154results about How to "Reliable data source" patented technology

The invention provides a method for collecting consumption data of users. The method is characterized by comprising the steps of: receiving a preferential request of a user, wherein the preferential request comprises a user number and a trade company code; searching a user account with the user number as an identifier in a user database of a server; searching preferential information which can be enjoyed by the user in a trade company database of the server according to the user number and the trade company code, and returning the consumption code corresponding to the preferential activity to the user; and after the user uses the consumption code to consume in the trade company, receiving the user consumption data uploaded by the trade company and updating the user database and the trade company database by the server. Correspondingly, the invention also provides a server device and system for collecting the consumption data of the users. According to the invention, the function of collecting the consumption data of the users is achieved by virtue of support of a third party, thus reliable data sources are provided for subsequent popularization, convenience for users and trade companies, analysis of user behaviors and the like.

The present invention discloses a zone area reasonable line loss prediction method based on a data mining technology. The beneficial effects of the present invention are that: the method of the present invention aims to discover the potential correlation between the zone area characteristic data and the zone area line loss by using the actual sampling data of the zone area line loss and utilizing a data mining means to process the mass data, is reliable in data source by being compared with a conventional theoretical line loss calculation method, and can reflect the on-site actual line loss status better; the algorithm flow is simple and practical, and the efficiency is higher; a multiple linear regression model is compact in structure, can reflect the influence degrees of the characteristic parameters to the zone area line loss visually, and is easy to analyze the status of a zone area of unreasonable line loss; the method is easy for software realization, and can be integrated in a line loss management system more conveniently.

The invention provides a method for three-dimensional (3D) printing of a restoring implant by bony articular surface reconstruction. First three-dimensional reconstruction of a bone articular model is performed, and then virtual restoration reconstruction of bony articular reconstruction, reversal design of a bone articular defect area restoring implant and 3D printing forming of a bone articular defect restoring implant are performed. Modeling software is utilized to copy a normal side bone articular three-dimensional model to an affected side in a sagittal plane symmetry mode, so as to obtain a complete structure reference model before the occurrence of fracture of the affected side; 3D printing pro-processing software is utilized to support and generate the model, a corresponding forming material and a quick forming process are selected to perform 3D printing, a support structure of the implant is further removed, and finally an individual bone articular reconstruction restoring implant is obtained. The individual reversal design is performed according to the symmetry morphological structure of the human body, the bony articular surface reconstruction defect restoring implant is quickly formed by combination with a 3D printing technology, not only can a bone articular defect restoring reconstruction be greatly improved, but also the design and manufacturing efficiency of the implant is effectively improved, the cost is reduced, and customized design and individual-based treatment are performed.

The invention discloses a human face recognition method based on dual data enhancement. A human face data set obtained through the dual data enhancement improves the accuracy of human face recognition. The method comprises the steps that S1, the data set is selected; S2, the data set is preprocessed; S3, primary data enhancement is performed: a generative adversarial network model based on information maximization is built, and training is completed; S4, secondary data enhancement is performed: human face samples generated in the step S3 are subjected to translation, rotation, turnover and zoom processing; and S5, human face classification is performed: the human face samples generated in the step S4 are trained and recognized by selecting a convolutional neural network model.

The invention discloses a method for extracting the width of river channels within a basin by using a digital elevation model. The method comprises the following main steps: the digital elevation model (DEM) data of the basin are extracted; the slope grids, river channel grids and confluence accumulative grids of the basin are calculated according to the digital elevation model (DEM) data of the basin; near-river channel slope grids are extracted by using the slope grids and the river channel grids; near-river channel confluence accumulative grids are extracted by using the confluence accumulative grids and the river channel grids; moving average calculation is performed on the basis of the near-river channel slope grids, so that moving averaged near-river channel slope grids can be obtained; and the width of the river channels within the basin is extracted on the basis of the near-river channel confluence accumulative grids and the moving averaged near-river channel slope grids. The method of the invention has the advantages of stable and reliable data sources, high calculation efficiency, objective and reasonable results and the like. With the method adopted, the rapid calculation and extraction of the width of the river channels within the basin can be benefitted.

The invention discloses a parallel feature extraction system and method for general specific voice in a voice signal. A model mainly comprises a voice signal, an emotion recognition model, a voiceprint recognition model and a voice recognition model. Output features obtained by an LLD channel are combined with output features obtained by a spectrogram and a TEO channel to obtain 1*1024-dimensionalemotion features; the spectrogram is fed into a convolutional neural network CNN as an input, the spectrogram and MFCC are fed into Seq2Seq, the models of the two channels are fused and an attentionmechanism is add to form a voiceprint recognition model; 42-dimensional MFCC is adopted as input, and output is carried out in combination with a BIMLSTM channel and a Seq2Seq channel; the spectrogramis combined with a Seq2Seq channel for outputting; and the models of the two channels are fused and an attention mechanism is added to form a voice recognition model. The method has the advantages ofhigh accuracy, high integration level, capability of freely selecting schemes and the like.

