126 results about "Statistical Mode" patented technology

The invention discloses an abnormal flow detection method and device, computer equipment and a storage medium. The method comprises the following steps of: screening the historical flow data of the monitoring object; obtaining target traffic data, carrying out regression analysis on the target traffic data; establishing a flow prediction model, predicting the flow data of the monitored object by using the flow prediction model; obtaining a prediction result of the flow data of the monitoring object in a preset time period, carrying out statistical analysis is on a prediction result according to a preset statistical mode; obtaining a traffic alarm threshold value of the monitored object, further obtaining a real-time access log of the monitored object when the real-time traffic data of themonitored object is greater than the traffic alarm threshold value, and performing abnormal traffic alarm if the response time of the real-time access log is greater than the response time threshold value. According to the embodiment of the invention, the accuracy of the alarm threshold can be improved, judgment is carried out by combining the response time of the service, and thus the accuracy ofabnormal flow detection is improved.

The invention discloses a rockburst grade predicting method based on an information vector machine to mainly solve the problem that in the current underground engineering construction process, the rockburst geological disaster prediction effect is not good. A rockburst evaluation index and a grading standard are selected, and domestic and overseas great deep rock engineering rockburst instances are widely collected to establish an abundant training sample library. A cross validation strategy is utilized for training an IVM model with the superior statistics mode recognition performance, accordingly, a nonlinear mapping relation between the rockburst evaluation index and the rockburst grade is established, model initial parameter setting and the training sample library are adjusted according to the training result, and the IVM model predicting the rockburst grade is finally established. By means of the method to predict the rockburst grade, the complex mechanical analysis or calculation is not needed, only the input feature vector of a sample to be predicted needs to be input in the prediction model, and then the prediction value of the rockburst grade can be obtained. The method is economical, efficient and high in prediction precision and has good engineering application prospects.

In a method for statistics mode reloading and for the statistical acquisition in the storage of a dataset in an electronic postage meter machine, the statistics mode of the electronic postage meter machine created for the acquisition of pre-compressed data according to statistics classes (postal classes) is interchangeably installed. A formation of freely selectable, new statistics instruction data for a future statistics mode ensues in the data center for the purpose of a transmission in the form of an instruction dataset. The installation of the statistics mode ensues during a communication of the postage meter machine with the data center. A microprocessor of the postage meter machine is programmed to change the statistics mode by modem or with another suitable communication means at least periodically or when the mail carrier is changed, or within the framework of a reloading of the postage meter machine. Preceding transactions are provided in the communication mode in order to transmit data of the old statistics mode to the data center. A deletion of the old statistics data ensues after a successfully ended, error-free transaction for interrogating the old statistics data and after a transmission of valid, new statistics instruction data during a following transaction. The acquisition now ensues according to new statistics classes, whereby all check steps for membership in respective statistics classes are executed.

A method and apparatus to provide an improved statistical model is disclosed. In one embodiment a statistical model for an electronic communication media is generated. The statistical model based on a predetermined set of features of the electronic communication. The statistical model is thereafter processed with a genetic algorithm (GA) to generate a revised statistical mode. In one embodiment, the revised statistical model is provided in a classifier to classify incoming electronic communications. In one embodiment, the classifier is to determine whether a received electronic communication is to be classified as spam or legitimate.

The invention discloses an ad ordering searching system and system, which comprises the following parts: front retrieval mode, ad statistical mode and ad management mode, searched ad distributed mode to single click price and historical click information of ad from ad management mode and ad statistical mode to order the searched ad and return the front N searching ads according to the request of front search mode, wherein the searching terminal connects front searching mode, searched ad distributing mode and ad statistical mode sequently; the front index mode connects the searching engine group; the ad statistical mode connects the searching terminal; the ad management mode connects the searched ad distributing mode and main ad terminal. The invention maximizes the income of the searched ad, which also monitors the ad in the ad list.

The invention discloses a processing system and method of voting in the group, which is composed of multiple members at terminal, wherein the terminal connects the server through network, which contains front user boundary to display topic for discussion and receive input data; the server contains memory unit to reserve the topic data, informing mode to transmit the voted topic to the terminal according to the topic data, topic maintaining mode according to the data from terminal, result statistical mode of the voted result. The invention realizes the group member topic voting through maintaining the topic data by server in the real-time communication tool.

The invention discloses a man-machine conversation satisfaction degree prediction method and system. The method comprises the steps that satisfaction degree training data of a plurality of training man-machine conversations are obtained; conversation characteristics of the training man-machine conversations are adopted as training samples, corresponding satisfaction degree results are adopted as target values for classification model training, and a classification model is obtained; an actual man-machine conversation is obtained, the conversation characteristics of the actual man-machine conversation are extracted, and the conversation characteristics of the actual man-machine conversation are input into the classification model to obtain the satisfaction degree result predicted by the classification model. When the satisfaction degree is predicted, the conversation characteristics influencing prediction can be added or deleted easily, through a statistical mode, the weights, needing to be specifically set, of all the characteristics do not need to be directly considered any more, only the proper classification model needs to be selected, and weight setting is automatically completed through the study of the classification model on the training samples.

