302 results about "Collection analysis" patented technology

The invention relates to the technical field of information management, in particular to an information scheduling scenarized service agent system. The system comprises an information scheduling acquisition and analysis module, a scene classification and service matching module, a service scheme instruction generation module and a service intelligent execution module, user behavior data, environment perception data and business system data corresponding to information scheduling can be obtained, and an original information set is generated; the original information set is preprocessed, an information scheduling scene classifier is constructed, the service matching degree is calculated in combination with the real-time service resource state, and a candidate service scheme set is generated; performing optimization sorting on the candidate service scheme set to generate an optimal service scheme, and disassembling the optimal service scheme into an executable service instruction sequence; receiving a service instruction sequence and generating a service evaluation report; and if the display does not reach the preset service quality threshold value, triggering a dynamic adjustment mechanism to realize self-iteration upgrading of the information scheduling scenarized service. According to the invention, intelligent scheduling and service of information in a complex scene can be realized.

The invention relates to the technical field of power monitoring, in particular to a moisture-proof environment-friendly ring main unit online monitoring system with continuous fault indication and a ring main unit, and the system comprises an electric parameter dynamic analysis module, an environment collaborative verification module, a closed-loop control execution module and a behavior path optimization module. According to the method, the current fluctuation and the power difference value are matched through dynamic time warping, the temperature rise rate and the condensation index are calculated through linear regression, multi-dimensional verification is formed through fuzzy logic judgment, operation parameters are adjusted in real time through PID control, strategy weight is optimized through a genetic algorithm, feature extraction is reversely corrected, and the fault recognition precision and the response speed are improved; closed-loop feedback is established to continuously optimize the system state, environment and electrical parameter coupling analysis is enhanced, the misjudgment probability of a single threshold value is reduced, parameters are dynamically corrected, the adjustment real-time performance and accuracy are improved, the adaptive capacity under the complex working condition is enhanced, a complete closed loop of collection, analysis and feedback is established, and the insulation degradation judgment reliability is improved.

The invention relates to the technical field of chip scheduling and optimization, in particular to a neural network-based main control chip task scheduling and dynamic performance optimization method, which comprises the steps of data acquisition and feature engineering, neural network model design, simulation environment training, model compression and deployment preparation, real-time state monitoring, dynamic decision reasoning, scheduling strategy execution and performance optimization. The data acquisition and feature engineering comprises the following steps: S1, hardware index acquisition; analyzing task attributes (calculation-intensive / IO-intensive), a dependency relationship (DAG), deadline (Deadline) and a resource demand (CPU / GPU occupancy rate); collecting data during chip operation through a performance counter (IPC, cache hit rate and branch prediction error rate), a temperature sensor and a power consumption monitoring unit (PMU); the neural network scheduler can achieve the energy efficiency ratio which is 20%-40% higher than that of a traditional method (such as a CFS scheduler), meanwhile, the neural network scheduler adapts to sudden load changes, and the practicability and the application range of a main control chip are wider.

The invention relates to the technical field of artificial intelligence and biomedicine, and provides a multi-agent diagnosis planning device and method based on a consultation thinking process. The multi-agent diagnosis planning device comprises a diagnosis planning agent, a pathological section analysis agent, an in-hospital information aggregation agent, an information search agent, a knowledge base search agent, an evaluation agent, an arbitration agent and a risk assessment agent. Each agent realizes data interaction through a dynamic priority message bus, and the evaluation agent and the arbitration agent form a progressive verification closed loop: after the evaluation agent outputs a question evidence chain, the arbitration agent triggers diagnosis correction only when question items are greater than 3 items, and otherwise, final diagnosis is output based on a preset rule. According to the invention, the thinking process of multidisciplinary expert collaboration in clinical consultation is simulated by constructing a multi-agent collaborative diagnosis framework, and the whole process intelligence from medical data acquisition and analysis to diagnosis decision is realized.