Provided is a high voltage circuit breaker self-diagnosis method based on abnormal sample identification, comprising: (1) collecting high voltage circuit breaker current characteristic data through high voltage circuit breaker manufacturers, Jiangsu province maintenance departments, etc.; (2) initializing a storage area (including a real time database, a distinguishable area and an undistinguishable area) of a self-diagnosis model; (3) setting self-diagnosis model correlated parameters of following modules: a PSO optimization module, a KFCM identification module, etc.; (4) placing an initial training data set in the distinguishable area of the self-diagnosis model, adding KFCM clustering results based on the initial training data set into the real time database, and accordingly the PSO optimization module calculating the initial parameter of an SVDD detection module; and (5) the self-diagnosis model performing circular operation to process test samples, processing types comprising: distinguishable sample processing, undistinguishable sample processing and new fault type appearance processing. The method can effectively clarify and summarize current data of a high voltage circuit breaker, and provide a more scientific basis for management of electric power maintenance departments, and production and improvement of high voltage electrical equipment manufacturers.

The invention provides an indoor position service-oriented navigation network construction method, which comprises the following steps of S1, importing a BIM building model in a target building IFC format, and obtaining an original model capable of being applied to indoor position service through three-dimensional visualization; S2, extracting semantic information in IFC through semantic filtering, and constructing an ontology model in a formalized mode; S3, in the form of a dual graph, converting the topological relation in the original model into a graph model; S4, extracting geometric information of structural components such as rooms, columns, walls and stairs and indoor facilities such as furniture in the BIM model, constructing constraint boundaries, performing spatial subdivision through a limited Delaunay triangulation refinement algorithm, and constructing a geometric network model; and S5, integrating the ontology model, the graph model and the geometric model data to form anavigation network for indoor position service. Based on BIM model data, a dual model is established by extracting semantic information, geometric information and a topological relation, and a construction method considering a real indoor environment navigation geometric network is explored.

A positioning method for a super-large gear laser tracking in-situ measurement system belongs to the technical field of precision measurement. Based on the positioning method, different measurement spaces are divided and different stations are arranged first according to global geometric features of different gears. During positioning, a plurality of to-be-measured points are arranged in a measurement area, and usually, modeling of a large gear requires acquisition of measurement data of the upper end face and the addendum circle of the gear. A laser tracker carries out measurement outside the area of the to-be-measured points, and the laser tracker is sequentially moved to acquire three-dimension coordinate values of the to-be-measured points of different stations. In order to unify the coordinate values of the to-be-measured points of different stations, a reference station needs to be selected to unify coordinates of other stations to the reference station. Finally, optimization calculation is carried out with the use of redundant data provided by the multiple stations to obtain coordinate correction values of the to-be-measured points, thus providing a reliable data source for building a gear coordinate model and improving the accuracy of gear positioning.

The invention relates to a Beidou continuously operating reference station (CORS) compatible bus precise positioning system. The Beidou continuously operating reference station (CORS) compatible bus precise positioning system includes a Beidou CORS compatible bus precise positioning terminal, a CORS positioning system, a communication service center and a bus background management system; the Beidou CORS compatible bus precise positioning terminal includes a CPU module, a power source module, a Beidou/GPS dual-mode positioning module, an inertial navigation positioning module, a 3G/4G communication module, a touch screen display module and a storage module; and the CORS positioning system includes a base station, a data processing center and a communication gateway 1. According to the Beidou continuously operating reference station (CORS) compatible bus precise positioning system of the invention, the GPS and the CORS are combined together, and therefore, the effectiveness and integrity of the system can be improved; the defect of incapability of performing position when a bus enters a GPS blind area can be eliminated, and vehicle real-time accurate positioning can be realized, and positioning accuracy can reach a centimeter level; accurate positioning data which are obtained in real time are transmitted to a background management center so as to be stored, and therefore, reliable data can be provided for the generation of bus roads.

The invention provides a method for calculating geomorphologic unit hydrograph initial probability through a digital elevation model. The method includes the following main steps that drainage basin digital elevation model (DEM) data is extracted; drainage basin classification riverway grids are extracted through the drainage basin DEM data; river confluence points are extracted based on the classification riverway grids; sub-basin outlet points are extracted according to the river confluence points; sub-basin areas are extracted through the sub-basin outlet points; the geomorphologic unit hydrograph initial probability is obtained through analytical calculation based on the sub-basin areas. The method for calculating the geomorphologic unit hydrograph initial probability through the digital elevation model has the advantages that the data resource is stable and reliable, the calculation efficiency is high, and the result is objective and reasonable, which facilitates the direct solution of the geomorphologic unit hydrograph initial probability.

