106 results about "Risk avoidance" patented technology

Method, system and software for social-financial investment risk avoidance, opportunity identification, and data visualization, which can use social data with other data to generate and present new types of data, which can be used by investors to make investment decisions, which can include a scoring model, which can help users identify trends and / or interpret and synthesize large amounts of data based on social data and other data, which can include an interactive, graphical user interface, which allows users to explore and examine social data and other data that can impact, for example, the investment performance of a company's stock, and which can include the ability to click on any word or point on a line plotted over time to see additional information constructs, where the social data can be illustrated via numeric scores, line and scatter plots, word clouds, word radials, gauges and the like.

The invention relates to a self-vehicle active avoidance system based on vehicle-vehicle communication. The self-vehicle active avoidance system comprises a receiving module, a self vehicle information collecting module, an information processing module, an action response module and a sending module, wherein the receiving module is used for receiving front vehicle running information sent by a front vehicle; the self vehicle information collecting module is used for collecting self vehicle running information; the information processing module is used for obtaining the current road information, and is used for judging whether the self vehicle and the front vehicle have a collision occurrence risk or not according to the front vehicle running information, the self vehicle running information and the current road information; when the condition that the self vehicle and the front vehicle have the collision occurrence risk is judged, a control signal for executing the risk avoidance action is output; the action response module is used for responding the control signal output by the information processing module, and controls the self vehicle to execut active warning, active braking or active steering; the sending module is used for sending the self vehicle running information to a back vehicle. The invention also provides a self-vehicle active avoidance system based on vehicle-vehicle communication. The system and the method have the advantage that the risk that vehicles running in the same direction generate rear-end collision and receive rear-end collision can be reduced.

The invention discloses an abnormal state processing method, system and device, belonging to the technical field of Internet. The method comprises that a server obtains abnormal state of a user account according to network operation information of the user account, grades the abnormal state, and pushes the abnormal state carrying the abnormal grade to wearable electronic equipment bound to the user account; the wearable electronic equipment receives the abnormal state, and displays prompt information corresponding to the grade according to the abnormal grade; an operation instruction triggered according to the prompt information corresponding to the grade is received, and sent to the server; and the server receives the operation instruction, and carries out at least one safety strategy processing operation, corresponding to the grade, on the abnormal state of the user account according to the operation instruction. The problems that abnormal state processing methods provided in the background are low instantaneity and risk avoidance effect, the abnormal state can be processed in real time by the method, system and device in the invention, and risks can be avoided.

The invention relates to a multi-scale region flood disaster risk remote sensing assessment method and system. The method comprises the steps of cooperatively extracting feature information of a flood disaster water body by utilizing multi-source multi-platform remote sensing data to form space distribution data of the water body; by analyzing critical features of the flood disaster water body, and in combination with environmental factors in a historical flood disaster occurrence and development process, establishing a flood disaster long-time series data set based on the critical features of the water body; and then according to a reasoning algorithm, performing multi-scale region flood disaster risk level assessment from a disaster flooding range and a disaster loss degree to generate a space distribution result of flood disaster risk assessment. The method has a very important effect for enhancing disaster early warning, avoiding risk and the like, can reduce the loss caused by flood disasters maximally, and is an important scientific basis of performing disaster risk management and decision-making.

The invention discloses an earthquake simulator capable of carrying out an earthquake drill, which comprises a simulating cabin (1), a basic platform (9) and a cabin shaking device, wherein the basic platform (9) is arranged under the simulating cabin (1), and the cabin shaking device is arranged between the simulating cabin and the basic platform. A small shaking device comprises a horizontal shaking device and a longitudinal shaking device. Under the condition of earthquake, the earthquake simulator can help people to understand and learn emergency shock-proof knowledge, improve the abilities of emergency risk avoidance, self-help and self-protection and change adaptability when the earthquake disaster occurs.

The invention provides a prediction method based on a knowledge map and a complex network combination. The method comprises the following steps: acquiring a plurality of software fault cases of different types; anyalzing Multiple fault phenomena and fault causes in fault cases by clustering analysis. The key words of phenomenon clustering and cause clustering are extracted as clustering labels ofeach category to generate knowledge map. Wherein Clustering labels are respectively corresponding to a plurality of functional modules of the software; Acquiring a mapping relationship between each functional module and the software code; Setting up code network; mapping The functional modules corresponding to the clustering label to the code network under each version, and the corresponding codepart is marked to predict the location of the code network risk of the unknown version software. The invention can effectively mark the specific software fault correspondence into the code network, and then predict the risk of the unknown version of the software code network, and then implement effective risk avoidance measures.

