186results about How to "Accurate forecast" patented technology

Systems and methods are described for scoring consumers' credit risk by determining consumers' income risk and future ability to pay. Methods are provided for measuring consumers' income risk by analyzing consumers' income loss risk, income reduction risk, probability of continuance of income, and economy's impact on consumers' income. In one embodiment, a method is provided to evaluate an individual's creditworthiness using income risk based credit score thereby providing creditors, lenders, marketers, and companies with deeper, new insights into consumer's credit risk and repayment potential. By predicting consumers' income risk and the associated creditworthiness the present invention increases the accuracy and reliability of consumers' credit risk assessments, results in more predictive and precise consumer credit scoring, and offers a new method of rendering a forward-looking appraisal of an individual's ability to repay a debt or the ability to pay for products and services.

The invention relates to an energy storing method and apparatus for use by end-users of energy, such as commercial property owners and operators. The system differs from past systems, insofar as it is not intended to be used by and in connection with energy suppliers, such as large utility and power supply plants and grids. The system preferably relates to the manner in which an end-user of energy can implement energy and costs savings, by using energy storage and time-shifting methods, to control and regulate the consumption of energy in a manner that achieves a cost savings over a period of time. One aspect of the method relates to accurately forecasting and predicting the energy demands and peaks that might occur on a daily basis, by recording and analyzing the prior day's history, as well as the overall energy demand histories, using short and long term forecasts, and then setting up a variable energy storage/use plan or schedule that helps to reduce the peak demands by time-shifting the energy that is used, i.e., reducing consumption during high demand/high cost periods, and using the energy stored during low demand/low cost periods during the high demand/high cost periods.

The invention relates to a strip steel quality forecasting, furnace condition early-warning and fault diagnosis method, in particular to a strip steel quality forecasting, furnace condition early-warning and fault diagnosis method based on partial least square, comprising the following steps: model selection: multiple models are adopted to describe the process characteristics of corresponding steel types; data preprocessing: data alignment based on the model is carried out, synchronization relation of process input and quality output is built and data dimensionless treatment is carried out to eliminate effect of process data on modeling precision owning to non-unity of physical units; an off-line model building; a PLS (partial least square) model for strip steel quality and process variable is built by utilizing a great amount of historical data in normal working conditions; determining control limit of an monitor-control index; determining variable quantity control limit; and on-line forecasting and on-line detection and fault diagnosis. In the invention, the model for the strip steel quality and the process variable is built by PLS algorithm, so as to realize real-time quality forecasting, process monitoring and fault diagnosis.

The invention discloses a device for breakout prediction during slab continuous casting. At least four rows of thermocouples are arranged on a continuous casting mould from a meniscus of the mould to a mould outlet in an array mode, wherein all the thermocouples are connected to a computing control unit; and the computing control unit computes the temperature distribution state of molten steel in the mould according to temperature information of the thermocouples to determine whether a breakout alarm is needed. The invention also discloses a method for realizing the breakout prediction during the slab continuous casting by the device, which comprises the steps that: the computing control unit acquires the temperature information of the thermocouples and establishes a mathematical model for a temperature field of the mould; and when the distance from the position of the maximum temperature of the molten steel in the mould to the height of the mould outlet is less than a preset threshold value, the computing control unit sends out the breakout alarm. Through the device and the method, the alarm can be immediately sent before the occurrence of the breakout and breakout accidents can be avoided.

The invention discloses a method for electrically forecasting a danger in underground tunneling engineering, which comprises: building an approximately even current field in the direction of a tunnel or a laneway by burying long-distance fixed-source first and second power supply electrodes underground in the direction of the tunnel and the laneway; measuring and recording current field change under the background of the approximately even current field by using a measuring electrode buried in tunnel heading face of the laneway and a measuring electrode arranged in or outside the tunnel; and predicating and forecasting a danger around the tunnel heading face according to a law for the change of the electric field. The method has the advantages that: an electrical instrument can be placed in ground station for observation; intra-laneway power supply is avoided; the arrangement of the electrodes is convenient; and the early warning and forecasting cost is low. The method can be widely used in the field of projections involving laneway or tunnel construction, such as coal mine, mine production, communication, water conservancy and hydropower and subway projections.

