculation strategy; and based on the target index comprehensive weight, adopting an alternative scheme sorting method of a compromise scheme to evaluate the green energy system so that related personnel can adjust a development strategy of the green energy system based on the evaluation.

The invention discloses an integrated growth and development evaluation management system for children, and particularly relates to the technical field of growth and development evaluation. Child growth and development stages are divided through child physiological parameter collection and dynamic time sequence analysis based on machine learning; processing the child limb proportion time sequence data by using a dynamic time warping algorithm, and evaluating the synchronism of bone growth and soft tissue development; identifying whether the children have development deviation risks or not according to the growth and development stages and synchronism; for children with development deviation risks, combining gene information, and adopting a genetic algorithm and a dynamic programming model to evaluate the growth potential of children individuals; according to the method, the synchronism of child bone growth and soft tissue development and child individual growth potential and development adaptability are subjected to correlation analysis, the probability of potential development abnormality is evaluated, whether personalized intervention measures are started or not is judged, comprehensive monitoring and risk early warning of child growth and development states are achieved, and scientificity and practicability are achieved.

The invention discloses a student development quality evaluation method and system based on artificial intelligence, and the method comprises the steps: multi-dimensional data collection, complex feature fusion, multi-level feature calculation, high-order feature generation, association rule mining and a real-time dynamic adjustment mechanism. The development conditions of students in five aspects of morality development, academic development, physical and mental development, aesthetic quality and labor and social practice are comprehensively and objectively evaluated; the method comprises the specific steps that subjective evaluation is replaced with multiple indirect data acquisition, and the influence of human subjective factors is reduced; through multi-level feature calculation and high-order feature generation, the depth and accuracy of data analysis are improved; analyzing the relationship among the high-order features by using an association rule mining technology, and carrying out ultimate feature fusion; calculating a comprehensive development evaluation coefficient through a comprehensive scoring formula, generating comprehensive development evaluation data, and performing personalized feedback and real-time dynamic adjustment; according to the invention, a scientific decision basis is provided for education management and personalized teaching.

The invention discloses a chronic disease patient nursing management system based on big data, which relates to the technical field of medical nursing and comprises a disease course development analysis unit, a patient health analysis unit, an online diagnosis and treatment unit, a nursing management unit, a nursing recommendation unit and a nursing correction unit. According to the invention, the disease course development model of the chronic disease is constructed according to the disease course development data, the disease development evaluation trend is graded and judged according to the physiological data of the patient, the judgment result is corrected through the online diagnosis and treatment unit, and the matched nursing list is obtained according to the judgment result. The nursing list is sent to a remote medical terminal of a nurse and an intelligent mobile terminal of a family member of the chronic disease patient, physiological data of the patient is obtained after each nursing judgment period is completed, the correction trend of the nursing influence coefficient is judged, and the effect of the nursing scheme is evaluated. The nursing list is timely corrected according to the chronic disease development process of the patient, the disease development condition of the patient is better matched, and chronic disease deterioration is inhibited.

The invention provides an enterprise-oriented evaluation method and system for judging whether business and financial fusion adjustment is carried out or not, and a storage medium. The evaluation method comprises the following steps: acquiring login information of an operator; obtaining to-be-evaluated data input by an operator, and sending the labeled to-be-evaluated data to the server; calculating an enterprise data integrity evaluation value for evaluating the integrity of the enterprise data; calculating an enterprise maturity evaluation value for evaluating the management level and the operation efficiency of the enterprise; calculating an enterprise standard degree evaluation value for evaluating the standardization degree of the enterprise process and the operation industry; calculating an enterprise development degree evaluation value used for evaluating the enterprise innovation capability and the business growth capability; calculating an enterprise compliance evaluation value; calculating an enterprise input-output ratio evaluation value; calculating an enterprise comprehensive index score and an enterprise consultation index; and determining an evaluation result based on the enterprise comprehensive index score and the enterprise consultation index. By adopting the evaluation method provided by the invention, the evaluation result can be obtained more quickly and accurately.

