41results about How to "Improve accuracy and timeliness" patented technology

The invention discloses a driving working load calculation method of an automobile driver; the driving working load of the driver is represented and obtained by utilizing physiology, psychology and driving behavior of the driver; a driving working load calculation model is built by adopting main task measurement, physiology and psychology measurement, synchronous measurement of a working load self-evaluation system and selection indexes; the method comprises the following steps: a driving working load feature information detection system of the automobile driver is built; a building method of the driving working load calculation model of the automobile driver is built; by adopting the obtained driving working load information and data analysis and selection, the driving working load calculation model of the automobile driver is obtained; electro-cardio indexes are taken as representation indexes of physiology and psychology driving working load measurement; in the invention, the characteristics of the driving behavior of the driver are considered, the accuracy and promptness of the driving working load calculation of the driving working load calculation are improved; in addition, the operational method is simple and provides reference frame for road traffic safety study.

The embodiment of the invention discloses a parameter self-adaptive adjusting method and device. The parameter self-adaptive adjusting method is used for adjusting the pelletizing parameters of a pellet production system in a self-adaptive mode, improving the quality of the pelletizing quality, enabling the quality of a produced finished pellet to meet the production requirements, and saving the labor cost. The method comprises the following steps that the particle size of a green ball produced by a disc pelletizer is detected; and whether the green ball produced by the disc pelletizer meets apreset condition or not is judged based on the particle size of the green ball; and if the particle size of the green ball produced by the disc pelletizer does not meet the preset condition, the parameter adjustment strategy of the pellet production system is determined on the basis of the granularity of the green pellet.

The invention discloses a coal and gas burst risk parameter drilling and predicting integrated method. In a process of constructing and drilling a coal bed by using a drilling machine, a guide pipe is arranged in a hole opening of a drilled hole, the drilled hole is connected with a slag collector and a gas drainage pipe, a gas concentration sensor and a flow speed sensor are arranged in the gas drainage pipe, a weight sensor is arranged at the bottom of the slag collector, a counter and a torque sensor are arranged on the drilling machine; during drilling, coal dust enters into the slag collector through the guide pipe, coal dust weight information is transmitted to a multi-information sensor through the weight sensor; gas information is transmitted to the multi-information processor through the gas concentration sensor and the flow speed sensor; the torque of the drilling machine and the quantity of drilling stems are transmitted to the multi-information processor through the torque sensor and the counter on the drilling machine; and the burst risk of coal and gas in a region is predicted. The coal and gas burst risk parameter drilling and predicting integrated method provides multi-information quantity for the prediction of the burst risk of the coal and the gas, so that the accuracy of the burst risk of the coal and the gas is improved.

The invention is applicable to the field of medical apparatuses and instruments and provides a pre-hospital emergency ambulance. The pre-hospital emergency ambulance is composed of an emergency assay module, an electrocardio and ultrasonic diagnosis module, an emergency treatment module, an emergency treatment comprehensive management information system, an auxiliary module, a power module and a communication module. Through combined diagnosis and detection of the emergency treatment module, the emergency assay module and the electrocardio and ultrasonic diagnosis module, the accuracy and the timeliness of disease diagnosis are improved, unfolding time of field apparatuses can be shortened and burdens of medical workers can be reduced due to stretchers and intensive care units (ICUs), on-the-spot rescue, midway diagnosis and emergency treatment can be performed timely, the ambulance can be directly transferred to divisions for emergency treatment in hospitals so as to form a seamless treatment chain combining pre-hospital care, midway life support and rapid in-hospital treatment, the maneuverability is high, starting for immediate use is achieved, the operation is simple, the ambulance is suitable for emergency treatment and cure in the field or during transfer and capable of effectively assisting medical workers to treat and cure according to symptoms, and the emergency handling capacity and the emergency rescue capacity of emergencies are improved.

The invention provides a heat pump defrost control method, which comprises the steps of when running at a heating mode, judging whether a condition for entering a defrost mode is met or not accordingto a pressure value of a heat pump; when meeting the condition for entering the defrost mode, entering the defrost mode; when running at the defrost mode, judging whether a condition for exiting the defrost mode is met at the same time according to the pressure value of the heat pump and a coil temperature value of the heat pump; and when meeting the condition for exiting the defrost mode at the same time, exiting the defrost mode. The heat pump defrost control method provided by the invention can be used for effectively judging whether a heat pump unit meets the condition for exiting the defrost mode or not, so that the accuracy and the timeliness in defrosting are improved, and a defrosting effect of the heat pump unit is further improved.