The invention discloses a fabric defect detection method based on a single-classification support vector machine (SVM). The method comprises the following steps: obtaining a defect-free fabric image, optimizing parameters of a Gabor filter by use of an RDPSO algorithm, and constructing a single optimal Gabor filter most adapted to a defect-free fabric image texture feature; optimizing parameters of the single-classification SVM by use of the RDPSO algorithm; performing Gabor convolution filtering on a fabric image to be detected; extracting one group of texture features on the image after filtering on the basis of GLCM; and performing defect determining by use of the single-classification SVM. According to the invention, by use of the single optimal Gabor filter, the detection speed can be effectively improved and the requirement for real-time performance of a system is ensured; and by taking the single-classification SVM as a defect determining method, the problems of local extreme values, over-learning, under-learning and the like by use of a conventional statistical mode identification method can be avoided, the generalization capability of a system can be effectively improved, and the requirement for detection accuracy of the system can be guaranteed.

A radar speed measurement device (10) comprising a display (12) for displaying a target speed, a radar emitter (14) for emitting radar waves toward a target, a radar receiver (16) for receiving radar waves reflected from the target, an analog to digital converter (18) for producing digital signals associated with the radar waves, and a signal processor (20) for determining the target speed by analyzing the digital signals. The device (10) can also calculate statistics associated with the target and further comprises a statistical processor (22) for calculating the statistics. The device (10) can operate in either of two modes. A speed mode is preferably used to determine the target speed, when the target is a race car or any other object. A baseball statistics mode is preferably used to determine the target speed, when the target is a baseball thrown by a pitcher.

The invention discloses an online monitoring method for insulation of a three-phase asynchronous alternating current motor stator. The online monitoring method comprises the following steps of synchronously collecting voltage and current signals of a motor insulation system; using a PWM (pulse width modulation) demodulation technique to process the collected voltage and current signals of the motor; extracting feature indexes of the processed signals, such as a MCSA (motor current signature analysis) feature index, a current signal statistical mode identification index, a sequence voltage distribution statistical index, a Park conversion feature index, a three-phase alternating current voltage difference statistical index and a three-phase alternating current difference statistical index; using each extracted index as a training set of a support vector machine to pre-diagnose the state, outputting the comprehensive state pre-diagnosis result of the motor insulation system, and evaluating the running state of the motor insulation system on line. The online monitoring method for the motor insulation system has the advantages that the motor insulation state can be effectively monitored for a long time; by integrating multiple types of insulation feature indexes, the reliability and monitoring precision of the method are improved, and the data processing precision is high.

The invention discloses a control method and system of an air-conditioner, a readable storage medium and an air-conditioner. The control method is applied to a cloud server and the air-conditioner. The cloud server is in communication connection with the air-conditioner and an intelligent terminal. The control method includes the steps that after a control signal of one-key memory is received, theoperation habits of a user in every moment on one day or several continuous days are statically recorded, a historical operation habit database is obtained, and the statistical modes include the usermanual input mode; an automatic operation control instruction of the user is received; under the automatic operation control instruction, the historical operation habit database is acquired; and theair-conditioner is controlled to automatically run in the corresponding moments according to the operation habits in the historical operation habit database. Repeated operation of the air-conditionerin all scattered time periods by the user is avoided, the effect of relieving and saving efforts for the user is achieved, the using experiences of the user are improved, the data statistical modes include the user manual input mode, and thus conveniences and rapidness are achieved.

The invention discloses a target position identification method based on Haar features. The target position identification method comprises the steps: an initialization phase: acquiring a plurality of images including target positions as positive samples, and a plurality of images without target positions as negative samples, and extracting Haar features from all the positive samples and negative samples to obtain feature values; a training phase: utilizing the obtained feature values to train an Adaboost cascade classifier; and an identification cutting phase: acquiring the images to be identified, extracting Haar features, and utilizing the trained Adaboost cascade classifier to identify the images to be identified, wherein the feature matching region with the largest area is the target position. The target position identification method based on Haar features utilizes the Adaboost to learn and establish a multi-layer tree classifier, and utilizes a histogram statistical mode to accurately position the target at a later stage, thus eliminating the interference caused by different illumination environments and greatly improving the identification accuracy and speed, wherein the accuracy achieves more than 99.9%.

The invention relates to the technical field of image processing, in particular to a ship monitoring method and system and a port operation prediction method and system. A multi-object class recognition model is constructed based on Fa aster R-CNN neural network algorithm. A CNN neural network algorithm establishes a multi-object classification recognition model, the target recognition algorithm is trained and detected through a data set, the detection precision of the trained target recognition algorithm is evaluated, and a ship classification recognition model is established. The remote sensing image is pre-processed and ship identification is performed through a ship classification identification model. According to the method, the spatial visualization effect more conforming to realityis achieved, the data source is real and traceable and is not limited by different working states of equipment of the ship and different port statistical modes, and the monitoring result is more objective. The method has better timeliness performance, can carry out daily statistics on ship entering and exiting conditions of the port in real time, and is convenient for predicting and evaluating the seasonal operation condition of the port.