The invention discloses a vacuum combined preloading intelligent regulation and control method and system for coastal soft foundation treatment, and the method comprises the steps: cleaning a construction area, laying a drainage sand cushion layer and a plastic drainage plate, constructing a vacuum system and a monitoring network, carrying out preloading according to a layering grading and tide adaptation principle, and starting a vacuum control unit. Data is collected and analyzed in real time to trigger a regulation and control instruction, a vacuum degree compensation value and supplementary loading operation are adjusted according to the instruction, secondary strengthening is conducted on an area with the strength not reaching the design, and finally unloading and leveling are conducted according to the standard; the system comprises a data acquisition module, an edge calculation module, an intelligent control module, a stacking execution module and a vacuum regulation and control module, and the modules are connected through wired or wireless communication links to realize data interaction and instruction transmission; according to the method, the problems that the vacuum degree is unstable and regulation and control are lagged in the coastal tidal environment in a traditional method are solved, and the soft foundation treatment efficiency and safety are improved.

The invention provides a fracture deformation-seepage cross-scale visualization experiment device and a test method, and relates to the technical field of hydraulic rock mechanics and measurement. Comprising a macroscopic observation assembly, a microscopic observation assembly, a microscopic seepage model, a temperature-stress-seepage loading system, a monochromatic coaxial light source and a data acquisition and analysis system, the microscopic seepage model is used for placing a fractured rock mass; the temperature-stress-seepage loading system is used for injecting fluid with fluorescent microspheres into the microcosmic seepage model, applying load, regulating and controlling temperature and collecting data; the data acquisition and analysis system is used for processing data and images. By arranging the macroscopic observation assembly and the microcosmic observation assembly, double-scale synchronous observation is achieved, the whole process of fracture internal fluid interface evolution and rock mass deformation can be obtained in real time under the multi-physics field coupling conditions of temperature, stress, seepage and the like, visual correlation of deformation, flow and stress is achieved, and the measurement accuracy is improved. And an experimental basis is provided for establishing a fracture multi-field coupling mechanism model.

The invention discloses a dual-carbon data acquisition and analysis system and method based on multi-source information fusion, relates to the technical field of dual-carbon data acquisition and analysis, and solves the technical problem that in the prior art, energy consumption monitoring and analysis cannot be performed on petrochemical enterprises in a dual-carbon data acquisition and analysis stage, so that the accuracy of data acquisition cannot be ensured. Specifically, an energy consumption analysis unit carries out operation energy consumption monitoring analysis on a petrochemical enterprise, collects statistical deviation information and data floating information, and deduces an energy consumption monitoring analysis result according to information comparison; the production process detection unit is used for detecting the production process of the petrochemical enterprise, and deducing whether the production process meets the actual requirements or not through data acquisition and analysis; and the carbon emission data analysis unit performs carbon emission data analysis on the petrochemical enterprise, and deduces whether the carbon emission of the petrochemical enterprise meets the actual demand through carbon emission data analysis.

The invention discloses a collection, analysis and utilization linkage method for the full life cycle of vulnerability intelligence, which comprises the following steps: respectively acquiring original vulnerability intelligence of a plurality of heterogeneous data sources, and carrying out standardization processing on the original vulnerability intelligence to obtain vulnerability description information; constructing an asset knowledge graph, wherein the asset knowledge graph is used for representing IT asset objects in the enterprise and dependency and deployment relationships among the IT asset objects; performing graph traversal query on the vulnerability description information based on an asset knowledge graph, and identifying an affected asset list affected by vulnerabilities; and according to a preset response strategy, generating a safety response instruction from the affected asset list and sending the safety response instruction to the safety protection system. According to the method, the asset knowledge graph is constructed and the multi-source vulnerability information is subjected to standardization and mapping correlation analysis, so that the accurate and rapid identification of the affected assets of the power system and the automatic response strategy generation are realized, and the efficiency and the accuracy of the vulnerability management of the key information infrastructure of the power grid are effectively improved.