The invention discloses a credit risk assessment system and method based on weak variable data. The credit risk assessment system comprises an original data platform, a data management platform, a risk control model platform, a small bank score model, a personal qualification assessment module, an address information verification assessment module, an operator information checking assessment module and a payment consumption assessment module. The system depends on a big data intelligent analysis platform and an eagle eye decision engine risk control system independently researched and developed by our company. By combining a big data index real-time calculation function, data modeling and a risk control strategy and cooperating with a plurality of related credit agencies in the industry, the system does not depend on a central bank credit report and strong feature data; the mass weak variable feature data are analzyed, the applicant qualification is reasonably evaluated, the risk is effectively avoided, meanwhile, the client audit passing rate is increased, and the client false killing rate is reduced.

The invention provides a monitoring and warning system of water accumulation of a sunken road section and a forecasting and warning method of the monitoring and warning system. The method includes thefollowing steps: a warning road detection unit judges whether a water accumulating volume reaches a danger threshold of water accumulation, and sends warning information and the water accumulating volume to an intelligent transportation system center, and the intelligent transportation system center broadcasts the warning information and the water accumulating volume to vehicles covered by otherroad detection units. The monitoring and warning system is helpful for all departments and users to understand road situations of sunken road sections in real time in case of sudden heavy rain, so that risks are avoided as much as possible, vehicles in danger can be rescued in time and personal safety in vehicle driving is better ensured. The monitoring and warning system is in a low-frequency operating mode at ordinary times, which greatly saves resources.

The invention relates to an indicator system generation method based on an entropy weight method. Based on the safety management indicator system of the chemical enterprise, the method researches reasonable improvement and updating on the basis of the original indicator system to construct a new indicator system. The basis of improvement is that the historical chemical accident cases act as the analysis data according to the irrationality of the data reverse analysis indicator weight. The entropy weight method is not the algorithm of a large number of sample data assignment, the entropy weightmethod is adopted to evaluate the sample quality to form the sample weight, the weight of the safety indicator system is reversely analyzed and calculated on the basis of the data and the indicator weight is appropriately adjusted and updated. Reasonable and necessary modification is made according to the actual situation so that continuous improvement of enterprise safety supervision and safetyevaluation can be promoted and the risk avoidance can be better performed.

The invention discloses a method for combining logistic regression credit approval based on user data and expert features. The method comprises the steps of inputting data cleaning, carrying out datadimension reduction and preprocessing, carrying out data classification, data feature engineering and feature extraction, introducing expert features, carrying out feature prediction and outputting anapproval list. In the present invention, according to the credit approval method, expert features in a traditional financial model are combined with a classic machine learning method. The future default possibility of possible dynamic change is predicted by combining market real-time updating data and feature engineering. A prediction model and an optimized logistic regression algorithm are adopted. The complex credit constraints are met. Obtained default probability prediction and risk premium results are more accurate. Auditors can be liberated from heavy credit risk assessment auditing andpricing. The large-scale small and micro enterprise credit approval can be rapidly achieved. It is possible to guarantee intelligent rating and avoid risks.

The invention provides an enterprise risk prediction method and device, and the method comprises the steps: obtaining the basic data of an enterprise, and enabling the basic data to comprise the business registration basic information, the industry information, the legal affair information, the change information, and the legal affair information of an associated enterprise having an association relationship with the enterprise; performing structured processing on the basic data to obtain structured basic data; reading the structured basic data, carrying out missing value processing and abnormal value processing on the structured basic data, and taking the basic data subjected to the missing value processing and the abnormal value processing as a training set; using a machine learning classification algorithm to train the training set to obtain a prediction model; in the prediction stage, acquiring basic data of the to-be-predicted enterprise, and inputting the basic data of the to-be-predicted enterprise into the prediction model to obtain a risk probability of the to-be-predicted enterprise. The enterprise risk is automatically predicted, the enterprise is helped to measure and avoid the risk, and the viability of the enterprise is improved.

