115 results about "Group model" patented technology

A speech recognition method and apparatus perform speaker clustering and speaker adaptation using average model variation information over speakers while analyzing the quantity variation amount and the directional variation amount. In the speaker clustering method, a speaker group model variation is generated based on the model variation between a speaker-independent model and a training speaker ML model. In the speaker adaptation method, the model in which the model variation between a test speaker ML model and a speaker group ML model to which the test speaker belongs which is most similar to a training speaker group model variation is found, and speaker adaptation is performed on the found model. Herein, the model variation in the speaker clustering and the speaker adaptation are calculated while analyzing both the quantity variation amount and the directional variation amount. The present invention may be applied to any speaker adaptation algorithm of MLLR and MAP.

The invention discloses a game theory-based multi-micro-grid interconnection running optimization method. The method includes the following steps: analyzing load demand response characteristics of allmicro-grids, and constructing a micro-grid group model; then initializing a system, establishing a day-ahead game model, and calculating a net load of the i-th micro-grid in a j-th period and a totalnet load amount of the system by day-ahead forecast data; obtaining respective optimal strategies by solving by all the micro-grids according to initial status, carrying out information exchange in amicro-grid group, sharing respectively obtained best strategy information, and updating status information; judging, by a system control center, whether Nash equilibrium is reached, and if the systemmeets an equilibrium condition, ending a game, and outputting a final optimization strategy set; and otherwise, turning ahead to carry out optimization again according to updated status information.The method can give consideration to both the stability and the economy of the system, and realize individual benefit maximization and optimal group running of the micro-grids at the same time.

The invention provides a driving track real-time risk assessment framework based on internet of vehicle big data. A track scoring system is established by using the vehicle feature information and theclaim information stored in a database and the driving track information collected from a vehicle-mounted sensor in real time, wherein the track scoring system includes a vehicle grouping model, a track clustering model and a behavior claim model so that real-time scoring of the driving tracks can be realized, the reference is provided for vehicle insurance premium pricing, insurance premium adjustment, insurance premium prediction and creating the new vehicle insurance, and thus the insurance premium price preference is given to the tracks of great driving environment and operation behaviorsand the insurance premium price penalty is given to the tracks of poor driving environment and operation behaviors.

An affine transformation analysis system and method is provided for matching two images. The novel systolic array image affine transformation analysis system comprising a linear rf-processing means, an affine parameter incremental updating means, and a least square error fitting means is based on a Lie transformation group model of cortical visual motion and stereo processing. Image data is provided to a plurality of component linear rf-processing means each comprising a Gabor receptive field, a dynamical Gabor receptive field, and six Lie germs. The Gabor coefficients of images and affine Lie derivatives are extracted from responses of linear receptive fields, respectively. The differences and affine Lie-derivatives of these Gabor coefficients obtained from each parallel pipelined linear rf-processing components are then input to a least square error fitting means, a systolic array comprising a QR decomposition means and a backward substitution means. The output signal from the least square error fitting means then be used to updating of the affine parameters until the difference signals between the Gabor coefficients from the static and dynamical Gabor receptive fields are substantially reduced.

The invention discloses an outsourcing encryption and decryption CP-ABE method capable of achieving user revocation, and relates to the technical field of data encryption and decryption in a mobile cloud environment. The method further achieves the outsourcing encryption operation on the basis of conventional outsourcing attribute encryption, and reduces the encryption calculation cost of a local client. The method achieves the access control of fine granularity of a file on a cloud server, simplifies the secret key management operation for a user, and achieves the revocation of the access authority of an unauthorized user. When the user is revoked, a legal user does not need to update a secret key, and alleviates the burden of an authorization mechanism. The local user just needs to carry out the simple XOR operation to update a cryptograph. The security proof indicates that the method provided by the invention has the non-adaptive selection plaintext safety under a common dual linear group model. The performance analysis indicates that the method reduces the encryption calculation cost of mobile equipment more effectively, can achieve the revocation of an illegal user efficiently, and achieves the control of the access authority of the user effectively.

A conception of object dimension is introduced into the area, where the administrated objects (AO) are rather concentrative. The definition of AO is finely compartmentalized. The AO are compartmentalized into manifold groups under different dimensions. Nesting between groups is allowed. A multi-layer tree is formed. The different dimension represents different sorting modes of AO. The system supports several sorting modes co-existed. The system authorities are split into data authority and operate authority. For the data authority, all data entity in this system controlled by the data authority must possess corresponding safety administration objects (SAO). Associating these SAO with different Role, the invention can complete the data authorities splitting. All SAO in this model are grouped. Multi-grouping all SAO in the system in the same running are supported. Each grouping model is named a 'dimension'. Each value on the dimension is corresponding to a certain group.