The invention discloses a series feature extraction system and method aiming at a general voice task in a voice signal. After an emotional corpus is built, voice preprocessing is performed; an audio file subjected to voice preprocessing is used as input to be connected with a voice feature extraction model; the voice feature extraction model can obtain basic information and prominent features of aspeaker through a voiceprint recognition layer; the basic information and the prominent features are fed into a voice recognition layer together; the information of the speaker and the text information are obtained; on the basis of extracting keywords, the information and low level descriptors are transmitted into an emotional recognition layer together; personalized voice features and emotionalfeatures are used for performing emotional recognition to obtain emotional relevant features; a voice feature extraction model can also obtain the basic information and the prominent features of the speaker through the voiceprint recognition layer; the basic information and the prominent features are fed into the voice recognition layer together with voice recognition features; the information ofthe speaker and the low level descriptors are transmitted into the emotional recognition layer together; and the emotional feature output is performed. The series feature extraction system and methodhave the advantages of great data scale, accurate emotion expression, high integration level and the like.

The invention discloses a mountain torrent rapid early warning and forecasting method based on multi-dimensional rainfall characteristic space optimal decision. The method comprises: firstly, calculating initial soil water saturation S of a successive historical rainfall flood process based on a three-layer evapotranspiration principle; secondly, counting the rainfall P of the successive historical rainfall flood process; thirdly, quantifying a rainfall space distribution characteristic K of a successive historical rainfall flood process by combining drainage basin DEM data; calculating a landform unit line of the drainage basin based on the DEM data; taking P, K and S as mutually orthogonal coordinate axes to construct a multi-dimensional rainfall characteristic space coordinate system, establishing a rainfall data point set, dividing the corresponding rainfall data point set into two types of an ultra-alarm subset A and a non-ultra-alarm subset B according to whether the flood process is over-alarm or not, and solving an optimal classification decision equation between the two types of subsets by combining an SVM principle; and if early warning is needed, calculating the runoff process at the outlet of the drainage basin by taking the rainfall as the input of a landform unit line, and carrying out real-time flood forecasting.

The invention provides a displacement computing method and device for an intelligent terminal. The method comprises the following steps: acquiring the acceleration data of the intelligent terminal; judging whether the intelligent terminal is in a motion state according to the acquired acceleration data of the intelligent terminal and a preset threshold value so as to obtain a judgment result; acquiring the acceleration data of the intelligent terminal when the judgment result shows that the intelligent terminal is in the motion sate; removing the noise data in the acquired acceleration data so as to obtain the preprocessing data of the acceleration data; computing the preprocessing data so as to obtain the displacement data of the intelligent terminal. By firstly removing the noise data in the acquired acceleration data of the intelligent terminal and then computing the displacement of the intelligent terminal according to the obtained preprocessing data, the displacement computing method and device for the intelligent terminal can avoid the defect that the computing results deviate because of the direct processing of the acquired acceleration data.

The invention relates to a pollutant detection system, a method and a storage medium, and belongs to the technical field of unmanned planes. The pollutant detection system comprises a monitoring terminal and an unmanned plane. The unmanned plane comprises a controller, an attitude detection module, a wind direction and wind speed detection module, a range finding module, a positioning module, a temperature and humidity detection module, a pollutant detection module, and a first communication module. The temperature and humidity detection module, the pollutant detection module, the attitude detection module, the wind direction and wind speed detection module, the range finding module, the positioning module, and the first communication module are all connected to the controller; and the first communication module communicates with the monitoring terminal. The pollutant detection system utilizes the flexibility and operability of the unmanned plane; the unmanned plane is used to detect the concentrations of pollutants in the high altitude; a pollutant distribution pattern can be obtained, the pollutants in the high altitude can be monitored, and accurate and reliable data is providedfor the scientific and reasonable treatments on air pollution.

The invention belongs to the technical field of file synchronization, and specifically relates to a remote resource synchronization method and system for three-layer architecture. The remote resource synchronization method for the three-layer architecture comprises the steps that a cloud server traverses local directories and generates a list file containing all file synchronization information; an offline server obtains a newest list file from the cloud server, compares the newest list file with the local list file and generates a deletion list and a downloading list; the offline server deletes local files according to the deletion list; the offline server downloads corresponding files from the cloud server according to the downloading list; and a playing terminal obtains playing resource file directories in the list file updated by the offline server through a local area network and obtains playing resources according to the downloading addresses of the playing resource file directories. Through adoption of the technical scheme of the method and the system, the updated files can be conveniently and effectively synchronized to the playing terminal.