The invention relates to an earthquake fire indoor risk-avoidance self-rescue device and a method thereof which can provide a risk-avoidance self-rescue chance for people who are trapped in a house and are difficult to escape when in a heavy earthquake or a fire disaster. The device and the method comprise an arc-shaped steel plate which has a rotary fan, a storage device and an upright column atboth sides, and an arc-shaped steel plate which has a rotary fan at one side, and a pothook, an upright column and a protection fastener at the other side; a steel pipe which has a screw hole in the middle and a steel column inserted into each end penetrates the arc-shaped steel plate; another steel column and the arc-shaped steel plate which has a rotary fan at one side, and a pothook and a protection fastener at the other side constitute a risk-avoidance space which can be stretched and retracted; the device and the method are provided with a battery, a light bulb, an alarm, a high-pressurepump, etc. When heavy earthquake happens, a steel ball and a spring, a steel wire and a vibrator cause the light to turn on due to the shake, and lead the alarm to give an alarm and to stretch the risk-avoidance space, then people can avoid risk, survive by water, food and paper, and can realize self-rescue by using the high-pressure pump to remove the steel column after enter the risk-avoidance space; when in a fire disaster, people can use water and respirator to protect the body and escape after entering the risk-avoidance space. The device and the method solve the problem that people can not escape and are smashed or burned to death since the houses are ruined and knocked down in a heavy earthquake and a fire disaster, which can be widely used for the human body safety protection in the house when in the heavy earthquake and the fire disaster.

The invention relates to an anti-fraud and credit risk prediction method and system based on an association network. The method comprises: determining whether a tested user is a fraud user listed in ablacklist or not; if the tested user is not the fraudulent user, obtaining a relationship group having data interaction with the tested user, and constructing an association network through the relationship group; and analyzing node objects in the association network, and determining a credit score of the tested user so as to carry out risk early warning. According to the method, the credit scoreof the tested user can be determined more accurately by constructing the association network of the tested user and predicting the credit risk of the tested user through the association network, theprediction accuracy is improved, risk early warning is carried out when the credit score does not reach the standard, risk avoidance is facilitated, and the economic benefits of banks and other financial institutions are ensured.

The invention relates to a road surface water depth detecting method and device and a vehicle. The method comprises the following steps: when the vehicle wades into water, acquiring a distance measurement signal transmitted by a radar mounted on the vehicle, wherein the distance measurement signal comprises distance measurement information for at least one target point on a road surface; acquiringvehicle inclination information and vehicle underwater penetration information; and determining water depth at the position of at least one target point on the road surface according to the distancemeasurement information of at least one target point on the road surface, the vehicle inclination information and the vehicle underwater penetration information. The target point can be an optional expected detection position point, can be a position point located on the road surface in front of the radar, and can also be a position point on a vertical downward road surface of the radar. Therefore, the vehicle not only can acquire current underwater penetration and current road surface water depth, but also can acquire the water depth of the road surface in front of the vehicle, and thus can provide accurate and reliable data support for determination of a follow-up running strategy and risk avoidance.

A system and method for directing and monitoring the whereabouts of persons within an environmentally hazardous area includes equipping each person with devices for monitoring personal physiological conditions (56), equipment conditions (64), topographical locations (34), environmental conditions (57) and other pertinent data. The data are individually encoded and uploaded to a processing center (36) where they are analyzed (58,60,61) in order to ensure compliance with health or environmental norms and safety regulations, generate hot-spot mapping (53) and to issue real-time risk avoidance behavior directives (62), worker, mechanism and material traffic directions, warnings (59), permissions or interdictions.

A method for drive assistant comprises the following steps of detecting whether the driver's effective response information is received within a predetermined time period during driving; detecting a safety index of the current environment if the driver's effective response information is not received within the first predetermined time period; executing a preset tolerable error command if the safety index of the current environment is greater than a predetermined value; and executing corresponding risk avoidance processing if the driver's intervention command is not received within the secondpredetermined time period after executing the error driving command. Through the layer-by-layer detection of attention concentration, it is possible to detect the driver's inattention state more timely and accurately, and improve the safety of automatic driving or assisted driving.

The invention discloses an SDK safety detection method for IOS. The method comprises the steps of SDK starting, SDK automatic detecting, re-signature detecting, dynamic library injection detecting, debugger injection detecting and anti-debugging detecting. According to the method, the SDK is called through an interface, safety analysis is conducted on the running environment of an IOS applicationat a certain timing or scenario after the IOS application is started to avoid risk, detection conducted on the safety of the IOS application by using the SDK is more comprehensive compared with the prior art and the protecting means of other applications on the market, the self protection level of the SDK is higher, core detection functions are obscurer and do not easily avoid by hook, and therefore the protection level on the application is greatly improved.