The invention relates to a quality control method based on multiple monitoring indexes. The method mainly comprises steps that firstly, through the basic principle of a decisive tree, prediction variables are classified through utilizing control variables; secondly, a test set is calculated through utilizing the classification result, and model adjustment and optimization are carried out according to the prediction result; and lastly, the final model result is outputted and taken as a quality control standard to verify in a reverse mode whether detection samples of the multiple monitoring indexes correspond to interval ranges of a categories of the decisive tree; if the detection samples of the multiple monitoring indexes correspond to the interval ranges of the categories of the decisive tree, a value is determined to be a normal monitoring value, otherwise, the value is determined to be an abnormal value. The method is advantaged in that automatic and intelligent suspected data screening and determination and data quality analysis pre-determination functions are realized, data quality is guaranteed, and powerful support is provided for subsequent data use and environment forecast early warning.

The invention discloses a power distribution network operation monitoring method. The power distribution network operation monitoring method comprises the steps of: constructing a holographic image map of a position where a device belongs to at the key node of a power grid, and an appearance holographic image and an internal mechanism holographic image of the device; respectively integrating the appearance holographic image, the internal mechanism holographic image and the holographic image map to construct a holographic image operation monitoring system; and acquiring dynamic operation data of the device monitored by the power distribution automation system in real time, and superposing the dynamic operation data to the holographic image operation monitoring system. According to the method and the system, the perception degree of the operation monitoring personnel of the power distribution network to the device operation state and the surrounding environment can be improved, the powerdistribution network is monitored more three-dimensionally and visually, and the accuracy and the timeliness of the operation management and control decision of the power distribution network are improved.

The invention provides a floating environment monitoring device. The device comprises a buoy float, a data acquisition and transmission unit, a safety warning unit, a cloud platform and a mobile terminal, wherein the outer surface of the buoy float is a metal plate; the buoy float is filled with a foam material; a plurality of monitoring wells are symmetrically distributed along the central axis of the buoy float; the data acquisition and transmission unit comprises a water temperature sensor, a turbidity sensor, a PH sensor, an integrated control cabinet, a Beidou wireless communication module and a solar power supply module; the safety warning unit comprises a solar navigation lamp; data acquired by the monitoring device is transmitted to the cloud platform in real time through the Beidou wireless communication module; and the cloud platform is used for displaying the result on the mobile terminal in real time after finishing simple analysis of the data. The monitoring device can adapt to a severe monitoring environment in which the water level changes greatly; an external power supply is not required; real-time automatic monitoring and demonstration of various water temperatureand water quality parameters can be realized; units outside the buoy float are detachable; and convenience is brought to transportation as well as repair and replacement of parts.

The invention discloses a road condition information determination method and device, electronic equipment and a storage medium, belongs to the technical field of data processing, and further relates to technologies such as artificial intelligence, deep learning and intelligent traffic. The method comprises the steps of: determining track prediction road condition information of a to-be-predicted road section according to navigation track data of the to-be-predicted road section; determining image prediction road condition information of the to-be-predicted road section according to the road section image data of the to-be-predicted road section under the condition that it is determined that the to-be-predicted road section meets an image prediction scheduling condition; and determining target predicted road condition information of the to-be-predicted road section according to the track predicted road condition information and/or the image predicted road condition information. According to the road condition information determination method and device, the electronic equipment and the storage medium of the embodiment of the invention, the accuracy and timeliness of the road condition information can be improved, so that the user experience is improved.

The invention provides a user value prediction method and a training method of a user value prediction model. The prediction method comprises the steps of obtaining behavior characteristic data of a to-be-predicted user in a newly added period; taking the behavior characteristic data as the input of the multi-class prediction model, and obtaining the value prediction result of the multi-class prediction model; and taking the value prediction result of the multi-class prediction model as the input of the classification model, and obtaining the future value of the to-be-predicted user output bythe classification model. According to the technical scheme provided by the embodiment of the invention, the potential high-value user can be mined in time before the user becomes the high-value user,and the accuracy and timeliness of user value prediction are improved.

