183results about How to "Self-learning ability" patented technology

The invention discloses a wearable device and method for intelligent monitoring and early warning of chronic diseases. The device includes a wearable equipment terminal, a user mobile terminal and a cloud server; the wearable equipment terminal transmits collected physiological signals, motion data and location information processed through a data signal processing module to the user mobile terminal through the wireless communication module; the user mobile terminal includes a wireless communication module, a data storage module and a data processing module; the data processing module is internally provided with an evaluation and prediction model, data in the data storage module is called for evaluating and predicting chronic diseases of users through the evaluation and prediction model in real time, and the evaluation and prediction result is sent to a user interaction interface; the cloud server includes a cloud database and an evaluation and prediction model update module, the cloud database is used for storing the data evaluation and prediction result sent from the user mobile terminal, and an updated personalized evaluation and prediction model is sent to the user mobile terminal to update the evaluation and prediction model.

Provided are an advertisement filtering system and an advertisement filtering method specific to text characteristics. The advertisement filtering system specific to the text characteristics comprises a content input interface, a characteristic analyzing module, a decision calculation module, a data recording module, an information base, an instruction output interface, a manual operation input interface and a machine learning module. The content input interface is used for receiving user generated contents from an internet interactive product. The characteristic analyzing module is used for analyzing the user generated contents, extracting various characteristics of the user generated contents and calculating characteristic values and generating characteristic vectors according to characteristic history and manual operation records. The information base is used for storing various characteristic data of the user generated contents. The decision calculation module is used for comprehensively judging whether to filter the user generated contents or not according to the characteristic vectors generated by the characteristic analyzing module. The data recording module is used for writing the characteristic data, classified data and the manual operation records into the information base. The instruction output interface is used for sorting the judgement result of the decision calculation module into a display/shield operation instruction and synchronizing the display/shield operation instruction to the internet interactive product. The manual operation input interface is used for receiving and analyzing the operation of the filtering result modified by manual work. The machine learning module utilizes the result obtained from every analysis and the manual operation records to perform learning and updates the decision calculation module according to the learning.

The invention relates to a human body behavioral modeling identification method based on a priori knowledge cluster in a computer system. The method comprises the steps of human body behavioral modeling processing and human body behavioral identification processing. By the adoption of human body behavioral modeling identification method based on the priori knowledge cluster in the computer system, a constructed modeling system has a self-learning capacity and can continuously perfect a classifier along with the classification of observed samples. In cluster distribution obtained in the process of human body behavioral modeling, if outliers exist, the outliers serve as an abnormal behavioral model. When the system is designed, precaution is given as required, the method has great realistic meanings, important influence of priori knowledge on a human body behavioral identification result is considered, an improved cluster method is adopted to model and identify the human body, and foundation can be laid for identifying abnormal behaviors. The method is simple and efficient, can accurately identify different behavioral modes, and has good expandability. Working performance is reliable and stable, and the application range is wide.

The invention provides a method for ensuring navigation safety of a mobile robot in the unknown environments, comprising the following steps: 1) building a local grid map of the current environment and determining occupation probability of each grid; 2) constructing the structure of a fuzzy neural network controller; and 3) enabling the fuzzy neural network controller to output the correct speed command of the mobile robot in accordance with the current partial grid map, the current position information of the robot and the current output movement speed and the turning angle of an autonomous navigation system of the mobile robot. The method can overcome the problem that the single navigating and decision-making system is not high in reliability, avoid the mobile robot from such accidents as collision because of mistaken decision-making of the autonomous navigation system and ensure the safety of the mobile robot in the processes of exploration and movement in the unknown environments.

The invention discloses a neural network active-disturbance-rejection controller for an AC radial magnetic bearing, and a construction method thereof. The input of a first tracking differentiator is given radial displacement x*, and the output is a tracking signal x1 and a differential signal x2; the input of a first self-adaptive expanded state observer is controlling quantity u, radial displacement x and three parameters beta01, beta02 and beta03, the other two inputs of a first nonlinear state error feedback control rule is parameters beta1 and beta2, and the output is the controlling quantity u0; the difference of the controlling quantity u0 and an estimation value z3 is the input of a first compensation factor, the output of a second compensation factor is the controlling quantity u,and the controlling quantity u is used as one input of a first self-adaptive active-disturbance-rejection controller. By constructing the self-adaptive extended state observer, the internal disturbance and the externa disturbance of the controlled object are automatically controlled, and the online automatic adjusting of the three parameters beta01, beta02 and beta03 can be realized along the system disturbance change, the estimation and compensation precision on the disturbance by the extended state observer are increased, and the control performance of the active-disturbance-rejection controller is improved.