The invention relates to a city building complex and rendering method considering city image. According to the method, a fine continuous facet element in a building group model is abstracted to be an intuitive two-dimensional shape, by means of a multi-resolution expression binary tree (EBT), the city image is rendered, wherein the level of detail (LOD) of the city image is more flexible than that defined by the city geography markup language (GML) standard, and the readability and the verisimilitude of the city image are simultaneously guaranteed. According to the city building complex and rendering method considering the city image, an automatic road analysis algorithm is designed for extracting relevant space elements of the city image so as to assist grouping and combining of buildings, and by means of an indexing mechanism, an abstract edge Fedge, a building group example and the EBT are stored to serve as city building complex results so that the complex results are subjected to flexible pre-processing before the LOD scene of the city image is rendered and model updating is facilitated. The city building complex and rendering method considering the city image real-timely subjects a three-dimensional digital city model to visualized rendering and has a wide application prospect in aspects of city navigation, spatial position services and the like.

The invention discloses a new energy active power control method for a power generation right transaction in an electricity market environment. The new energy active power control method comprises the steps of: regarding the tracking of real-time lower spinning reserve of a thermal power generating unit as a general objective of new energy control, and calculating new energy power generation indexes; establishing a control group model according to power generation right transaction components, wherein power generation priority of each control group conforms to the priority of the corresponding component electric quantity; initializing grouping according to the power generation right component with the highest priority in each new energy field stations; carrying out intergroup distribution on the new energy power generation indexes according to the priorities of the control groups; performing precise control on the new energy field stations in the control groups after considering section constraint conditions and actual power generation capacities of different levels; and counting currently participating transaction component electric quantity of each new energy field station in real time, and automatically switching the control groups to realize hierarchical control of the power generation right after the component electric quantity index is completed until all power generation right electric quantity is completed. The new energy active power control method is of great importance in motivating new energy power generation enterprises to participate in the power generation right transaction and enhancing the level of new energy consumption.

The invention relates to a power system load modeling method based on a typical load group. The power system load modeling method comprises the steps of: 1) establishing a typical load group model: generating the typical load group model according to node load information; 2) and establishing a node load model: performing weighted aggregation to obtain node load model parameters according to parameters of the typical load group model and proportions of typical load groups, and establishing a node load model based thereon. Compared with the typical load parameters adopted in simulation at present, the power system load modeling method obtains load parameters of the node load model parameters by performing weighted aggregation on the typical load groups, thus the node active voltage response characteristics and reactive voltage response characteristics are closer to the actual measured situation.

The invention provides a content push method and device, and a computer device. The content push method includes the steps that user characteristics of an exposure application program and click behavior of a corresponding application program are acquired; a sample is generated according to the user characteristics and the click behavior of the application program; the sample is inputted into a grouping model to determine a group to which the sample belongs in a grouping model; the sample is inputted into a corresponding click rate prediction model of the group, and the estimated click rate ofthe application program by a user is obtained; the content is pushed to the user according to the estimated click rate of the application program. After the group to which the user belongs is determined by the content push method, the estimated click rate is obtained according to the click rate prediction model of the group, the accuracy of the estimated click rate is improved, and the content ispushed to the user accurately.

The invention provides a Chinese reading ability evaluation method, which comprises the following steps of: obtaining user information of a user, and calling an initial test question group corresponding to the user information in an evaluation question bank for the user to test; Calculating an initial capability value of the user according to a test result, obtaining an evaluation test paper corresponding to the initial capability value, and sending the evaluation test paper to a terminal where the user is located for the user to perform evaluation, the evaluation test paper comprising test question groups of multiple question types of continuous texts and discontinuous texts; And based on the project response theory, calculating a reading capability value of the user for answering the evaluation test paper by utilizing a preset high-order question group model. The invention also provides a Chinese reading ability evaluation device and a readable storage medium. According to the methodand the system, the user is tested according to the test papers of various question types of the continuous text and the discontinuous text, the item response of the user for answering the test papers is evaluated through the high-order question group model, and the question types have diversity and can more accurately and comprehensively inspect the Chinese reading capability of the user.

The invention discloses a speech recognition system and a recognition method thereof. The system comprises a speech acquiring module, a speech pretreatment module, a speech feature extraction module, a grouping judgment module and a speech recognition module, wherein the grouping judgment module is used for grouping speeches in a clustering mode; the speech acquiring module is connected with the speech pretreatment module, the speech pretreatment module is connected with the speech feature extraction module, the speech feature extraction module is connected with the grouping judgment module, and the grouping judgment module is connected with the speech recognition module; the grouping judgment module comprises a grouping judgment unit and at least two grouping models; the speech feature extraction module is connected with the grouping judgment unit, and the grouping judgment unit is respectively connected with the at least two grouping models; and the grouping models are connected with the speech recognition module.