The invention discloses a hard disk management method and device, relates to the technical field of storage, and solves the problems that in the prior art, a service system and a storage system are independently managed, hard disk management of the storage system cannot be matched with differences of different services on storage requirements, and storage resources are wasted or the storage accessefficiency is not high. The method comprises the following steps: a service system informs a storage system of faulty hard disk input/output I/O according to an I/O access state; the storage system determines a hard disk range with a fault according to the fault information; and within the hard disk range, the storage system further locates the faulty hard disk.

The invention discloses a numerical control machining center online monitoring intelligent regulation and control management cloud system which comprises a machined workpiece numerical control machining parameter determining module, a machined workpiece numerical control machining monitoring module, a numerical control machining process regulation and control terminal and a numerical control machining effect processing terminal. In combination with the numerical control machining parameters corresponding to the machined workpiece, the machined workpiece numerical control machining monitoring module is used for monitoring the numerical control machining process of the machined workpiece and monitoring the numerical control machining effect after machining is completed, and then the machining parameters are intelligently regulated and controlled according to the machining process monitoring result; according to the numerical control machining effect monitoring result, whether the machined workpiece is machined to be qualified or not is intelligently judged, intelligent online monitoring regulation and control of the numerical control center corresponding to the machining process are achieved, and the defects that the machining deviation judgment accuracy is not high and machining deviation judgment is delayed in manual monitoring regulation and control are greatly overcome.

The invention provides a serum exosome protein marker for obstructive sleep apnea-hypopnea syndrome and application thereof, and particularly provides application of a detection reagent of the proteinmarker in preparing a kit for detecting the obstructive sleep apnea-hypopnea syndrome. The protein marker is selected from C-reactive protein, haptoglobin and fibronectin; the kit detects the concentration of a protein marker in a subject serum exosome, and compared with normal comparison, the concentration of the C-reactive protein and the concentration of the haptoglobin are increased and/or the concentration of the fibronectin is reduced in the subject serum exosome, and therefore the probability of the obstructive sleep apnea-hypopnea syndrome is indicated to be increased. The invention also provides a related kit and a detection system. The concentration change levels of the three protein markers from the serum exosome can be used for detecting the obstructive sleep apnea-hypopnea syndrome.

The invention provides a method and device for highlighting a target text in an input box, electronic equipment, a computer readable storage medium and a computer program product, and relates to the technical field of text processing, in particular to the technical field of text input. According to the implementation scheme, the method includes: based on editable attributes of a rich text container of an input box, setting the rich text container to be editable; obtaining a current character to be displayed in the input box; determining a current analysis unit, wherein the current analysis unit comprises the current character; extracting a to-be-matched text comprising the current character from the current analysis unit; and displaying a rich text style of the target text in the input box in response to a target text matched with the to-be-matched text in a preset target text lexicon, so as to highlight the target text in the input box. According to the technical scheme, the accuracy and response speed of highlighting the target text in the input box can be improved.

The invention relates to an indoor comprehensive positioning method. The method comprises the following steps: acquiring RSSI data and user authentication data within a preset time; 2, respectively calculating the RSSI data and user authentication data into position data; and 3, carrying out weighting fusion on all the position data by using a preset positioning result model in order to obtain the final positioning result of a target object. Multiple pieces of positioning information of a network terminal and a user terminal are integrated to mutually fuse different positioning technologies, so compared with individual positioning technologies, the method greatly improves the timeliness and the precision of positioning and greatly improves the indoor positioning effect without increasing the investment.

The invention discloses a direct current leakage protection method. The protection method can be applied to a grounding system, a non-grounding system, or direct-current bus grounding or a non-grounding random switching system. According to the protection method, passive detection is realized by utilizing an electromagnetic coil principle, an electric leakage fault can be rapidly detected, a faultalarm can be sent out, a fault loop can be automatically cut off, the engineering quantity is reduced, and the timeliness and the accuracy are improved; meanwhile, the method is high in reliability and can be widely popularized and applied.

The invention discloses a vehicle alarm method, a vehicle alarm device and a computer readable storage medium. According to the vehicle alarm method provided by the embodiment of the invention, underthe state that a turn light switch is invalid or closed, an alarm can still be given to turning of a vehicle, the accuracy and timeliness of the alarm are improved, and the problem that an existing turning alarm can send out turning alarm information without depending on the situation that a driver turns on a corresponding turn light or a reminding device when the vehicle turns is solved.