The invention relates to a three dimensional laser scanning-GPS-combined side slope monitoring method. The monitoring method is characterized in that a three dimensional laser scanner system and a GPS monitoring positioning system are combined and are used for accurate monitoring of side slope geologic hazard. The method can accurately detect and forecast mine side slope geologic hazard, improve side slope monitoring intelligence and prediction effects, realize real-time monitoring of side slope deformation, accurate prediction of side slope deformation trend and precaution of geologic hazards such as side slope displacement and falling and guarantee mine production safety.

The present invention provides a forecast method of the bus arrival time of a digital public transportation system that comprises at least one on-board information device mounted on a bus, at least one electronic bus station and an information management system. The forecast method of the bus arrival time includes three steps. Firstly, the electronic bus station sends bus arrival information to the information management system via a wireless communication network; secondly, after successfully obtaining the bus arrival information, the data processing unit of the information management system processes the bus arrival information; finally, the estimated time when the bus arrives every electronic bus station ahead is calculated, and arrival forecast information is generated and then sent to every electronic bus station ahead for display via the wireless communication network. The present invention combines the data of realtime road condition and historic statistics and dynamically obtains the time needed for an operating bus to reach every station, thus accurately forecasting the arrival time.

The invention provides a pod propelling system testing device which comprises a motor. An output rotary shaft of the motor is fixedly connected with a main shaft, the end of the main shaft is connected with a commutator, output shafts at the two ends of the commutator are fixedly connected with cross shafts respectively fixed with a propeller, thrust and torque sensors used for measuring axial thrust and torque of the propeller are arranged on the cross shafts respectively, the thrust and torque sensors are connected with signal line sliding rings, and the signal line sliding rings transmit values measured by the thrust and torque sensors out. The pod propelling system testing device is suitable for performance study and matching tests of propellers and pods of multiple types, a series of performance of a pod propeller can be forecast more accurately, and the device is of great significance for performance optimization of the pod propeller and ship trials.

The invention discloses a Bohai sea spilled-oil transporting and extension value forecasting system.The system can conduct forecasting on a transporting trajectory of an oil film, an extended range, the oil film thickness, the oil-passing-through area, the time for spilled-oil for reaching a shore or a sensitive area and the like after oil spilling occurs on a point source and a continuous source in Bohai sea area, and a forecasting result can be displayed on a computer screen visually and dynamically.Oil spill emergency action modes, types and number of vessels and situations of laying oil fences or using oil dispersant or the like are selected according to the forecasting result, oil spill damage is relieved or eliminated, and disaster prevention and reduction are achieved.Back tracking is conducted on the source of spilled oil in the Bohai sea area by combining with finger prints and satellite remote sensing, the source of the spilled oil on the sea is found out, and therefore a troublemaker is determined.

The invention provides a grain condition alarm system. The system comprises a plurality of temperature sensors, a storage unit, an analysis unit and an alarm unit, wherein the temperature sensors are used for detecting the temperature of each position in the grain bulk; the storage unit is used for storing the detection position and time of each temperature sensor and the data of the detection temperature at the detection time; the analysis unit comprises a calculation module and a temperature difference comparison module; the calculation module is used for calculating the pre-detected temperature and the temperature difference between the actually detected temperature and the pre-detected temperature; the temperature difference comparison module is used for comparing the temperature difference with the temperature difference threshold in each detection position; the analysis unit also comprises a temperature comparison module; the temperature comparison module is used for comparing the actually detected temperature value with the temperature threshold in each detection position; when the temperature difference is not less than the temperature difference threshold or when the temperature difference is not less than the temperature difference threshold and the actually detected temperature is not less than the temperature threshold, the analysis unit sends out unsafety state information; and the alarm unit gives an alarm after receiving the unsafety state information. The invention also provides a grain condition control system and a grain bulk safety state discrimination method.