The invention discloses a high-speed unordered capsule defect detecting system, which comprises a capsule transmitting device, an image collecting system, a defect identifying system and DSP (Digital Signal Processor) system transplantation, wherein the capsule transmitting device adopts a mode that capsules are randomly arranged and transmitted and is provided with a shaking device in front of a transmission belt; the image collecting system adopts the high-speed shutter technology of an industrial camera of 90 frames per second to solve the problem of smearing and adopts an infrared filter and a lens used for filtering infrared rays as double lenses to solve the switching problem of different detecting light sources; and the defect identifying system uses a method for setting a dynamic gray threshold to separate a foreground from a background and adopts a method based on the threshold to extract the edges of undivided unordered capsules. The defect detecting system adopts a machine vision technology to detect the shape and appearance of solid capsules and does not need contact the detected articles, so the system belongs to non-contact detection. The defect detecting system solves the problem of secondary pollution of the detected capsules under the general technology. The defect detecting system is an environment-friendly detecting system, and the detecting efficiency and precision and the degree of automation are high.

The invention provides a method for predicting the dirt change trend of a large condenser. The method comprises the steps as follows: 1) a support vector machine prediction structure is established, and two subnets are respectively used for predicting the change trends of soft dirt and hard dirt; 2) the product of the current working condition, the historical dirt degree, the cleaning period and the like of the condenser and proportional divisor is used as the input of a support vector machine, the support vector machine is used for obtaining the prediction values of the soft dirt and the hard dirt, and then the sum of the soft dirt and the hard dirt is multiplied with the proportional divisor to be used as a finial dirt prediction result. The proportional divisor can be adjusted by an online learning algorithm to be fit for different conditions. The invention can overcome the difficulty that the dirt is difficult to be described by an exact mathematic model, and the invention is applicable to prediction under different working conditions, is applicable to the prediction of condenser sets with different capacities, can satisfy the prediction of different time spans and has self learning capacity, thereby realizing the exact prediction of the dirt change trend of the condenser.

The invention discloses a room temperature control algorithm based on a fuzzy neural network. A double-input single-output fuzzy neural network controller is designed, the room temperature is detected in real time and output and a temperature setting value are tracked, and an online learning mechanism is adopted to adjust adjustable parameters in the controller in real time to enable the controller to adapt to the change of room temperature and track the temperature setting value. Learning and computing functions of a neural network are integrated into a fuzzy system, and the human-like IF-Then rule of the fuzzy system is embedded into the neural network, so that the adaptive ability of a fuzzy control system is improved on the premise of maintaining the strong ability of knowledge expression, and the system has the ability of self-learning.

The invention provides a springback compensation method for creep age forming. The method comprises the following steps: Step S100, based on MSC.MARC commercial finite element software, constructing creep age forming finite element simulation; Step S200, weighting a springback iterative compensation process based on a molding surface of a finite element simulation result; and Step S300, considering a reverse compensation process of high temperature molding surface thermal expansion effect. The method considers the influence of the strength of a component on surface compensation, the influenceof a component feature structure on surface compensation, and reverse compensation of thermal expansion of a high temperature molding surface. A component formed by the model can still meet the engineering error requirement after being cooled.

The present invention discloses an automatic test paper generation method for network examination. The method comprises: (1) setting a test paper generation constraint condition; (2) generating an initial group P0 according to the constraint condition; (3) calculating the fitness function value of each individual; (4) determining whether the individual fitness function satisfies the test paper generation condition or not, and if individual fitness function satisfies the test paper generation condition, generating the test and ending the automatic test paper generation method; if the individual fitness function does not satisfy the test paper generation condition, determining whether the individual fitness function reaches the maximum iterations or not; if the individual fitness function reaches the maximum iterations, adding 1 to the iterations, and performing the genetic manipulation; and (5) generating a new group P1 through the genetic manipulation, and returning back to the operation (3). The automatic test paper generation method for the network examination employs the genetic algorithm to complete the automatic test paper generation to rapidly obtain a scientific test, solve the problem that the examination system is large in test randomness and unstable in the test paper generation process and improve the examination fairness and rationality.