The invention belongs to the technical field of cable fault positioning, and discloses a cable branch box fault early warning and positioning system based on online partial discharge monitoring. Comprising a topology building module which is used for building a topology model in a cable branch box and defining a signal propagation path rule; pre-calculating signal expectation characteristics from each topological node to all monitoring sensors to form a structured expectation library; the acquisition and analysis module is used for acquiring multi-source transient signals and performing feature extraction to obtain an information fusion matrix; the decoupling positioning module is used for performing analysis based on the information fusion matrix and the structured expectation library to obtain a fault positioning point; the evaluation and early warning module is used for extracting all transient events in a preset time period corresponding to the fault positioning point, forming a time sequence feature sequence, extracting and analyzing an evolution index of the time sequence feature sequence, obtaining a risk transition probability, dividing risk levels and carrying out corresponding early warning; according to the invention, non-confusion accurate positioning of the partial discharge source of a specific joint or a cable section in the branch box is realized.

An emotional disorder recognition control model acquisition method and system based on near-infrared brain imaging map characteristics, a controller and a control method, and the method comprises the following steps: step 100, fNIRS-based multi-dimensional nerve marker acquisition and analysis, step 200, an integrated handheld diagnostic device, step 300, a dual-mode high-speed intelligent analysis system, step 300, a near-infrared brain imaging map characteristic analysis system, and step 300, a near-infrared brain imaging map characteristic analysis system. And step 400, a closed-loop AI training and database iteration system realizes a link of collection-analysis-diagnosis-display by fusing technologies of signal collection, data preprocessing and normalization, characteristic parameter extraction, intelligent report display and the like, so that the transformation of mood disorder screening from subjectivity to objectivity and from experience driving to data driving is promoted, and the mood disorder screening efficiency is improved. Therefore, the embedded analysis system for the rehabilitation medical scene is provided.

The invention relates to the medical field, and discloses a gyromagnetic pulse action path optimization method and system, and the method comprises the steps: S1, carrying out the pulse data collection of a patient through pulse analysis equipment, and generating original pulse data; performing denoising processing on the original pulse condition data to obtain clear pulse condition data; s2, fusing the clear pulse condition data with other diagnosis information of the patient on the basis of a four-diagnosis combined parameter concept to generate comprehensive health assessment data; performing simulated fingering acquisition and analysis according to the comprehensive health assessment data, simulating the influence of different fingering on the pulse condition, and obtaining a simulated fingering analysis result; according to the method, through multi-part synchronous pulse condition collection, intelligent denoising and a deep learning filtering model, the definition and authenticity of pulse condition data are effectively improved, and the influence of environmental noise is reduced; the pulse condition data, the tongue condition, the facial expression, the voiceprint feature, metabonomics detection and other information are subjected to cross-modal fusion, and comprehensive assessment of the health state of the patient is achieved in combination with the traditional Chinese medicine four-diagnosis combined reference concept.

The invention relates to the technical field of network attack and defense elements, in particular to an attack and defense element collecting and processing method and system based on multi-source data. Comprising the steps of constructing a plurality of data monitoring points based on network system parameters; generating an acquisition evaluation value of each data monitoring point, and setting an initial acquisition frequency of each data monitoring point according to all the acquisition evaluation values; acquiring a monitoring data packet of each data monitoring point, and judging whether a primary acquisition instruction of each monitoring point is generated or not according to all the monitoring data packets; a plurality of data monitoring points are established in a network system according to the characteristics of the attack and defense elements, and the preprocessing model and the initial acquisition frequency of each data monitoring point are dynamically adjusted according to the historical characteristics of each data monitoring point, so that the overall operation load is reduced. And the attack and defense element acquisition and analysis efficiency of the network system is improved. Cooperative collection of multi-dimensional heterogeneous data is realized, and the attack and defense element collection and analysis efficiency of a network system is improved.

The invention discloses an environment control method, system and device for a mobile high-voltage chamber and a medium, and belongs to the technical field of high-voltage chamber environment regulation and control, and the method comprises the following steps: dividing the mobile high-voltage chamber into A analysis regions, and setting a temperature control intelligent agent in each analysis region; the method comprises the following steps: acquiring equipment state data of an analysis area through a temperature control intelligent body, and performing reconstruction analysis on the equipment state data by using an auto-encoder to obtain a state label; combining the temperature control intelligent agent with the state label, and calculating equipment state data to obtain a health state matrix; environment data of each analysis area is collected in real time, a microclimate situation map is formed in combination with the health state matrix, and an optimal partition temperature control instruction is generated; and adjusting the environment of each analysis area through the optimal partition temperature control instruction. The method has the beneficial effects that the mobile high-voltage chamber is divided into a plurality of analysis areas, and the temperature control intelligent agent is arranged in each area, so that the fundamental conversion from the traditional centralized control to the distributed cooperative control is realized.

