129results about How to "Realization risk" patented technology

The invention discloses an environment risk source pre-warning system, comprising a data collector, a data server, a risk real-time evaluation system and a warner. The data collector is used for collecting real-time monitoring data of detection points in an environment risk source. An environment risk source information database for recording environment risk source basic information and a threshold value database for recording the threshold values corresponding to the real-time monitoring data of the detection points are installed in the data server. The risk real-time evaluation system is used for carrying out security evaluation on the environment risk source and calculating the risk degree of the environment risk source. The warner is used for carrying out selective warning according to the risk degree of the environment risk source. According to the system, the risk evaluation and pre-warning can be carried out on the environment risk source, a monitor can be helped to take countermeasures effectively and timely, and losses resulting from a risk event can be reduced to the lowest.

The invention discloses a block chain-based data processing method and device. The method comprises the steps of obtaining user behavior data associated with a contractual relationship based on the contractual relationship when a block chain node determines the contractual relationship established between a first user and a second user, and determining a data access permission of the user behavior data; according to a preset relationship between the data access permission and a processing policy, determining the processing policy of the user behavior data, wherein the processing policy contains a processing rule matched with the data access permission; and performing processing on the user behavior data by utilizing the processing policy. By utilizing a block chain technology, different processing modes are adopted based on different data access permissions corresponding to the user behavior data, so that the processed data is ensured to be stored in the block chain node, the data is effectively ensured not to be tampered, the accuracy of user credit data obtained by assessment according to the data subsequently is improved, and the risk of internet financial businesses is effectively controlled.

The invention belongs to the technical field of hidden trouble prediction and management for trees in the channel of an overhead transmission line and specifically relates to a tree obstacle hidden trouble automatic pre-warning system for an overhead transmission line and a pre-warning method for the above system. The method comprises the steps of carrying out the field survey to conduct the data statistics on the hidden troubles of trees in an overhead transmission line protection zone and construct a hidden trouble database for trees in the channel of an overhead transmission line; conducting the traversing treatment on all trees in the tree hidden trouble database at regular intervals; for any tree with a hidden trouble, calculating the current distance between the tree and a corresponding conductive wire, judging the type of the tree hidden trouble, automatically pre-warning, dynamically evaluating the risk of the hidden trouble according to provisions on the safe operation of the overhead transmission line, and dynamically updating the hidden trouble data of the tree in real time. According to the invention, the problem that existing tree obstacle hidden trouble-shooting methods are time-consuming, labor-consuming and easily cause the artificial misjudgment can be solved. Meanwhile, the pre-warning information is provided timely. The damage to both the personal safety and properties, due to the occurrence of tree obstacle hidden hazards, can be prevented.

The invention discloses a risk early warning management control system. The system comprises an acquisition module, a configuration module, a calculation module and a management control module. The acquisition module is used for acquiring field inspection information, operation state information of a plurality of terminal facilities and collection information. The configuration module is used forconfiguring weight scores and evaluation grade values of the terminal facilities according to the field inspection information, the operation state information of the terminal facilities and an influence proportion. The calculation module calculates weight values of the terminal facilities according to the weight scores, and calculates a risk value of a current area according to the weight values,the evaluation grade values and the collection information. The management control module judges a risk level to which the current area belongs according to the calculated risk value, and carries outcorresponding risk management control according to the risk level. The invention further provides a risk early warning management control method. The risk early warning management control system andmethod can adjust relative weight values and evaluation grade values of various influence factors according to current environment conditions, thereby reducing the degree of human intervention in a risk evaluation process.

The disclosure relates to a safety monitoring system based on multiple sensors. The system comprises a sensing equipment end, a local server, a cloud server and a client, wherein the sensing equipmentend is used for acquiring environment information of a target user and sending the environment information to the local server; the local server is used for inputting the environment information as atraining sample into an artificial neural network model to carry out self-learning training so as to update parameters of the artificial neural network model; the cloud server is used for sending theupdated parameters to the sensing equipment end, receiving a safety monitoring state of the target user, which is from the sensing equipment end and is returned according to the updated parameters, and pushing the safety monitoring state of the target user to the client; and the client is used for receiving the safety monitoring state of the target user. According to the disclosure, by adopting amulti-dimension sensing technology and a self-learning algorithm based on big data, living habits of the target user, such as an old person, are learned and understood so as to achieve the ability ofpredicting the potential risks.

The invention discloses a credit loan risk joint control method, device and equipment and a readable storage medium. The credit loan risk joint control method comprises that when a credit loan approval instruction is detected by a node device in an all-in-one machine, application information corresponding to the credit loan approval instruction is obtained; whether a credit load application behavior corresponding to the application information is a fraud behavior is identified; if YES, a first blacklist file is generated on the basis of the application information; and the first blacklist fileis broadcast to other node devices associated with the all-in-one machine, so that the other node devices updates local blacklist files thereof. The technical problem that different places or types of credit load risks cannot be controlled in a joint way due to the fact that different types of credit devices work in independent states and cannot synchronize application risk information in real time in the prior art is solved.