The invention relates to a power grid communication service oriented communication risk early warning and risk avoidance method. The method comprises a communication risk early warning process and a risk avoidance process; the communication risk early warning process comprises following steps: carrying out risk parameter quantified assignment to optical communication devices and optical channels; setting service weights according to the importance degrees of the borne power grid communication services; and determining the risk probabilities of the communication risks of the services. The risk avoidance process comprises following steps: with respect to the service communication channels which have relatively high communication risk probability values and need route optimization, carrying out priority sorting to the service communication channels according to risk existing degrees; constructing a delay information matrix list; and searching new service routes to the services which have risks and need the route optimization. According to the method of the invention, timely and effectively early warning is carried out to the communication risk probabilities in the power service; automatic route optimization is carried out to the service channels with the communication risks; and the interruption risks in the power grid services are avoided timely.

The invention discloses a dispatching method and system for an energy center in an industrial park. The method comprises: establishing an optimized operation model inside an energy center in an industrial park under a deterministic parameter and carrying out calculation to obtain an operation cost; according to the operation model, establishing a robust model and an opportunity model of thermal load uncertainty and electric load uncertainty by using an IGDT; on the basis of an inputted equipment thermal load parameter, an inputted equipment electric load parameter, and a controllable load parameter as well as the operation cost and operation cost range information, solving a robust model and an opportunity model respectively by using a CPLEX solver, thereby obtaining a robust dispatching method and an opportunity dispatching method; on the basis of the robust model, obtaining a robust dispatching strategy for resisting thermal load and electric load fluctuation; and on the basis of the opportunity model, obtaining an opportunity dispatching strategy for having an opportunity to obtain better operation costs. Therefore, a reference is provided for a risk avoidance type decision maker and a risk preference type decision maker.

The invention discloses a securities investment risk assessment and pre-warning system, which comprises a user side and a service platform, wherein the user side performs data communication with the service platform through the internet, and the service platform comprises an identification module, a data base module, a data transmission module, a transaction processing module, a transaction analyzing module and a transaction pre-warning module; the user side logs in the service platform through the identification module, the user side and the service platform perform data exchange through the data transmission module, and the transaction processing module, the transaction analyzing module and the transaction pre-warning module are communicated. By means of the method, the securities investment risk assessment and pre-warning system can perform comprehensive and accurate price assessment on investment risk and pre-warn investors to effectively avoid risks.

The present invention provides a monitoring data processing method for landslide and a landslide forecasting method, and relates to the field of disaster warning. Monitoring points are arranged at a pre-monitoring area, features of charged particle escaping from the surfaces of the monitoring points are monitored to obtain the measurement data related to the charged particle escaping from the surfaces and perform statistics of the measurement data, a statistics value is obtained according to a statistics result, the current statistics value is compared to a statistics value before, and the forecasting of the landslide is achieved according to the fluctuation showing the change of the measurement data obtained according to a comparison result. The forecasting of the landslide is creativelyperformed based on the features of overflowing charge particles of the surfaces to achieve the forecasting of the landslide is achieved of the pre-monitoring region in a lossless mode while improvingthe prediction precision. The forecasting is provided for the regions with the landslide forecast to occur to allow people around the pre-monitoring region to start to adopt risk avoidance measures soas to reduce the personnel casualties and property loss of the broad masses of the people.

The invention belongs to the electric power field and relates to a two-stage stochastic planning-based virtual power plant risk avoidance optimization operation method. With profit maximization adopted as an objective, a day-ahead market stage and an actual market stage are obtained through division; a virtual power plant optimization operation model is established according to risks brought about by the uncertainty of the electricity price, wind power generated output and photovoltaic power generated output of a day-ahead market; virtual power plant optimization operation problems are researched under different situations of the electricity price, wind power generated output and photovoltaic power generated output of the day-ahead market; and an objective function is divided into three parts, namely, benefits, cost and risk planning. With the method adapted, a basis can be provided for the purchase and sell of electricity in the day-ahead market and an electric power and energy balance market for a virtual power plant operator; retailers can adjust the operating situation of different equipment of the virtual power plant, electricity sell and purchase sources according to the electricity price of the day-ahead market and renewable energy output, so as to maximize their own interests; and energy conservation and emission reduction can be realized with the interests of the virtual power plant operator ensured.