The present invention considers the driving factors of the rural comprehensive energy system carbon emission assessment method and equipment, considers the multiple factors that affect the carbon emissions of the comprehensive energy system, establishes a multi-dimensional low-carbon comprehensive assessment index system, and constructs a scientific low-carbon development assessment method. First, the construction process of the comprehensive assessment index system is clarified; then the external driving factors of carbon emissions at multiple levels such as the environment, economy, society and technology are analyzed; the evolution mechanism and development factors of energy, power grid and energy use are analyzed, and the internal driving factors of the new rural comprehensive energy system at the low-carbon technology level are explored; the internal and external driving factors are integrated to construct a multi-dimensional low-carbon comprehensive assessment index system. Finally, based on the positive and negative bull's eye improved gray target model, a low-carbon development potential assessment method is proposed to achieve quantitative analysis of the assessment indicators, thereby exploring the development potential of each factor.

The invention provides an urban coordinated development evaluation method based on water resources and coupling factors thereof, and belongs to the technical field of development evaluation based on deep learning. The method comprises the following steps: firstly, constructing a structured data set covering a ternary system, and introducing a physical quantization tag to ensure the objectivity of an evaluation result; secondly, designing a causal modeling network with a two-level structure, fusing system-level and index-level contribution analysis mechanisms, and realizing structured mining of a coupling causal relationship; then, through a model structure inversion mechanism, proposing a three-item multi-dimensional index system for evaluating the potential, coordination and stability of urban development; and finally, in combination with structure prior information and an evaluation result, constructing a game theory-driven multi-round regulation and control path deduction framework, and realizing automatic generation of a collaborative variable regulation and control scheme and prediction and evaluation of a development effect, thereby providing high-quality collaborative development path suggestions with reasonability and mechanism interpretability for cities.

The invention relates to the technical field of talent development evaluation, and discloses a multi-dimensional data fusion-based intelligent evaluation method for talent development of a power grid company, which is used for solving the problem that an evaluation period is no longer representative during talent development evaluation, and comprises the following steps of: collecting original development data of each person in a human resource management system; the method comprises the following steps: performing standardization processing on original data, constructing a multi-dimensional feature data set, constructing a talent development analysis model, setting an initial evaluation period, obtaining fluctuation data based on the multi-dimensional feature data set, performing evaluation according to the fluctuation data to obtain a period adaptability deviation index, and judging whether the current evaluation period needs to be adjusted or not. If it is judged that the current period needs to be adjusted, the initial evaluation period is adjusted to obtain an actual evaluation period, the accuracy of talent development evaluation is effectively improved, and the credibility of an evaluation result is improved.

This invention discloses a method and system for invoking computational rules based on key indicators of preschool education, relating to the field of preschool education technology. It involves constructing a cloud-based big data center to collect multi-source data from preschool education, processing this data to obtain correlated data clusters, and building a preschool education AI model including a judgment model, a child development assessment and diagnosis model, a personalized gamified learning content recommendation model, and a home-school collaborative interaction support model. The judgment model analyzes the input to the preschool education AI model to determine which type of model to use for key indicator output. Simultaneously, a dynamic data pipeline is constructed to connect the cloud-based big data center and the preschool education AI, and a detection window is set to protect data security. This invention achieves more intelligent and precise preschool education intervention through the cloud-based big data center, the preschool education AI model, and the dynamic data pipeline.