The invention discloses a data processing method and device for webpage clicking amount statistics. The data processing method for the webpage clicking amount statistics comprises the steps of acquiring the coordinate system of a monitored webpage, recording the clicking amount of the webpage through the coordinate system, determining hot spot regions on the webpage according to the clicking amount and determining the number of the hot spot regions in a statistical mode. Through the data processing method and device for the webpage clicking amount statistics, the problem that in the related technology, zoning statistics cannot be carried out on the clicking condition of the webpage is solved, and therefore the effect of carrying out automatic statistics on the number of the clicked hot spot regions in the webpage is achieved.

The invention discloses a stochastic resonance preprocessing-based digital modulation mode automatic identification method and mainly solves a problem that the prior art has low modulation mode automatic identification performance under a low signal noise condition. The method comprises: sampling received continuous digital modulation signals; normalizing the sampled signals; preprocessing the normalized signals by using a bistable stochastic resonance system to improve the signal-to-noise ratio of the signals; computing the two-order, four-order and six-order cumulants of the signals obtained after stochastic resonance preprocessing by using a statistic mode identification method so as to obtain characteristic vectors; and training a support vector machine by using the characteristic vectors, and identifying the modulation modes of the digital signals by using the trained support vector machine. The method can improve the successful rate of the identification of the modification modes of the digital signals effectively and particularly can ensure accurate identification with a low signal-to-noise ratio. The method can be used for improving the performance of a receiving terminal of a communication system.

The invention discloses an online state statistical system and a method, which can at least solve the technical problem that the traditional single machine statistical mode cannot meet large growth demands of internet users as the processing speed and the memory capacity of a single server are limited. The online state statistical system comprises multiple front-end dotting servers and a rear-end memory database for sharing of the multiple front-end dotting servers, wherein each front-end dotting server can be used for receiving a dotting request from an online user terminal and sending user online state information acquired by dotting data included in the dotting request to the rear-end memory database; the rear-end memory database can be used for carrying out statistics and memory on the user online state information sent by each front-end dotting server; and the rear-end memory database is realized through one or more SSDB servers.

A method, apparatus and system for a virtual machine to issue an instruction to a virtual device, such virtual device being monitored by a management core of a virtual machine monitor. The virtual machine may instruct the virtual device to enter into for example a chat mode, a statistic mode, a file transfer mode or to execute or perform other functions. A management core of a virtual machine monitor may for example collect, channel, route or direct such instructions to a host, one or more other virtual machines or other components in a host network.

The invention discloses a livestock quantity statistics system and method for the livestock industry. The livestock quantity statistics system includes an image acquisition device and an image processing device. The image acquisition device moves or stays along a set route. The image acquisition device is used for collecting images and/or video information of livestock and livestock. The image processing device is used for processing the livestock field and the image and/or video information of the livestock to obtain the number of livestock corresponding to the livestock field. The inventionadopts a fully automatic method, which can prevent mistakes and leakages of manual statistical mode and the situation that the statistics are not timely, and greatly saves human cost, and can preventstress reaction of livestock caused by label fixation and label reading and writing, and does not interfere with the normal growth of livestock; Only a very small number of the mobile devices need tobe deployed in the poultry (livestock) house, and multiple poultry (livestock) houses can share one of the mobile devices when conditions are suitable, so that the cost is lower and the maintenance iseasier to manage.

The invention provides a group control system of elevators. Target value of electric power consumption in the appointed period of time is set by a target electric power setting apparatus. An electric power consumption statistical section is arranged on a group management control apparatus, and records each elevator consumed electric power and average latency according to every preset time period in a statistical mode. A working number control section, is equipped for planning working number of elevator in every time period for obtaining target value according to target value of consumed electric power set by the target electric power setting apparatus as well as consumed electric power and average latency in every time period obtained by the electric power consumption statistical section.A group management control section is arranged for controlling operation of each elevator called at the elevator riding point according to working number in every time period planned by the working number control section.

The invention discloses a forwarding service monitoring method and system for network equipment. The method comprises the steps of defining service features, generating a specific ACL, setting a statistical cycle, counting the number of messages and the number of bytes and calculating the PPS, the BPS and the number of packet losses, so that a monitoring report is generated. The system comprises a service identification module, a monitoring and calculating module and a report generating module. According to the forwarding service monitoring method and system for the network equipment, by defining the service features, quick determination of multiple services entering or leaving a port is achieved; by generating the specific ACL, the conflict between the specific ACL and a security policy ACL is avoided, and the security of a network is guaranteed; by the adoption of the red/yellow statistical mode, the influence of a forwarding time delay is eliminated, and the forwarding services can be monitored in real time.