The invention provides a data query method and device, electronic equipment and a storage medium, and the method comprises the steps: comparing a current query item and current user identity information with a data set in a pre-established cache database, and obtaining a comparison result; if the comparison result represents that the comparison is successful, outputting a historical query result searched from the cache database; and if the comparison result represents that the comparison fails, searching a network query result from the network according to the current query item and the current user identity information, outputting the network query result, and updating the cache database according to the network query result. The method can improve the search result display efficiency; the accuracy and timeliness of data query can be improved in a weak network or even no network environment.

The invention belongs to the technical field of computers, and provides an auxiliary indoor and outdoor identification method, intelligent wearable equipment and a storage medium. The method comprisesthe steps: receiving a positioning operation instruction of a monitoring terminal, and triggering the monitored intelligent wearable equipment to carry out the positioning operation; when the positioning operation of the intelligent wearable equipment is triggered, acquiring indoor and outdoor information based on positioning and indoor and outdoor information identified based on the current environment image; and combining the indoor and outdoor information based on positioning and the indoor and outdoor information based on current environment image identification to assist the intelligentwearable equipment to identify the indoor and outdoor information. According to the scheme, the intelligent wearable equipment is triggered to carry out positioning operation, the multiple pictures ofthe current environment are continuously obtained, the indoor and outdoor information based on positioning and the indoor and outdoor information based on picture recognition are combined, the intelligent wearable equipment is assisted in recognizing the indoor and outdoor information, and the indoor and outdoor identification accuracy and timeliness are improved.

The invention relates to an automatic leakage warning device of a solar water heating system. The automatic leakage warning device comprises a solar heat collection module, a heat accumulation water tank and a collector circulating pump. The automatic leakage warning device is characterized by further comprising a first flowmeter, a second flowmeter and an intelligent alarm controller, wherein the first flowmeter and the second flowmeter are respectively arranged on a water inlet pipeline and a water return pipeline and are respectively connected with the intelligent alarm controller through a first signal wire and a second signal wire, and the intelligent alarm controller can detect and compare flow data on the first flowmeter and the second flowmeter; and the intelligent alarm controller is connected with the collector circulating pump through a third signal wire, the intelligent alarm controller can control the collector circulating pump to be started or stopped, and can give out an alarm signal. The automatic leakage warning device provided by the invention is novel in design, reliable in operation, high in intelligent degree, and can detect the leakage condition and alarm in time.

The invention provides a flow monitoring method for a network access line, and the method comprises the steps: obtaining the historical flow of the network access line in a historical time period a for a target time period, wherein the target time period comprises b target sub-time periods, and each historical time period comprises a historical sub-time period corresponding to each target sub-timeperiod; determining a flow threshold of the network access line for each target sub-period according to the historical flow of the a historical sub-periods corresponding to each target sub-period toobtain b groups of flow thresholds; monitoring the actual flow of the network access line in each target sub-period to obtain a group of actual flow for each target sub-period; and generating alarm information under the condition that the network access line is determined to be abnormal according to the m groups of actual flows and the m groups of flow thresholds for the m sub-periods. The invention further provides a flow monitoring device of the network access line, a computer system and a computer readable storage medium.

The invention is suitable for the technical field of sea fog forecasting, and provides a sea fog forecasting method, device and equipment based on a neural network and a storage medium, and the method comprises the steps: collecting ground and high-altitude live observation data sets in a forecasting region, carrying out the preprocessing of the live observation data sets, and obtaining a sea fog forecasting result according to the preprocessed live observation data sets; and the sea fog in the future preset time in the forecast area is predicted by using the pre-trained sea fog prediction model, so that the accuracy and timeliness of sea fog prediction are improved.

The invention provides an intelligent pipe network big data acquisition, analysis, early warning and positioning system and method, the system comprises a cloud server, an overground detection deviceand an underground detection device, the underground detection device comprises data detection optical fibers arranged along a pipeline, and sensor groups are arranged on the data detection optical fibers according to set positions. The data detection optical fibers are in communication connection with the cloud server through the optical fiber monitoring acquisition terminal, and the ground detection device is in communication connection with the cloud server; and the cloud server acquires and processes the detection data so as to realize detection positioning and early warning of the pipe network leakage point. The special optical fibers capable of adapting to the pipe network environment are arranged on the pipe network, real-time data collection and big data analysis are carried out onthe net-shaped pipeline, monitoring data of the pipe network are obtained, faults can be rapidly recognized and positioned, real-time early warning is achieved, and intelligent monitoring of the pipenetwork is improved.