The invention provides an embryonic development evaluation method and device, electronic equipment and a storage medium, and relates to the technical field of assisted reproduction. The method comprises the following steps: acquiring an embryo image of a to-be-evaluated embryo, and extracting an inner cell mass image from the embryo image; traversing the internal cell cluster image, and determining a pixel distribution index corresponding to the internal cell cluster image; determining at least one feature parameter of the internal cell mass image according to a pixel distribution index corresponding to the internal cell mass image; and determining an evaluation result of the to-be-evaluated embryo according to each characteristic parameter of the inner cell mass image. According to the method, pixel traversal is carried out on an extracted internal cell cluster image to obtain position indexes of a plurality of center pixel points so as to obtain a pixel distribution index, and feature mining is carried out based on pixel relative position difference information indicated by the pixel distribution index so as to obtain multiple feature parameters capable of representing texture information of the internal cell cluster image. Therefore, the method is used for evaluating embryonic development, and the accuracy and credibility of an evaluation result are improved.

The present invention discloses a children's integrated growth and development assessment and management system, specifically relating to the technical field of growth and development assessment; by collecting children's physiological parameters and performing dynamic time series analysis based on machine learning, the growth and development stages of children are divided; the dynamic time warping algorithm is used to process the time series data of children's limb proportions to evaluate the synchrony of bone growth and soft tissue development; by integrating the growth and development stages and synchrony, it is identified whether a child has a risk of developmental deviation; for children with a risk of developmental deviation, combined with genetic information, a genetic algorithm and a dynamic programming model are used to evaluate the individual growth potential of children; the synchrony of children's bone growth and soft tissue development and the individual growth potential and developmental adaptability of children are analyzed in association to evaluate the probability of potential developmental abnormalities and determine whether to initiate personalized intervention measures, realizing comprehensive monitoring and risk warning of children's growth and development status, and having scientificity and practicality.

The invention provides an artificial intelligence health management auxiliary evaluation and analysis system and method, and the system comprises a multi-modal model generation module which is used for generating a multi-modal medical intelligent evaluation model; the artificial intelligence auxiliary evaluation and analysis module is linked with the multi-modal model generation module, calls a medical intelligent evaluation model, and performs personalized analysis and full-cycle risk evaluation on the medical state of the patient based on artificial intelligence; the full-cycle risk assessment comprises health assessment, lesion assessment, development assessment, suspicious change detection and postoperative rehabilitation assessment. Therefore, based on artificial intelligence auxiliary evaluation and analysis, evaluation and analysis are performed on the whole-cycle diseases of the user, multiple aspects such as health evaluation, lesion evaluation, development evaluation, suspicious change detection and postoperative rehabilitation evaluation are covered, so that the pre-detection of the whole-cycle diseases is realized based on an artificial intelligence technology, the early detection rate is improved, and the detection efficiency is improved. And postoperative rehabilitation evaluation is assisted to be completed.

The invention discloses an urban and rural fusion development evaluation method based on a combined weighting and coupling coordination model, and relates to the technical field of data processing. The method comprises the following steps: S1, constructing an urban and rural fusion index evaluation system; s2, three-level combination weighting is carried out; s3, constructing a space-time two-dimensional improved coupling coordination model; step S4, performing evaluation based on ESDA and an obstacle degree model; and S5, multi-dimensional verification is carried out. According to the method, a high-quality data basis is provided for dynamic empowerment through accurate indexes screened in a three-dimensional mode, a scientific basis is provided for space-time coupling coordination calculation through reasonable weights of the dynamic empowerment, reliability is guaranteed through multi-scene verification of accurate results of space-time optimization, and finally, an intelligent evaluation report and a policy suggestion library are output. The method directly serves urban and rural fusion development decision, improves the overall evaluation efficiency, and improves the conversion efficiency from the evaluation result to the policy decision.

The application relates to an artificial intelligence-based child growth and development evaluation method, device, equipment and medium. The method comprises the following steps: acquiring standardized growth and development data of a child and performing asynchronous time sequence alignment processing to generate a time sequence alignment characteristic vector sequence; inputting the time sequence alignment characteristic vector sequence into a cross-scale attention fusion model to perform feature fusion and generate a comprehensive feature representation; combining a pre-constructed hierarchical time sequence mode detection network to calculate a comprehensive anomaly index of the child; constructing an event-driven dynamic state space model based on the comprehensive anomaly index and generating a personalized growth corridor; comparing real-time monitoring data and a personalized growth corridor boundary, and generating a personalized growth and development evaluation report based on a comparison result. The method can effectively solve the technical defects of poor fusion effect of high-frequency data and low-frequency data in a traditional method, difficulty in capturing early weak development abnormalities and lack of personalized evaluation standards.