The invention discloses a hadoop-based panoramic big data distributed storage method, can provide a novel big data distributed storage method for big data of intelligent grids, and can effectively solve the problems of storage redundancy, low access efficiency, poor disaster recovery robustness and the like of the traditional relational database. The hadoop-based panoramic big data distributed storage method comprises the steps of firstly, optimizing the design of an Hbase table based on distributed data storage and access to minimize and fixedly set the row key length, then performing load balance, JVM (Java Virtual Machine) optimization and split-and-merge service optimization on Hbase system performance, and finally, optimizing large-scale small files of an HDFS (Hadoop Distributed File System) by adopting a labeling method. The method obviously improves the power big data distributed storage technology on storage redundancy optimization, fast access, high efficiency and high reliability and disaster recovery security.

The invention discloses an operation simulation system based on a human body organ 3D model, comprising a CT data input unit, a CT image segmenting unit, a three-dimensional modeling unit and an operation simulation unit; the CT data input unit is used for inputting CT data; the CT image segmenting unit is used for segmenting soft tissue organ, cancer, blood vessel and hard tissues from the CT image, and segmenting the soft tissue according to the blood vessel; the three-dimensional modeling unit is used for establishing a three-dimensional model of every section of soft tissue organ, cancer, blood vessel and hard organ, and integrating to be a human body organ 3D model; the operation simulation unit comprises an operation simulation excision module, an excision result analysis module, an operation simulation measuring module, and an operation simulation risk evaluating module. The invention further discloses an operation simulation system based on the human body organ 3D model. The system and the method can directly acquire the section of the organ suffering from cancer and accurately position the cancer, thereby further reducing the operation difficulty and risk, and realizing the pre-operation simulation excision and operation risk evaluation.

The invention relates to the field of urban safety risk management and control, and discloses an urban safety regional risk analysis method and system. The method comprises the following steps: acquiring video data of a crowd activity region by video monitoring equipment; acquiring block port data of each main entrance of a region; counting and calculating the traffic flow of a block port according to the block port data of the region, analyzing the proportion of vehicles to personnel entering the area, acquiring the data of vehicles remaining in the region, and carrying out early warning about regional road congestion; analyzing video data of the crowd activity region based on a video detection technology, and identifying crowd real-time statistics, density estimation and regional dynamichuman flow abnormal characteristic analysis under multiple scenes in the region by adopting a depth learning algorithm; and carrying out probability analysis and verification by utilizing regional pedestrian flow historical data, block port flow historical data, crowd real-time statistical data and the block port data of main entrances, calculating regional entrance pedestrian flow and traffic flow density, and carrying out early warning about regional safety risk in advance. By the method, real-time sensing of human flow and traffic flow in a key region is realized, and safety risk early warning and prevention in the key region are also realized.

The invention relates to a chemical industry park real-time quantitative risk assessment method based on multi-disaster real-time coupling, introduces a Monte Carlo analysis method and solves the problem of uncertainty of setting of a model probability parameter. By effective integration of the Monte Carlo analysis method and a risk distance calculation method, a chemical industry park site selection risk protection distance is initially determined. According to an environmental risk system principle, by combining characteristics of the chemical industry, a chemical industry park enterprise comprehensive risk assessment index system based on inherent risks of a risk source, effectiveness of a prevention and control mechanism and vulnerability of a receptor is constructed. A catastrophe rating method is introduced to assess an environmental risk comprehensive level, a chemical industry enterprise environmental risk comprehensive assessment method based on a catastrophe principle is proposed, and comprehensive assessment grades are divided into five grade levels so as to discriminate a comprehensive risk level of a chemical industry park enterprise and timely take emergency response strategies. According to the chemical industry park real-time quantitative risk assessment method disclosed by the invention, planning evaluation and risk management of a chemical industry park can be implemented, and a risk prevention ability and a risk management level of the chemical industry park can be improved.

The invention discloses a waste heat recovery system based on a data center and a control method for the waste heat recovery system. The waste heat recovery system comprises a waste heat collecting unit, a heat pump unit, a heat storage unit, a waste heat conveying unit and a user end. The waste heat recovery system has the advantages that the waste heat collecting unit collects heat generated ina machine room of the data center, and the heat is transmitted to the user end through the waste heat conveying unit after being compressed and condensed by the heat pump unit; the waste heat recoverysystem further stores a part of waste heat in advance through the heat storage unit, when the waste heat is insufficient, the waste heat is released and used, and therefore the waste heat utilizationrate is increased; the purposes that the indoor waste heat is extracted and utilized, circulating water of a heat supply network is heated, and heat supply is realized can be achieved by the waste heat recovery system; and the heat generated by the machine room of the data center can be recycled and reused by the waste heat recovery system, so that energy waste and environmental pollution causedby emission of the waste heat of the machine room can be avoided.