The invention relates to the technical field of geological disaster monitoring, in particular to a mine side slope deformation monitoring and early warning system and an early warning method thereof. The early warning system is composed of a ground control subsystem, a space wireless communication network and a communication auxiliary subsystem of monitoring workers, wherein the ground control subsystem, the space wireless communication network and the communication auxiliary subsystem are used for carrying out communication connection. The ground control subsystem is composed of a GPS mine side slope monitoring subsystem and a GPS monitoring data processing subsystem. The GPS monitoring mine side slope subsystem comprises a set of displacement measuring robots, a receiving antenna, a data transmission module, a GPS receiver and a power supply system, wherein the GPS receiver is used for receiving mine side slope deformation data collected by the displacement measuring robots. Various data are collected in real time, the monitoring data are processed, and the uploaded data are fast and automatically stored, transmitted, updated, counted and managed. The mine side slope deformation monitoring and early warning system has the advantages that the mine side slope displacement is dynamically monitored in real time, and safety production of a mine is guaranteed.

The invention discloses a global earthquake geomagnetic anomaly big data monitoring and early warning system and a monitoring and early warning method based on a mobile Internet. The system provided by the invention comprises a mobile terminal. The mobile terminal is in bidirectional connection with an intermediate layer. The intermediate layer is in bidirectional connection with a main control cloud end. The intermediate layer comprises a distributed cloud computation unit, a distributed mass storage unit, an automatic structured distribution unit and a data filtering unit. The main control cloud end comprises a comprehensive analysis unit, a decision-making unit and a management subsystem. The global earthquake geomagnetic anomaly big data monitoring and early warning method based on the mobile Internet is characterized in that the mobile Internet is used to collect data collected by an intelligent mobile phone or a tablet personal computer, the main control cloud end is used to analyze the data, and a magnetic field abnormal value is obtained and fed back to the intelligent mobile phone or the tablet personal computer for visually displaying a magnetic field abnormity distribution state. Through the analysis of the main control cloud end, a user is enabled to obtain data of great reference value.

The present invention discloses a heavy pollution sequence case base-based region heavy pollution discriminating and prediction method and device and belongs to the atmospheric heavy pollution prediction technical field. The heavy pollution sequence case base-based region heavy pollution discriminating and prediction method includes the following steps that: a historical heavy pollution sequence case base of a target region is established according to collected pollution index data and meteorological element data monitored by each monitoring site of the target region, sequences in the case base are composed of meteorological element data; on the basis of the predicted meteorological element data of the target region in a certain future period, the sequence of the future period is obtained; and similarity comparison is performed on the sequence of the future period and the sequences in the historical heavy pollution sequence case base, so that the heavy pollution condition of the target region in the future period can be discriminated. With the heavy pollution sequence case base-based region heavy pollution discriminating and prediction method and device of the invention adopted, the accuracy of the prediction of the heavy pollution of the target region in a selected future period can be improved; and the accuracy of the prediction is high.

The invention discloses a system and method for remote control coal mine evacuation working face advance detection and forecasting, which comprises a remote control system, a firing device, a blasting excitation system, a blasting receiving system and an anti-explosion geological advance detector host, and is characterized in that the remote control system comprises an anti-explosion computer, a remote controller master computer and a remote control slave computer; the anti-explosion computer and the remote control master computer are connected to realize duplex communication; the remote controller master computer is connected with the remote controller slave computer point to point through a cable; the remote controller slave computer is connected with the anti-explosion geological advance detector master computer to realize duplex communication; the remote control coal mine evacuation working face advance detection and forecasting system also comprises a synchronous signal detectionbox; and the output end of the firing device is connected with the synchronous signal detection box, the firing device outputs excitation signals to the blasting excitation system through the synchronous signal detection box, thereby preventing an operator from harm.

