106 results about "Risk avoidance" patented technology

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 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 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 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 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 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 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 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 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 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.

A method is provided to avoid risk at a workplace. The method comprises establishing an indication including a first region with a first safety level at the workplace; determining a position of an object in the workplace and generating position information; and issuing a first alert if it is determined that the object is in the first region based on the position information and the indication.

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.