The invention discloses a fetal brain development assessment method and a computer program product, and belongs to the field of medical image analysis. The method comprises the following steps: firstly, acquiring a brain image of a fetus, and then segmenting the brain image by using a segmentation model trained based on a multi-gestational-age sample and a loss function adjusted along with gestational ages to obtain a brain segmentation result; calculating a brain development index of the fetus based on the segmentation result; estimating the gestational age of the fetus by using a gestational age estimation model, wherein the gestational age estimation model comprises a segmentation model serving as a generator and a discriminator obtained through adversarial training; acquiring a normal brain development index range of the corresponding gestational age from a reference database based on the estimated gestational age; and finally, comparing the calculated brain development index with a normal range to obtain a fetal brain development evaluation result.

The application belongs to the technical field of medical devices, and discloses a pediatric penis development evaluation method and system based on multi-modal sensor measurement, which comprises the following steps: calling hardware parameter group corresponding to the scene to configure current scene parameters, collecting and verifying environmental conditions, and then starting the measurement process; collecting double-frequency tissue impedance data of the pubic symphysis region, locking the measurement reference zero point, identifying the interface channel, and obtaining the fat pad thickness; starting constant force standardization traction, maintaining constant force creep after reaching the force threshold of the age group, latching the current displacement to generate the stretching length, collecting double-path homologous strain data at the same time, and obtaining the circumference value; checking the stretching length and the circumference value according to the preset physiological boundary, determining the measurement quality grade, obtaining the final development parameter, evaluating and grading the development based on the fat pad thickness, and generating the development evaluation conclusion; receiving the doctor's calibration instruction, updating the physiological boundary based on the development evaluation conclusion and the final development parameter.

The invention belongs to the technical field of energy consumption monitoring, and discloses a low-carbon digital economic development evaluation system and method based on big data, and the system comprises a data collection module which collects the state data, collection time and regional energy consumption of different regions of a shopping mall; the data processing module is used for preprocessing the state data to obtain effective state data, and performing regional evaluation on the effective state data to obtain regional state description; the feature optimization module is used for performing state association evaluation on the effective state data based on regional state description to obtain an optimal data set; the model construction module is used for constructing an energy consumption prediction model based on the optimized data set and the regional energy consumption, and realizing accurate monitoring on the energy consumption of different regions of the shopping mall based on the energy consumption prediction model; and the accuracy of monitoring the energy consumption of different areas of the shopping mall is greatly improved.

A novel tool for assessing child development is described. The tool has an assessment device (10) including a microprocessor, a camera (34), a microphone (46), and a touch-enabled screen (56). A platform (12) holds the touch-enabled screen (56) in a vertical position. An activity pad (16) has a boundary (18) for an activity to be performed, said boundary (18) adapted to fit within the field of view of the camera (34). A series of assessment tasks are presented via the touch-enabled screen (56). The camera (34) captures a video recording of the assessment tasks performed on the activity pad. Images of the video recording are processed to identify performance characteristics of the child.

The present invention discloses an e-book reading analysis and processing method, which belongs to the technical field of e-book reading analysis and processing. The method comprises: step one: obtaining the e-book historical reading records of each user stored in a platform, and setting the reading categories of each user based on the e-book historical reading records of each user; step two: obtaining the e-book reading records of the users in real time, and dynamically updating the reading categories of each user based on the e-book reading records of each user; step three: performing real-time development evaluation based on the reading categories of each user, and obtaining a corresponding development status curve; step four: performing real-time early warning analysis on the platform development according to the development status curve, obtaining a corresponding early warning analysis result, and performing corresponding early warning processing according to the early warning analysis result; the present invention realizes multi-dimensional reading feature extraction and intelligent classification, and accurately grasps the reading needs and preferences of various users; based on user classification and development status analysis, reasonably allocates platform resources and improves resource utilization efficiency.