The invention provides a grain condition prediction system that comprises a plurality of temperature sensors, a storage unit, an analysis unit and an alarm unit, wherein the temperature sensors detect the temperature of all positions in a grain bulk; the storage unit is used for storing the current detection data and the historical detection data; the analysis unit comprises a calculation module and a temperature change rate comparison module; the calculation module calculates the following parameters at each detecting position: practical temperature change rate, prediction temperature, prediction temperature change rate and the temperature change rate difference between the practical temperature change rate and the prediction temperature change rate; the temperature change rate comparison module is used for comparing the temperature change rate difference at each detection position with the temperature change rate difference threshold of the detection position; the analysis unit alsocomprises a temperature comparison module that is used for comparing the currently practical detection temperature value with the temperature threshold at each detection position; and an alarm can begiven under the alarm condition of whether the temperature change rate difference is more than or equal to the temperature change rate difference threshold at the detection position and whether the currently practical detection temperature value is more than or equal to the temperature threshold at the detection position.

The invention relates to a method of supplementarily forecasting the steelmaking finishing point of a converter, belonging to the field of ferrous metallurgy. The method comprises the steps of: aiming at small and medium converters without dynamic detection equipment, calculating the addition quantity and oxygen consumption of auxiliary materials by an industrial control computer and a process database according to the initial converter blowing metal filling information and the target carbon content and temperature of molten steel at the finishing point; calculating the carbon content and temperature of a blowing process molten pool in real time according to the blowing process information; and calculating the content of Mn, P and S in the molten steel when the blowing achieves the finishing point. The method is applied in production practice of 80t converters, and test results show that the forecasting values on the compositions and temperature of the molten steel at the steelmaking finishing point of the converter by adopting the method are close to the practical value, an operator can be assisted for accurately controlling the steelmaking finishing point of the converter, thereby continuously improving the steelmaking finishing point control level of the converter.

The invention relates to a medium-long term forecasting method for wind power, which is characterized by comprising the following steps of: (1) collecting global large-scale meteorology forecasting field data, and providing an initial field and side boundary condition of 7 days for a WRF (Weather Research Forecast) mode; collecting topography, vegetation and sea temperature data for providing underlying surface information for the WRF mode; (2) building the WRF mode to calculate meteorology field information; (3) inputting the large-scale meteorology forecasting field data collected in the step (1) and the underlying surface information into the WRF model to obtain the wind direction and the wind speed forecasting data within the wind field range; and (4) solving the output power of each fan according to the forecasted wind speed by a fan power curve, and accumulating to obtain the total output power of the wind field. The medium-long term forecasting method can accurately forecast the wind power in future 7 days in the WRF mode, has long forecasting time, operation stability, flexible forecasting scheme and few limitation conditions, and does not need the historical operation data of the wind field.

The invention relates to multifunctional seismic detection and predicting device. It sets network type multifunctional detecting well and sonar tube in lithosphere to detect its sound signal and seismic signal while breaking, uses vertical deformation of the laser detecting multifunctional detecting well to calculate its horizontal stress change by function calculating, combines satellite observation for ground change and magnetic variation to observe and analyze natural environment in earthquake, before and after. Thus it can exactly predict by the numbers for the crust lithosphere change and the becoming earthquake.

The invention discloses a new method for surveying population density of microarthropods such as panonychus citri mcgregor, predatory mites and diaphorina citri kuwayama. The new method comprises the following steps of: randomly drawing a citrus sample plant; placing adhesive plate boxes below tree crowns in the east, south, west and north directions of the tree crown of the citrus sample plant; knocking branches of the tree crowns above the positions where the adhesive plate boxes are arranged for many times to drop the microarthropods; adhering the microarthropods falling in the adhesive plate boxes to adhesive plates of the adhesive plate boxes; collecting the adhesive plate boxes to perform statistical survey, wherein the adhesive plate boxes comprise box bodies; a layer of plate corresponding to the size of the bottom surface is arranged on the bottom surface of each box body; an adhesive material is coated on the upper surface of the plate; and thus, the adhesive plates are constructed. Thus, by surveying with the method provided by the invention, the used time is less, the sample can be stored for a long time, and most importantly, the detection sensitivity to the microarthropods of red spiders, predatory mites and the like is greatly improved; and since the detected objects are adhered and cannot escape, the detection is more convenient, simpler and more accurate.