The invention relates to the technical field of data processing, and particularly discloses a Tibetan word segmentation method and system based on a multi-language pre-training model CINO, and the method comprises the steps: collecting a to-be-labeled data set, and providing massive text resources for subsequent research; then word segmentation conversion is carried out to obtain a to-be-trained data set, the text is converted into a lexical element sequence suitable for model processing, a model learning structure is facilitated, attribute parameters of the to-be-trained data set are analyzed, whether data division is carried out or not is judged accordingly, and reasonable division can guarantee representativeness of a training set and a verification set, avoid data distribution deviation and improve the generalization ability of the model; then a training and verification data set is obtained through division and used for training a multi-language pre-training model CINO, training process parameters are collected and analyzed, the model training state can be informed, strategies and hyper-parameters can be adjusted in time, and model initialization is completed, so that Tibetan word segmentation accuracy and reliability are promoted to be improved, and application of the multi-language processing technology in the Tibetan field is assisted.

The invention relates to a coal industry chain operation plan assessment method and device, equipment and a storage medium. The method comprises the steps of obtaining to-be-assessed data; determining an evaluation index of the multi-dimensional evaluation index system; determining an evaluation period, a simulation scene and time constraints, space constraints, occurrence probability and influence intensity related to the simulation scene, and obtaining scene setting parameters; a preset objective weighting method is adopted to calculate the weight of each third-level index, and a TOPSIS multi-attribute decision model is combined to calculate and obtain a comprehensive evaluation result; performing problem analysis based on the comprehensive evaluation result, generating optimization suggestions corresponding to the problems, and obtaining a plan analysis result; and generating a target evaluation report. According to the integrated operation plan evaluation method provided by the invention, automatic acquisition and analysis of index data and report generation can be realized, automation and intelligence of an evaluation process are effectively realized, and evaluation efficiency, accuracy and systematicness of a coal industry chain operation plan are greatly improved.

The invention relates to the technical field of digital information monitoring, in particular to a network equipment operation monitoring log integration system based on multi-source data acquisition and analysis. Comprising a multi-source data acquisition unit; a pretreatment unit; the intelligent analysis unit is used for constructing a normal operation behavior baseline of the network equipment, identifying abnormal operation of the equipment and mining a log association relationship among multiple pieces of equipment; a log integration unit; and a visualization unit. According to the invention, an intelligent analysis unit adopts an attention mechanism enhanced time sequence modeling technology to construct an equipment normal operation behavior baseline, sub-fragments are divided according to equipment operation periodicity, and differentiated weights are given according to key index fluctuation characteristics, so that the baseline is more focused on a time period with significant influence on the equipment state; and meanwhile, an improved association mining algorithm is combined to introduce an equipment topology association degree pruning low association item set, so that the rationality of a behavior baseline and the comprehensiveness of multi-equipment log association analysis are improved.

The invention belongs to the field of information network security. The invention specifically discloses an agent-based logic vulnerability detection method, system and device, and a medium. The method comprises the following steps: capturing service system request response data through network traffic, identifying an HTTP protocol through a port and protocol features, filtering non-HTTP request data, extracting and analyzing the request data, standardizing extracted parameters, continuously collecting and analyzing through an API analysis agent, improving the semantic analysis capability of a large model, perfecting a logic relation graph, and improving the semantic analysis efficiency of the large model. A complete vulnerability life cycle data link is constructed through a vulnerability analysis agent, the system logic vulnerability mining efficiency and coverage are improved, and automatic logic vulnerability alarm and disposal can be realized and the risk disposal real-time performance is improved by accessing the agent to a network security protection product, an alarm analysis platform and other systems.