The invention relates to a flood control risk identification and evaluation method for a water diversion project. The method comprises the following steps: collecting and arranging flood control dataof a water transfer project; carrying out rainfall runoff production, confluence flow capacity, channel section engineering geological characteristics and economic and social layout first-level floodcontrol risk factor identification; decomposing the first-level flood control risk factor into a second-level flood control risk factor, and constructing a flood control risk evaluation index system;performing flood control risk factor index numerical calculation and normalization processing; calculating index weights through an analytic hierarchy process; and determining and evaluating the comprehensive flood control risk level of the channel section. The invention has the beneficial effects that: starting with various risk sources and risk events involved in the whole flood disaster chain process, the system comprehensively identifies flood control risk factors of the water diversion project, constructs a corresponding evaluation index system, establishes a comprehensive flood control risk evaluation model of the water diversion project based on a risk evaluation theory, and realizes quantitative evaluation and risk grading and classification management of flood control comprehensive risks of different channel sections of the water diversion project.

The invention discloses a sky-ground integrated agricultural remote sensing big data system based on smart agriculture. The sky-ground integrated agricultural remote sensing big data system comprises a smart agriculture map display and query module, an agricultural soil environment information display module, a remote sensing seedling condition dynamic monitoring module, a growth model simulation analysis module, a soil moisture monitoring module and a meteorological data display and comparison module. The system has the beneficial effects that dynamic monitoring data of crop growth vigor, flood and drought disasters, diseases and pests and the like are realized, and the optimized fertilization quantity, the base fertilizer and topdressing fertilizer distribution proportion, the fertilization period and the fertilization method of different crops in each fertilization unit are mastered through field trials; basic parameters such as a soil nutrient correction coefficient, a soil fertilizer supply capability, nutrient absorption amounts of different crops and a fertilizer utilization rate are found out; a crop fertilization model is constructed, a basis is provided for fertilization partitions and fertilizer formulas, the basis is presented to governments at all levels and agricultural competent departments in a visual mode, and the functions of real-time monitoring, risk early warning and data analysis of global disease and pest occurrence situations are achieved.

The invention discloses an overflow early-warning method according to vehicle-passing data. Vehicle entering/exiting flow rates at different moments of an upstream and a downstream of a road segment are analyzed based on a phase sequence and phase duration of a signal control scheme, a road segment vehicle bearing capacity is analyzed based on a GIS (geographic information system) map, and a dataanalysis model is constructed based on a vehicle-passing information rule at the downstream of the road segment, and finally, the overflow risk quantization and early-warning are performed.

The invention relates to an automobile electronic technology, in particular to a method and a system for evaluating performance of a power supply system of an automobile. The method for evaluating the performance of the power supply system of the automobile comprises the following steps of: determining a group of input parameters including an electricity utilizing load demand and an electricity utilizing duration of a starting system and/or electrical components of a tested automobile; according to the input parameters, controlling the power supply system to supply power to the starting system and/or the electrical components by using a power management system; acquiring running parameters of the power supply system; and according to the running parameters, evaluating the performance of the power supply system of the automobile. Compared with the prior art, the method and the system for evaluating the performance of the power supply system of the automobile have the advantages that: an electric quantity matching test of the whole automobile is not required; functions and reliability of a power diagnosing system are improved; and on-line dynamic electric quantity matching balance is realized and risk evaluation is started.

The invention discloses a multi-view driving risk assessment method and a multi-view driving risk assessment device based on a network connection environment. The method comprises the following steps:step 1, dividing a region to be subjected to risk assessment into a plurality of sub-regions; 2, acquiring first environment sensing information of each sub-region through selected roadside sensing equipment, and judging the confidence coefficient of each sub-region; 3, judging whether the sum of the areas of the sub-regions corresponding to a low-confidence region in the region to be subjected to risk assessment is smaller than a preset ratio of the area of the region to be subjected to risk assessment or not; 4, fusing and splicing the first environmental perception information of the low-confidence region and the second environmental perception information of the same sub-region as the first environmental perception information to obtain an enhanced environmental perception result corresponding to the Alow of the low-confidence region; 5, generating a global environment perception result of the region to be subjected to risk assessment; and 6, evaluating the overall risk of the region to be subjected to risk assessment. According to the invention, the purposes of real-time perception and risk assessment without blind areas can be achieved by using a network connection environment.