The embodiment of the invention provides a domain name information maintenance system based on block chain hybrid consensus. A first network node where an international general top-level domain registration office is located forms a gTLD block chain, and a second network node where a top-level domain registration office of each country or region is located forms a ccTLD block chain. In each blockchain, the domain name information updating process is jointly participated by the network nodes of the block chain, the domain name information updating process cannot be influenced by faults or attacks of a certain network node, and the decentralized maintenance mode is safer than a centralized maintenance mode and has the advantage of being beneficial to maintaining the stability of the system.International general domain name information maintenance and national domain name information maintenance are carried out separately, the difference between the regional domain name and the generaldomain name in information maintenance is adapted, and the information maintenance efficiency is improved. In addition, the domain name information is prevented from being maliciously tampered throughthe block chain technology, and a reliable data source is provided for domain name updating.

The invention discloses a method for evaluating the running health state of a magnetic control paralleling reactor. The method comprises the steps that (1), the running characteristic of the magnetic control paralleling reactor is considered, indexes for evaluating the running health state of the magnetic control paralleling reactor are specifically selected, and the measured values of the evaluation indexes are obtained; (2), normalization processing is carried out on the measured values of the evaluation indexes through reactor preventive test regulations and the data of field researches, and evaluation index quantized values of the same measuring unit are obtained; (3), solution of the state grade membership degree is carried out on the evaluation index quantized values based on the fuzzy theory, and the different state grade membership degrees of all the evaluation indexes are obtained; (4), the running health state of the magnetic control reactor is comprehensively evaluated through an evidence theory evaluation model, and the running state of the magnetic control reactor is determined. According to the method, sample learning does not need to be carried out through a large number of prior data, and the running state of the reactor can be accurately diagnosed.

The invention discloses a motor vehicle tail gas remote measuring result modification method, which comprises the following steps of collecting motor vehicle basic information, motor vehicle tail gasremote measuring data and environment variables around the remote measuring equipment installing point by using motor vehicle tail gas vertical remote sensing detection equipment; obtaining motor vehicle annual inspection relevant information; building a motor vehicle tail gas exhaust data set; preprocessing the collected data; using a random forest model for training a motor vehicle tail gas remote sensing detection result modification model so as to realize the real-time online modification on the motor vehicle tail gas remote sensing detection result.

The invention discloses a vehicle battery health state assessment method and system. The method comprises the steps of obtaining historical operation data of a vehicle battery; dividing the historical operation data into a plurality of fragments, and screening out the fragments meeting a preset condition to form a first set; correcting the battery capacity and the battery energy of the fragments in the first set; and constructing a plurality of battery health state evaluation indexes based on the corrected first set to serve as model feature values, and adjusting and optimizing the model feature values through a plurality of machine learning models to obtain an evaluation result of the vehicle battery health state. The battery health state is evaluated based on the historical operation data of a real vehicle battery, a data source is more real and reliable, and an evaluation result is more accurate.

The invention provides a simulation method of a multi-model flexible architecture based on basin fine classification. The simulation method comprises the following steps: S1, constructing a Xinanjiang-Green Ampt mixed runoff production calculation model of a semi-humid semi-arid basin; S2, subjecting the semi-humid and semi-arid watershed to infiltration-excess and saturation-excess sub-watersheddivision for fine classification; and S3, constructing a flexible architecture model of the infiltration-excess and saturation-excess space of the semi-humid and semi-arid watershed, and performing calculation. The invention provides a convenient and effective method for forecasting the flood process of the semi-humid and semi-arid region, finely classifies the watershed, provides a more reasonable and reliable simulation method for simulating the flood, and improves the calculation precision of the hydrological model. And meanwhile, the problem of classification of mountainous watersheds in medium and small drainage basins lacking observation data is solved, important basic data is provided for flood forecasting and other aspects of the semi-humid and semi-arid regions, and the scientificity of flood forecasting of the semi-humid and semi-arid regions is enhanced. The method is stable and reliable in data source, high in calculation efficiency and objective and reasonable in result.

The invention discloses a method and a system for planning an optimal air quality path based on PM2.5, and belongs to the technical fields of environmental pollution and path planning. The method comprises the following steps: obtaining a starting position and a final position; acquiring user's traffic modes; obtaining one or more path planning schemes according to the starting position, the finalposition and the user's traffic modes; predicating the concentration value of the PM2.5 at each position point in every arrival path according to the user's traffic modes and the one or more path planning schemes; and planning a path with a smallest PM2.5 concentration value according to the concentration value of the PM2.5 at each position point in every arrival path, and outputting the path. The method and the system can provide an optimal air quality path reference basis for people's travel, and minimize the influences of environmental pollution on the physical health of people when traveling.