The invention relates to the technical field of AI large model analysis, and discloses an AI-based intelligent chest card collection and analysis method and system, and the method comprises the steps: achieving the communication between an equipment management service module and chest card equipment through an emqx service module, and carrying out the information configuration of the chest card equipment through the equipment management service module; sound information is collected through chest card equipment; and uploading the sound information to a quality inspection analysis platform, processing the sound information through the quality inspection analysis platform to obtain an audio transliteration text, and analyzing the audio transliteration text based on an AI large model to obtain a service judgment result. Compared with a traditional keyword matching mode, the AI analysis is carried out in a mode of transferring the text through the audio, the ability of understanding semantics and hidden information can be improved, and the accuracy of judging the service quality can also be improved. The intelligent chest card recognizes personnel position information and personnel face information through the structured light module, and the definition of human voice collection can be greatly improved.

The invention provides an employee work assessment recommendation method and system based on a collaborative filtering algorithm, and relates to the technical field of employee work assessment, and the method comprises the steps: extracting a task dependency relationship and time consumption data from a project management system, and constructing an employee task dependency graph; secondly, collecting and analyzing work interaction information containing document operation and task marking features, and identifying task switching critical points to generate quantitative indexes; constructing a similar employee group and extracting an efficient working mode by means of a collaborative filtering algorithm after establishing an evaluation data set through space-time alignment of the two; by taking the task dependency graph as an environment state and the efficient mode as a reference, generating a task sequence optimization scheme by using a reinforcement learning model; according to the scheme, the staff group composition is adjusted according to the scheme execution effect, the optimization model is fed back, finally, a comprehensive evaluation result is generated based on the scheme and actual task sequence matching degree and the quantitative index stability, the task sequence optimization and physiological state adjustment ability can be accurately evaluated, and the work assessment scientificity and the task execution efficiency are improved.

The invention provides a remote data acquisition and analysis method and system for a baby stroller, and the method comprises the steps: synchronously acquiring environmental stimulation and passenger physiological reaction data through multiple modules on the baby stroller, locally processing the environmental data into cumulative stress indexes, and processing the physiological data such as sound production into state classification labels. And when the passenger has negative stress states such as crying, screaming and the like, the system automatically packs the accumulated stress index sequence in the previous period of time to form a stress event data packet. And the data packet and baseline data in a normal state are transmitted to a remote server together, and a specific environment mode causing the negative stress of the passenger is identified through comparative analysis. According to the method, through event-triggered data acquisition and comparative analysis, specific external factors causing discomfort of infants can be accurately identified and understood.

The invention discloses a terminal connector multi-station data acquisition and analysis method and platform, and relates to the technical field of data acquisition and analys.The method comprises the steps that a unified machining time axis of a terminal connector is established, and a multi-station monitoring data set is established; state abnormity identification based on stations is carried out, and station abnormity is established; configuring a dynamic state chain by using a multi-station monitoring data set and a processing time axis; performing residual analysis according to the dynamic state chain and the healthy connector track, and establishing an abnormal focus point; configuring a behavior causal database between stations, and establishing a backtracking positioning result; and generating a terminal connector quality detection result. According to the invention, the technical problems of non-uniform multi-station data acquisition, low abnormal positioning precision and low quality detection efficiency in the production process of the terminal connector in the prior art are solved, and the technical effects of realizing multi-station data acquisition in the whole production process of the terminal connector and improving the abnormal positioning precision and the quality detection efficiency in the production process are achieved.

The invention relates to the technical field of agricultural data visualization, in particular to a salinized cotton field visual multi-point salinity collection and analysis method and system.The method comprises the following steps that soil conductivity distribution data of a salinized cotton field area is obtained, a high-salinity accumulation area and a low-salinity dilution area are recognized, particle gap distribution characteristics are collected, and a salinized cotton field is obtained; and screening areas with loose or compact particle structures, executing temperature gradient analysis, screening surface thermal environment abnormal subareas, detecting wind speed distribution, removing wind field disturbance areas, and obtaining a recommended planting area list. According to the method, high and low salt areas are accurately identified through salt space distribution analysis, distribution precision is improved, humidity dynamic expression is refined, structural abnormal blocks are screened by using a particle gap change trend, soil management is optimized, surface temperature and wind speed data analysis is superposed, thermal disturbance and wind field abnormity are eliminated, and agricultural management precision is improved through multi-dimensional data fusion. The capability of coping with a complex environment is enhanced, efficient decision making is effectively supported, and the overall agricultural production benefit is improved.