The invention discloses a science and technology listed enterprise financial risk early warning method under a limited information condition, and belongs to the technical field of financial risk research and information scientific cross fusion. The method comprises the steps of firstly, constructing a financial risk index system based on the science and technology type listed enterprise, determining the index weights of all indexes fused with subjective and objective information in combination with data information and expert experience, and adopting the subjective and objective fused index weights to relatively objectively and comprehensively quantify the financial risk of the science and technology type listed enterprise at a certain time point; and finally, constructing a science and technology listed enterprise financial risk self-adaptive early warning threshold value by using the financial index data, and dividing the dynamic early warning interval to realize the quantification and early warning of the financial risk, thereby providing more detailed and effective early warning judgment basis for the decision-making level of the science and technology listed enterprise, and providing the theoretical support for early warning and risk avoidance for the science and technology listed enterprise to find the risk as early as possible.

The invention provides a bank debt risk detection system based on WEB. The system comprises: a WEB client-side unit used to input the debt data information which at least includes the customer code through a WEB page as well as generate and send a detection request; a risk exposure detection unit used to calculate the debt risk exposure according to the debt data information; an expected recovery amount detection unit used to calculate the total of the expected recovery amount of the debt; a risk coefficient detection unit used to calculate the debt risk coefficient; an expected recovery rate detection unit used to calculate the expected recovery rate of the debt according to the debt risk exposure, the total of the expected recovery amount of the debt and the debt risk coefficient, wherein, the debt expected recovery rate is equal to (the total of the expected recovery amount of the debt / the debt risk exposure) x the debt risk adjustment coefficient; a breach loss rate detection unit used to calculate the debt breach loss rate according to the debt expected recovery rate further to detect the bank debt risk. The bank debt risk detection system and the bank debt risk detection method based on WEB of the invention can quantitatively control the credit risk of the bank to reduce loss and avoid risk.

The invention discloses a risk avoidance method for electric power retailers to participate in balance market transaction. The method comprises the following steps: S1, respectively acquiring time sequences of electric power retailers' market bidding electric quantity curves in the day-ahead and real-time market electric quantity purchasing curves, and calculating to obtain an unbalanced electricquantity residual error sequence; S2, measuring the discrete degree of the unbalanced electric quantity residual error sequence by using the information entropy, and establishing a risk avoidance degree index; S3, establishing a multi-target risk avoidance model with the maximum power retailer operation income, user demand response satisfaction and risk avoidance degree; and S4, taking the controllable load of the user side as a balance resource to participate in the market transaction, and carrying out optimization control on the balance resource through the multi-target risk avoidance modelto enable the power retailer to avoid the transaction risk. The method provided by the invention is simple in implementation process, and can effectively reduce the risk of the electric power retailerparticipating in the balance market transaction.

The invention provides a risk detection method and device based on big data, an apparatus, and a readable storage medium. In the course of credit risk analysis, according to the need of risk control,we can get the requester information of the loan requester, and then establish the relationship between the requester information and other information in the way of relationship, so that the isolatedrequester information can be integrated with other information to form the information association map (information association network); Combined with the black (or gray) processing logic to detectthe credit risk, so as to detect the loan terminal of loan applicant by the way of big data analysis, improve the accuracy of credit risk detection, can more effectively carry out early warning of potential risks, can find and avoid risks and reduce the bad debt rate of loan as soon as possible.

A risk assessment system and method. A system is provided that includes: a risk avoidance process for implementing a customer solution, wherein the risk avoidance process includes markers where a risk is assessed; a system for assigning a value to a first risk coefficient associated with a design related process at each of a plurality of the markers; a system for assigning a value to a second risk coefficient associated based on a customer ability at each of a plurality of the markers; and a system for assigning a value to a third risk coefficient for the entire risk avoidance process based on a customer history.

The invention provides a park green space disaster prevention and risk avoidance capability evaluation method and system, and the method comprises the steps: obtaining the image data information of apark green space system, extracting the target park green space data from the image data information, and obtaining the historical disaster data of a target park green space; screening each evaluationindex of the disaster prevention and risk avoidance capabilities of the target park green land according to the target park green land data, and determining the comprehensive weight of each evaluation index; and according to the historical disaster data, each evaluation index and the comprehensive weight of each evaluation index, evaluating the disaster prevention and risk avoidance capability ofthe target park greenbelt, and generating an evaluation result. Through implementation of the invention, a unified evaluation standard is provided for disaster prevention and risk avoidance capabilities of park greenbelts; the evaluation result can visually reflect the disaster prevention and risk avoidance capability of the park green space, provides a theoretical basis for urban park green space disaster prevention planning, and has important significance for reinforcing the protection and development of park green space landscape resources, optimizing the disaster prevention capability ofan urban green space system, consolidating the stability of the green space system and the like.