The embodiment of the invention discloses a method and device for optimizing numerical weather forecast through assimilated inversion of water vapor content. The method comprises: calculating the layered water vapor content of each atmospheric layer through inversion according to the radiance received by an observation satellite and generated by ground radiation, optimizing the initial field of the numerical weather forecast mode according to the calculated layered water vapor content of each atmospheric layer to obtain an optimized initial field, and carrying out new weather forecast throughthe optimized initial field. The optimized initial field considers the influence of water vapor in the atmosphere on the field, so that the weather forecast of the optimized initial field can reflectthe real weather condition more accurately compared with the weather forecast based on the original initial field. According to the method, the optimization of the initial field by combining satelliteobservation data is realized, and the weather forecast closer to the real condition can be obtained through the optimized target initial field.

The invention discloses a landslide monitoring and forecasting method with accurate forecasting result in monitoring and forecasting field of natural hazard. The method comprises the following steps: (1) performing geologic examination to the area with slop deformation; (2) establishing the ground displacement monitoring network of the slope deformable body; (3) recording the monitoring data and generating the serial data point curve of the accumulated displacement s and time t of the slope deformable body; (4) the serial data point curve being subjected to maths fitting and generating the precasting model of the accumulated displacement s and time t of the slope deformable body; (5) precasting based on the precasting model. The method not only accurately monitors the overall process of the slop deforming, but also accurately precasts the slope deformation advancing several days, even of several hours; in addition, the method has features of neatness and quickspeed and is suitable for monitoring and forecasting the slope on a great variety of topographty, geologic conditions.

The invention discloses a visual intercom indoor terminal with a security and protection function. The visual intercom indoor terminal comprises a microprocessor, a security monitoring module and a smoke detection circuit, wherein the microprocessor is connected with a visual intercom module, the security monitoring module, an emergency power supply automatic switching module, an emergency evacuation module and a communication interface respectively, the security monitoring module comprises the smoke detection circuit, a temperature detection circuit and a fuel gas leakage detection circuit, the smoke detection circuit comprises a detection passage circuit and a reference passage circuit which are respectively connected into two input ends of a differential amplification circuit I, and the output end of the differential amplification circuit I is connected with a threshold comparing circuit I in series. The visual intercom indoor terminal has the beneficial effects that on one hand, danger situations can be accurately and quickly forecast by utilizing a multi-sensor fusion technology, and on the other hand, the visual intercom indoor terminal is arranged at vantage positions close to gates or passages, when accidents happen, emergency switches are automatically switched, and trapped personnel can be emergently guided and evacuated, so that great property loss and personnel injury accidents are prevented from occurring.

The invention discloses a hail and short-time heavy rainfall forecasting method. The method comprises the following steps: acquiring ground meteorological observation station data of a certain regionfrom March to September each year before hail and short-time heavy rainfall occur and data of a plurality of sounding stations at the upstream of the region; expanding the hail process data with relatively small data volume in the data through an SMOTE oversampling algorithm to obtain an oversampled data set; carrying out dimension reduction on the oversampled data set by adopting a PCA method; dividing samples in the data set after dimension reduction into a training set and a test set; constructing a GBDT + LR model, taking features extracted from leaf nodes of the GBDT model as input features of the LR model, and training and testing the GBDT + LR model through the samples of the training set and the test set; and acquiring ground meteorological observation station data three hours before a to-be-predicted time point of the region, acquiring data of a plurality of sounding stations at the upstream of the region, substituting the data into the trained GBDT + LR model and judging whether hail or short-time heavy rainfall occurs at the predicted time point.