The invention discloses a civil aviation operation safety assessment platform and method, and relates to the technical field of civil aviation operation safety assessment, WiFi signal interference risk assessment and hierarchical regulation are realized through cooperation of multiple modules, an electronic interference atlas module acquires key parameters, quantifies crosstalk probability and preliminarily judges the risk in combination with a threshold value and a sensor state, and the risk is evaluated by a WiFi signal. The signal coupling entropy analysis module calculates dynamic coupling entropy based on signal variables and monitors interaction risks in real time, the digital twin simulation module fuses historical data to evaluate the jump probability of a display and early warns potential threats in advance, and the safety margin optimization module implements three-level regulation and control according to risk levels. According to the method, an acquisition-analysis-simulation-regulation closed-loop system is constructed, interference can be accurately quantified, abnormity can be captured in real time, a strategy can be dynamically adjusted, civil aviation operation safety and regulation efficiency in a complex electromagnetic environment are improved, system fault risks caused by signal crosstalk are reduced, and an efficient scheme is provided for intelligent safety assessment.

The invention relates to the technical field of tunnel settlement data acquisition and analysis, in particular to a tunnel settlement data acquisition method and system based on laser ranging, and the method comprises the following steps: S1, equipment is a monitoring device comprising a holder and two laser ranging sensors with a fixed included angle, the first sensor horizontally points to the side wall of a tunnel, and the second sensor horizontally points to the side wall of the tunnel; the second sensor points to the tunnel vault at an included angle theta; s2, point distribution and base point selection, wherein monitoring points are distributed in the tunnel according to a preset rule, and a zero reference point is arranged in a stable area of a tunnel portal; in the scheme, through integration of the double laser sensors and automatic holder scanning, high-density and high-precision automatic continuous data acquisition of the tunnel section is realized, and the defects of low efficiency and insufficient coverage of a traditional method are overcome; meanwhile, by means of intelligent coordinate transformation, a deformation calculation model and a multi-stage early warning mechanism, real-time calculation, trend prediction and graded automatic alarm of settlement and convergence parameters are achieved.

The invention discloses an acoustic stimulation nerve regulation and control service management system combining AI and big data analysis, and the system comprises a cloud center layer, a region edge layer, a doctor management layer and a patient terminal layer which are connected with one another, the cloud is provided with a client management module, and an exclusive account is established for each patient; and an individualized sound stimulation scheme is generated and dynamically optimized by using an AI algorithm to realize remote closed-loop regulation and control. The platform supports remote demonstration and teaching of experts, autonomous operation and maintenance of clients and a mutual assistance network of the experts, and a cloud-side-end collaborative AIoT intelligent system is formed. The system is provided with a national-level data supervision interface, so that safety and controllability are ensured. Through the above mode, the AI and big data analysis combined acoustic stimulation nerve regulation and control service management system improves the accuracy and efficiency of personalized scheme formulation and optimization by constructing a collection-analysis-decision-execution-feedback-optimization closed-loop process; therefore, cloud-edge-end-human collaborative closed-loop intelligent regulation and control management with individualized nerve regulation and control and compliance safety considered is formed.

The invention relates to a decision recommendation system and method for preferentially processing key data of a supply chain of a manufacturing enterprise. According to the decision recommendation system and method, through a data fusion module, a priority evaluation module, a decision recommendation module and a self-adaptive feedback module, supply chain key data management realizes collection, analysis and decision; the invention discloses an optimized decision recommendation system and method for an automatic closed-loop process. The system is characterized by comprising a data fusion module, a priority evaluation module, a decision recommendation module and a self-adaptive feedback module, the data fusion module outputs structured data to the priority evaluation module, and the decision recommendation module generates a scheme according to the priority and feeds back an actual effect to the self-adaptive feedback module after execution. The self-adaptive feedback module reversely updates the priority rule; the data fusion module is composed of a data acquisition unit, a data preprocessing unit and a data storage unit, and the priority evaluation module is composed of a rule engine unit, a machine learning model unit and a dynamic weight adjustment unit.