The invention provides a rotor slip ring grounding deterioration early warning system and method, and relates to the technical field of steel production, the system comprises a connection detection system, a closing enabling system, an actual value acquisition middle end, a threshold comparison conversion system and an early warning processing output system, the connection detection system is used for connecting a left phase and a middle phase of a three-phase alternating 170V power supply; according to the invention, rotor slip ring grounding quantitative data can be dynamically collected and dynamically monitored, and early warning of rotor slip ring grounding deterioration is realized through signal conversion and signal transmission and logic processing and quantitative output of the central processing unit. The grounding deterioration of the slip ring of the rotor can be found in time, and the searching analysis and locking of accurate grounding points and grounding sources of a video acquisition system, a picture acquisition system and a manual proofreading system are combined, so that the running environment tolerance of the finish rolling motor is greatly improved; and finally, safe and stable operation of the finish rolling motor and maximization of production efficiency and production yield are realized.

The invention relates to a pre-hospital first-aid intelligent plan pushing method based on a 5G network, and the method comprises the following steps: 1, receiving illness state information transmitted from a mobile first-aid terminal through the 5G network, the illness state information comprising disease type information, at least one piece of patient chief complaint information and at least one piece of patient sign information; 2, according to the illness state information and a trained random forest plan classification model, obtaining pre-hospital first-aid plan classification number corresponding to the illness state information; 3, according to the pre-hospital emergency plan classification number, obtaining corresponding pre-hospital first-aid plan content information; and 4, sending pre-hospital first-aid plan content information to the mobile first-aid terminal by using a 5G network. The method is based on the 5G and artificial intelligence technology, the pre-hospital first-aid content is pushed to the pre-hospital first-aid medical staff in time, and the treatment capacity and efficiency of pre-hospital first-aid are improved.

The invention discloses an inter-connected merchant risk management and control method and an inter-connected merchant risk management and control system. The method comprises the steps that a first server, used for risk control recognition, of a third-party payment institution generates and sends a risk list accommodating at least one risk association merchant to a second server of an independentsoftware developer and a third server, used for risk control decision making, of the third-party payment institution; the second server clears the inter-connection merchants according to the risk list, and/or the second server reports the inter-connection merchants needing to be complained in the risk list to the third server; and the third server deletes the successfully complained inter-linkedmerchants from the risk list and cuts off payment of the inter-linked merchants in the currently effective risk list.

A terminal data intelligent acquisition method based on the Internet of Things comprises a terminal application, a data service program, a transmission trunk, a trunk monitoring program, a Spark calculation engine, a sensor terminal, an HBase database and cloud storage, and comprises the steps of data acquisition and comparison. According to one aspect disclosed by the invention, the accuracy andtimeliness of the acquired data are greatly improved by adding a comparison link of the acquired data.

The invention discloses a numerical control electric screw press screw spike molding tool, which comprises a lower die backing plate arranged on a press worktable and an upper die backing plate arranged on a press slide block. A lower step pad and a lower material-ejecting punching sleeve are installed in the lower die backing plate, a support pad is installed in the lower step pad, an adjusting pad is installed in the support pad and a lower die sleeve, and a tail punch is installed in the lower material-ejecting punching sleeve and the adjusting pad; a lower die shell is installed in the lower die sleeve, a guide die and a lower circular die are installed in the lower die shell, a hexagonal die outer sleeve is installed on the lower die sleeve, and a hexagonal die is installed in the hexagonal die outer sleeve; and an upper die sleeve is arranged below the upper die backing plate, an upper die pad and an upper punch fixing sleeve are arranged in the upper die sleeve, and a hexagonalupper punch is arranged in the upper punch fixing sleeve. The tool solves the problem of insufficient sealing height of an original tool, and also overcomes the defect of the short material withdrawaldistance of the original tool.

The invention relates to an early warning method and device for customer loss of an automobile 4S store. The method comprises the following steps: acquiring historical data of a customer, and generating a data set; constructing an initial independent variable and a dependent variable according to the historical data; performing logistic regression modeling on the initial independent variables, and screening out a plurality of final independent variables from the initial independent variables; re-establishing the logistic regression model by adopting the final independent variable to obtain an early warning model; and inputting customer data to be predicted into the early warning model for processing to obtain an early warning result. According to the scheme of the invention, deep analysis and mining are carried out according to a large amount of data which is accumulated in the store and is related to customer consumption behaviors, and the problem of single analysis dimension of a traditional means is overcome through a model method, so that the accuracy and timeliness of early warning are effectively improved.