The invention discloses a method and system for evaluating the growth and development state of 0-6-year-old children based on intestinal flora and application, and belongs to the field of development evaluation of 0-6-year-old children, and the to-be-evaluated development state comprises one or more of neuropsychological development, skin, excrement, crying and screaming and night sleep; the method comprises the following steps: acquiring intestinal flora information of a to-be-predicted target population; the intestinal flora information comprises relative abundance information of flora significantly related to the corresponding development state; the intestinal flora information is input into a pre-constructed prediction evaluation model, evaluation results output by the prediction evaluation model are obtained, and the quantification results correspond to different development states. According to the method, near and long-term neuropsychological development, skin, excrement, crying and screaming conditions and night sleep indexes of the children are predicted through intestinal flora of the children, target spots capable of reference improvement are provided, bad development results possibly existing in the future can be found in time, and prevention and improvement are carried out in time.

The application discloses a kind of method, system and application based on intestinal flora to assess the growth and development state of children of 0-6 years old, belong to the development assessment field of children of 0-6 years old, and the development state to be assessed includes one or several of neuropsychological development, skin, stool, crying, night sleep;The method comprises the following steps: obtaining the intestinal flora information of the target population to be predicted;The intestinal flora information includes the relative abundance information of the flora significantly related to the corresponding development state;Intestinal flora information is input into the prediction evaluation model constructed in advance, and the evaluation result output by the prediction evaluation model is obtained, and the quantitative result corresponds to different development states.The present application predicts the neuropsychological development, skin, stool, crying condition, night sleep index of children in the short and long term through the intestinal flora of children, provides target points that can be referred to for improvement, can timely find the adverse development results that may exist in the future, and timely prevent and improve.

The invention discloses a real estate right survey information management system, which relates to the technical field of information management and comprises a survey information acquisition module, a survey information analysis module, a regional information analysis module, a development recommendation management module and a real estate right database. According to the method, the urban construction development evaluation index and the population inflow evaluation index of the city are analyzed, the development condition of the city is comprehensively analyzed, sufficient analysis of the development condition of the city is ensured, the accuracy of subsequent judgment of the development condition of the city is improved, management of real estate right information investigation is facilitated, and the economic benefit is increased. According to the number of public facilities in the region, the average income of residents and the number of available posts of enterprises, the life quality evaluation index of the region is analyzed, the to-be-optimized region is screened out, it is guaranteed that follow-up screening of the to-be-optimized region is accurate enough, the life experience of the residents is improved, and region development is helped to be more balanced.

The invention discloses an infant development assessment method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a target interaction video between a to-be-evaluated infant and a caregiver in response to triggering of an infant development evaluation event; for multiple frames of images in the target interaction video, determining a feature vector of each feature key point of the face image of the infant to be evaluated in the multiple frames of images in a face coordinate system; determining feature vector discrete coefficients of the multiple frames of images according to the feature vectors; and evaluating the social behavior development condition of the to-be-evaluated infant according to the feature vector discrete coefficient. Through the scheme, the social behavior development condition of the infant can be quickly, efficiently and accurately evaluated.