The invention provides a third party verification system based on a cloud intelligent seal and a verification management and control method. The third party verification system based on the cloud intelligent seal comprises a cloud intelligent seal terminal, a cloud management server, a cloud management client and a third party verification server, wherein the cloud intelligent seal sends seal information and a seal file picture to the cloud management server, a query code is generated, the query code is sent to the third party verification server through the cloud management server, the cloud management client is used for sending a verification application and receiving verification information among different users, a sealed file picture in need of verification is submitted to the third party verification server through a network, the authenticity of the seal file is verified, and a verification result is fed back. Through connecting the cloud management server of the seal with the cloud intelligent seal terminal with an intelligent function and a network function and the cloud management client, seal management and control cloud intelligence and management and control process integration are realized, and problems of incomplete management process monitoring and large management and control risks due to the blind area in the traditional seal self management process can be solved completely.

The invention discloses a molecular marker for diagnosing cerebral ischemic thrombosis. The molecular marker is a CTAGE5 gene, and early diagnosis can be provided for a patient with the cerebral ischemic thrombosis by detecting expression level of the CTAGE5 gene, so that early detection and early treatment are realized, and death rate of the patient with the cerebral ischemic thrombosis is reduced. The invention provides a cerebral ischemic thrombosis diagnosis product. The product comprises a reagent for detecting the expression level of the CTAGE5 gene and can realize the early diagnosis on the cerebral ischemic thrombosis.

The invention discloses an underground pipe gallery monitoring wireless communication system, which comprises a cloud server, a remote monitoring platform, an Internet gateway, pipe gallery equipmentand pipe gallery monitoring equipment, wherein each set of pipe gallery equipment and each set of pipe gallery monitoring equipment are respectively accessed to the Internet gateway through a 5G communication module, and the Internet gateway is connected with the cloud server through the Internet so as to transmit self operation state data or monitoring data to the cloud server; the cloud server analyzes the received data by using the data service module and stores the received data and an analysis result into a database; and the remote monitoring platform acquires data in the cloud server database through the Internet, and displays and outputs the acquired data in real time. Data communication between the equipment in a comprehensive pipe gallery and the remote monitoring platform is realized by utilizing the Internet of Things and the 5G technology, and the data transmission efficiency is improved, so that the monitoring efficiency can be improved, the risk prediction capability is improved, and the section loss during disasters is reduced.

The invention provides a judgment risk intelligent identification and early warning method. The method comprises the steps of obtaining case elements and calculating feature vectors of the case elements; inputting the obtained case element feature vectors into a trained multi-mark classification model to obtain a set of possible risk categories of the case; calculating a case early warning index according to the possible risk category set of the case, and selecting a preset corresponding early warning mode and an early warning object for early warning according to the value of the early warning index; according to the invention, complex risk points of multiple stages and multiple categories in the judgment process can be automatically identified, and the defect that the current complex judgment risk identification still depends on manual analysis and evaluation is solved; meanwhile, classification and graded intelligent early warning of judgment risks are achieved, and a court can be helped to efficiently respond to the risks so as to reduce risk hazards.

The invention discloses a tilt sedimentation monitoring system based on a surveying and mapping technology and a tilt angle sensor, and particularly relates to the field of building monitoring. The monitoring system comprises a wireless tilt angle sensor, wherein the connection end of the wireless tilt angle sensor is provided with a wireless receiver; the connection end of the wireless receiver is provided with a wireless gateway; the connection end of the wireless gateway is provided with a computer monitoring early warning system; and the connection end of the computer monitoring early warning system is provided with a total station surveying and mapping system. By use of the monitoring system, through the real-time monitoring data of the wireless tilt angle sensor, the dynamic change situation of a monitored object is tracked, and the total station surveys and maps data at a regular interval for approving the integral state of the monitored object so as to accurately master the structure stability situation of a monitored building or structure. The monitoring system is simple in operation, saves time and labor, is high in control flexibility, can lower measurement cost while efficiency is improved, and can realize the accurate monitoring and the risk early warning of the tilt sedimentation problem of the building or structure.

The method discloses risk analysis equipment, a monitoring system, and a monitoring method. The risk analysis equipment comprises a comparison module which is used for comparing the performance monitoring data of a monitored service and a call stack data with a plurality of preset monitoring threshold values, and giving a notice to an analysis module when the performance monitoring data or the call stack data exceeds one monitoring threshold value; the analysis module which is used for receiving the notice from the comparison module, carrying out the matching and comparison of the performance monitoring data and the call stack data with the data of a pre-stored warning or fault cases, and judging whether the monitored service has a potential risk or fault or not. The risk analysis equipment carries out the risk pre-judgment and fault inspection through the simultaneous collection of the performance monitoring data of the monitored service and the call stack data, and improves the fault positioning speed through the analysis of the two types of data.