The invention relates to the technical field of bird-repeller devices in airports and control method, in particular to a wireless-control intelligent bird- repeller system. The intelligent bird-repeller system comprises a central control unit (1) and a bird-repeller work unit (2) and is characterized in that the central control unit (1) comprises a data central processing module (3) which is connected with a control panel (10) by a data wire, as well as a bird monitor module (4), a programmable control module (5), a signal coding module (6) and a wireless transmission module (7) which are respectively connected with the data central processing module (3); and the bird-repeller work unit (2) comprises a wireless receiving module (8), a supply unit (9) and a bird-repeller device (11). The wireless-control bird-repeller system in airports can realize centralized, systematic and intelligent management on various bird-repeller devices in airports, enhance the utilization ratio and use effect of the bird-repeller devices and reduce the management cost on the bird-repeller devices.

The invention discloses an online novel content similarity comparison method which comprises the following steps that a pre-processing step is carried out: a compared online novel is pre-processed, key words are extracted, and the key words are replaced by synonyms to form a standard online novel; a characteristic fingerprint is extracted: the online novel to be compared is divided into a plurality of groups of close order words, a Hash table which is formed by the Hash operation of each group of close order words serves as the characteristic fingerprint; and characteristic fingerprints are compared: the characteristic fingerprint is compared with the characteristic fingerprints of existing online novels which are stored in a characteristic comparison library, and the similarity of the online novel to be compared and the existing online novels is determined according to the quantity or proportion of the same characteristic fingerprints. The method is used for comparing the similarity of the online novels, solves the problems of low efficiency caused by high complicacy of the method by pre-processing and checking omission caused by low purposefulness, and has self-learning ability, and the repetition checking accuracy is improved.

The invention discloses a traffic detection method. The method comprises the steps of classifying the preset number of captured data packets, thereby obtaining a normal traffic data matrix and an abnormal traffic data matrix; training an initial logistic regression model through utilization of the normal traffic data matrix and an abnormal traffic data matrix, thereby obtaining a logistic regression model; and detecting traffic data through utilization of the logistic regression model, thereby classifying traffic data into normal traffic data and abnormal traffic data. According to the method and the system, the problems that an existing traffic detection method is long in delayed time, complex in model and insufficient in robustness are solved; the accuracy of a detection and identification process is high, and the identification efficiency is increased. The invention also discloses a traffic detection system which has the above-mentioned beneficial effects.

The invention provides control method and system of the dynamic feedback of the service quality of an end-to-end service. The control system comprises the following modules: a data acquisition module, a service quality analysis module, a service parameter programming module, a service parameter regulating module and a knowledge base module, wherein the data acquisition module is used for acquiring and detecting the network performance parameters of the end-to-end service and the the end-to-end service evaluating information of a user; the service quality analysis module is used for analyzing the network performance parameters and the end-to-end service evaluating information of the user to determine service parameters which need to be regulated; the service parameter programming module isused for programming the service parameters which need to be regulated to form optimized service parameters; the service parameter regulating module is used for setting the optimized service parameters into service implementation equipment; and the knowledge base module is used for providing information support for the data acquisition module, the service quality analysis module, the service parameter programming module and the service parameter regulating module. The control method monitors an end-to-end network service system by utilizing the control system and programs and regulates the optimized service parameters of the service implementation equipment, thereby dynamically enhancing the service quality of the end-to-end service in real time.

The invention provides a method for controlling the frequency of a compressor, a device for controlling the frequency of the compressor and an air conditioner. The method for controlling the frequency of the compressor comprises the steps that after the air conditioner is started, if an initial set temperature is received, historical initial set temperatures in a time interval where the set moment of the initial set temperature is in are obtained, whether the initial set temperature is matched with the historical initial set temperatures or not is judged, and when a judging result is positive, the operation frequency of the compressor is controlled according to a received operation mode and historical temperature records in the time interval. According to the technical scheme, the air conditioner can have the self-learning capability, the frequency of the compressor of the air conditioner can be adjusted in real time according to the use habits of a user, so that the comfort degree experience of the user is improved, operation of the user is reduced, and the energy utilization efficiency is increased.

The invention discloses a method for talent ability evaluation and job matching for college students. The specific steps include the creation of a student-side personal quality model, the creation of an enterprise-side job ability model, a matching and scoring algorithm, an adaptive algorithm, and engineering implementation. The student-side personal quality model adopts the teaching-simulation-practice model, and the job ability model includes two basic ability models and a specific ability model. Starting from the enterprise-side job ability model, the relationship between variables is obtained through linear regression; the overall structure of engineering realization Consists of data acquisition, data preparation and data application. The present invention uses a big data matching algorithm to calculate the matching degree of the personal quality model and the job ability model, and uses this data to obtain each person's competitiveness and application ranking for a specific position, has self-learning ability, improves accuracy, and saves Reduce time cost, improve efficiency, and achieve better results.