The invention relates to the technical field of digital geological project management, in particular to a geological project management field work flow digital construction method, which comprises the following steps of based on mobile application data acquisition, analyzing field work task progress, environment information and operation normalization, identifying abnormal nodes, and adjusting task priority and resource configuration. According to the geological field operation risk safety level judgment method and system, the task states are analyzed in combination with the environment elements and the execution conditions during collection, the information comprehensiveness and transparency are improved, and the geological field operation risk safety level judgment information table is obtained. During execution, priority and resource configuration are dynamically adjusted, resource utilization efficiency is enhanced, resource input and output results are recorded, operation efficiency and matching degree are quantified, task positions and environment factor weights are fused, risk influences are normalized and analyzed, and project continuity and safety are guaranteed.

The invention relates to the technical field of information acquisition, in particular to a fire-fighting emergency broadcast data information acquisition system which comprises the following steps: performing sound source positioning analysis on original data to obtain sound source distribution data; performing sound propagation loss estimation according to the sound source movement track data to obtain sound propagation loss data; emergency broadcast coverage demand period reference simulation evaluation is carried out according to the sound propagation loss data to obtain period reference data; and according to a strategy gradient algorithm, an emergency broadcast putting strategy adjustment model is constructed through the environment correction data, and the emergency broadcast putting strategy adjustment model is sent to a fire-fighting command cloud platform so as to execute fire-fighting emergency broadcast data information acquisition and analysis. According to the method, the attenuation degree of the broadcast signals under different environment conditions can be analyzed through estimation of the sound propagation loss, data support can be provided for the actual broadcast propagation effect, the broadcast signals can be optimally delivered according to the environment conditions, and therefore effective transmission of the signals is ensured.

The invention relates to the related technical field of sustainable development (ESG), in particular to an ESG (environment, society and governance) full-scene evaluation solution system and method. Along with the increasingly serious problem of global sustainable development, the environment, society and government (ESG for short) has become an important factor which must be considered in the decision making process of enterprises and governments. In order to promote the realization of a sustainable development target, all walks of life start to actively collect, analyze and evaluate ESG related data. Many companies, investors and supervision organizations all positively discuss how to guide decisions through an accurate and effective ESG evaluation method, and sustainable economic growth and social responsibility are promoted. The invention provides a brand-new ESG full-scene evaluation solution, and aims to provide an efficient and accurate ESG evaluation method capable of covering multiple scenes by constructing an integrated and systematic management platform. According to the method, through a scientific data acquisition and analysis technology and in combination with a multi-dimensional evaluation index system, comprehensive evaluation on various aspects of environment, society and governance of an enterprise or a project is realized, and the ever-increasing demand of the modern society for sustainable development is met.

The invention relates to the technical field of motor test equipment, in particular to a test device for isolating generator vibration and a use method thereof. In order to solve the problems of insufficient external vibration isolation, structural adaptability, working condition adjustment flexibility, data acquisition precision and the like in the prior art, the invention provides the following technical scheme that the device comprises a base, a supporting platform is mounted above the base, a generator set is mounted at the top of the supporting platform, and a motor is mounted in the lower part of the supporting platform; a transmission shaft for connecting the motor and the generator set is arranged between the motor and the generator set; the supporting platform comprises a lower support in threaded connection with the base, and the lower support is fixedly connected with a plurality of sets of organic glass plates which are oppositely arranged through threads. External vibration interference can be effectively isolated, data accuracy is improved, the device is simple in structure and convenient to mount, adapts to different types of generators, can flexibly adjust working conditions, realizes integration of data acquisition and analysis, is wide in application scene, and improves test efficiency and reliability.