The invention discloses a physical electricity exploration experiment intelligent guiding system based on cognitive dynamic perception. The system is composed of four modules: 1) a self-adaptive exploration guiding module which constructs a self-adaptive dialogue engine based on a large language model, realizes personalized configuration and dynamic deduction of an experiment process, and evaluates the knowledge mastering degree of students in real time through a cognitive diagnosis algorithm; 2) an operation behavior analysis module, which is used for realizing experiment operation action analysis based on a visual large model and a normative recognition algorithm, and generating a multi-dimensional experiment evidence chain; 3) an intelligent experiment platform module which realizes digital design and automatic evaluation of circuit topology through a visual platform and a feature matching algorithm; and the evidence-based evaluation module is used for carrying out data fusion analysis based on the multi-modal large model, generating image-text historical records, carrying out experimental quantitative scoring, carrying out error operation attribution analysis and carrying out scientific literacy development evaluation. The system is helpful for improving the intelligent level of electricity experiment teaching, and provides objective data support for teaching decision making.

The invention discloses a simulation experiment system for comprehensive service resource planning of a Chinese and original city agglomeration, belongs to the technical field of comprehensive service resource planning, and aims to solve the technical problems of low intelligent degree and inconvenience in use when a functional area of the Chinese and original city agglomeration is evaluated in the prior art. According to the invention, information of a data source is collected through the data acquisition unit and is integrated and stored, and four appropriate indexes are screened out through the index selection module according to specific functional area characteristics. The four indexes are subjected to weight division through a weight setting module, and comprehensive score calculation is carried out through a comprehensive score calculation unit in combination with historical data of a functional region; by comparing the overall rising and falling trends of the comprehensive scores of different years and the comprehensive scores with the preset threshold values, the development risk of the functional area of the Chinese and original city agglomeration can be simulated through the comprehensive scores, the intelligent degree is high, and development evaluation of the functional area of the Chinese and original city agglomeration is facilitated.

The present application belongs to the technical field of child development assessment, and particularly relates to a child development disorder intelligent assessment system and method based on multi-modal data. The present application can distinguish between occasional abnormalities that occur for a short time and abnormal performance that persists by simultaneously considering the duration and deviation of abnormal performance, and can form comprehensive abnormal representations of children in different development ability dimensions by classifying in combination with different development ability dimensions, thereby enhancing the representation ability of the assessment results for persistent development abnormalities and abnormal performance in different ability dimensions. By comprehensively considering the ability dimension, duration and deviation of abnormal characteristics, the present application avoids assessment based on only a single index or single abnormal data, so that the assessment results can reflect the category, degree and persistent characteristics of child development abnormalities, and the accuracy of child development state assessment is improved.

The invention discloses a model for calling an operation rule based on a key index AI of preschool education, and relates to the technical field of preschool education. Multi-source data of preschool education is collected by constructing a cloud big data center, and the multi-source data is processed to obtain a data group with an association relationship; a preschool education AI model is constructed and comprises a judgment model, a child development evaluation and diagnosis model, a personalized gamification learning content recommendation model and a family cooperative rearing interaction support model, input of the preschool education AI model is analyzed through the judgment model, and what type of model is adopted for key index output is judged. And meanwhile, a dynamic data pipeline is constructed to connect the cloud big data center and the preschool education AI, and a detection window is arranged to protect data security. Through the cloud big data center, the preschool education AI model and the dynamic data pipeline, more intelligent and accurate preschool education intervention is realized.

The invention relates to the technical field of industry development evaluation, in particular to an emerging industry development evaluation method based on electric power big data and a related product, and the method comprises the steps: collecting multi-dimensional electric power data of emerging industry enterprises, and obtaining standardized electric power data; constructing a multi-dimensional evaluation index system, and determining a weight; performing quantitative scoring on each index; calculating to obtain a comprehensive evaluation score; obtaining a development prediction score; according to the method, multi-dimensional power data is used as a core data source, the Lagrange interpolation method and the normalization method are adopted for preprocessing, manual report errors and hysteresis are avoided, the evaluation period is shortened to monthly, objective weighting is achieved in combination with the entropy weight method, the influence of subjective factors of experts is eliminated, and the evaluation efficiency is improved. And the defects of unreliable data and unscientific weight of the traditional method are thoroughly overcome.