The invention discloses a log file processing method, device and system. The method includes: return code in log file is read; when error is determined by virtue of the return code, database is queried according to the return code, wherein the database is initialized with multiple error information and handling flow thereof; and error handling is automatically carried out according to the found handling flow. In the invention, the return code in log file is utilized to be matched with database initialized with various error handling flows, and handling flow corresponding to the error is executed, so as to realize automatic error correction. Compared with visual check and handling of the prior art, the invention is more timely and accurate and time-saving. Besides, the log file can be analyzed, and related information in the log file is recorded into the database every time, thus realizing the aim of retrospecting history log information.

The invention relates to a geological disaster prediction and forecast technology, and aims to provide a rainfall threshold analysis method causing basin landslide risks. The method comprises the following steps: establishing a three-dimensional grid according to DEM topographic data and soil layer thickness data of a target watershed, and generating boundary conditions and initial conditions required by an RIRM hydrological model; calculating space-time changes of hydrological elements in the drainage basin and drainage basin slope stability reference indexes of any three-dimensional positionin the drainage basin; drawing a relation curve that the safety factor SF, the landslide volume and the landslide area respectively change along with time under the conditions of different rainfall durations and different rainfall intensities; analyzing the relationship between landslide deformation damage and rainfall to obtain rainfall thresholds causing basin landslide risks under different conditions. According to the method, natural basin geomorphic hydrological response characteristics are reserved, and prediction errors can be effectively reduced; drainage basin hydrology and slope stability analysis can be carried out simultaneously, the actual occurrence process of drainage basin landslide disasters is met, and the prediction result is more real and reliable.

The present invention discloses an electronic watch automatic assembling mechanism. The electronic watch automatic assembling mechanism comprises a first assembling transmission band, a second assembling transmission band and a third assembling transmission band which are respectively arranged at the left portion, the middle portion and the right portion of the electronic watch automatic assembling mechanism, the first assembling transmission transmits a movement, the second assembling transmission band transmits a watch housing, and the third assembling transmission band transmits a cover. The second assembling transmission band comprises a left support side plate, a right support side plate, a reinforcement seat and a guide sleeve, there are four telescoping cylinders at the bottom portion of the second assembling transmission band, first connection bars are respectively installed at left and right sides of the extension bar of the second assembling transmission band, the first connection bars are connected with a clamp block. The mechanism also comprises a left support frame and a right support frame, a gear post, a second guide post, a left movement case and a right movement case, wherein a first guide post is arranged between the left support frame and the second support frame. The electronic watch automatic assembling mechanism can assemble four electronic watches at one time, after the shaped dimension of the electronic watch is replaced, a location die is not needed to be made once again, and the electronic watch automatic assembling mechanism has self learning function to optimize the assembling process, realize unmanned assembling of the electronic watch and reduce the production cost.

The invention discloses a vehicle-mounted application containerization isolation framework system based on IPFS and an implementation method, belongs to the technical field of vehicle networking safety, information safety and the like, and solves the potential information safety problem existing in operation and deployment of application software of a vehicle intelligent terminal and a vehicle-mounted system in an existing vehicle networking. The system comprises a unique container platform which is used for vehicle-mounted application installation and is deployed in a vehicle machine system of a vehicle, a decentration monitoring management platform which is used for safety monitoring and software review of a vehicle-mounted application program, and an IPFS protocol which is used for realizing communication between the container platform and the decentration monitoring management platform. The method is used for containerization isolation of the vehicle-mounted application.

The invention discloses a service anomaly warning method and device based on time sequence. The method includes: acquiring multiple true values of a preset warning index in an appointed time period according to preset time intervals; determining multiple predicted values of the preset warning index in the time period according to a predicting model which is obtained by fitting according to the time sequence of historical true values of the preset warning index; according the true values in the time period and the predicted values in the time period, determining whether to perform service anomaly warning in the time period or not; after the warning cycle where the time period is located is finished, adding the true values of the preset warning index in the warning cycle into the historicaltrue values of the preset warning index so as to update the predicting model. By the method and device, warning efficiency can be increased, and false warning and warning failure can be reduced.