The invention discloses a method and device for determining the temperature of cable group cable cores based on distributed optical fiber temperature measurement, and an installation method of a distributed optical fiber temperature measuring device. The method for determining the temperature of a cable group comprises the steps of measuring parameters of the environment where the cable group is laid, and parameters of cables in the cable group; establishing a cable group model according to the parameters of the environment and the parameters of the cables; reading a current of a conductor of the cable group, and according to the cable group model, conducting simulation computation on the skin temperature of the cables to obtain the estimated skin temperature Tc of the first cables in the cable group; measuring the actual skin temperature Tb of the first cables in the cable group in the axial direction; according to the estimated skin temperature Tc and the actual skin temperature Tb, computing a conversion coefficient alpha; according to the conversion coefficient alpha, correcting the estimated skin temperature of the cables, and computing actual skin temperature of each cable in the cable group. According to the method and device, the computational accuracy of the temperature of the cable group can be improved, and the temperature computation range of the cable group can be increased.

A client device can receive information about a population to which a user belongs. During operation, the client device determines information about a user, determines a group identifier for the user, and communicates the determined information about the local user and the group identifier to a group-modeling server. The client device then receives a group-activity model that corresponds to the group identifier, and generates a user-activity model for the local user based on the group-activity model and the determined information about the local user. The client device uses the user-activity model to compute an activity probability for a corresponding target activity. The group-modeling server receives user information from a plurality of client devices of a group, and generates a group-activity model for the group based on the user information. The server then sends the group-activity model to users of the identified group.

The invention discloses a crowd motion simulation method and system. The method is completed in a simulation server and the specific process comprises the following steps: receiving a scene model and crowd individual information, and respectively initializing the scene and the crowd individual information; performing grouping by using the K-Medoids algorithm with multiple influence factors according to the distances and relationships among individuals in the crowd to obtain a grouping condition of the crowd; and using the grouping condition of the crowd as an initial state of crowd motion, performing local path planning by using a companion group model based on affinity to realize group behaviors and collision prevention, and figuring out the motion path of each individual to arrive at a selected exit; and rendering the motion path and displaying a simulation result in real time.

The invention provides an HMM voiceprint recognition signing-in method and system based on grouping statistics. According to the method, at first, a signing-in client side collects voiceprint signals of signers, pre-emphasis, framing, windowing and end point detecting are sequentially carried out on the voiceprint signals, the voiceprint signals are transmitted to a server through a network, and then a signing-in server side carries out voiceprint characteristic parameter extraction on the voiceprint signals to generate signer grouping characteristic parameters and generate grouping characteristic parameters of a grouping model; According to the grouping characteristic parameters of each group of the grouping model and the grouping characteristic parameters of signer voiceprints, whether the signers are members of a certain group is judged; finally, the voiceprints of the signers are judged. According to the method, under the circumstance that the number of the signers is large, real-time efficient voiceprint recognition signing is achieved, investment on public equipment is reduced, use is convenient and efficient, by means of the combination of the system and the method, voiceprint recognition signing is achieved with high recognition efficiency and high real-time property.

The invention discloses a method for realizing a personal virtual application firewall based on Openstack. The method comprises the following operation steps of selecting a protocol analysis engine; expanding Neutron security group rules; designing a Neutron application security group model; increasing models and tables for personal application firewall rules; expanding a Neutron client part and increasing definition of personal application firewall rule group management interfaces; expanding a Neutron server part and increasing storage and issuance of a personal application firewall rule group; increasing the query response of ovs-agent to the security group rules; expanding an agent end and realizing the effect of the personal application firewall through iptables+ndpi+tc. The method has the beneficial effects that the Openstack realizes the security group, the security group is equivalent to a personal state firewall of a PC end in a physical network, through expansion of the security group, the fined control for an application is realized, and the security of network boundaries is facilitated.

The invention discloses a method for establishing a contact group in a mobile terminal and the mobile terminal. The method includes the steps that the mobile terminal receives condition attribute information of establishing a first contact group through a man-machine interface; the mobile terminal generates a first group model according to the condition attribute information; the mobile terminal matches attribute information of contacts stored in the mobile terminal according to the first group model to generate a first contact group. Due to the application of the method for establishing the contact group in the mobile terminal and the mobile terminal, the problem that in relative technologies, the only group can not meet requirements of users on different contacts as the establishing conditions of contact groups are single can be solved; and further users can establish contact groups in user-defined mode, multi-dimensionality of contact groups is realized, and improve systematical performance and user experience are improved.

The invention discloses a particle swarm algorithm-based neuron swarm model parameter adaptive optimization method. The method comprises the steps of S1, initializing a particle swarm, setting basic parameters of the particle swarm algorithm, setting a parameter combination search range of each particle, and setting basic parameters of a neuron swarm model; S2, calculating a fitness value of eachparticle in the initial particle swarm, and initializing a particle individual extremum and a global extremum according to the fitness value of the particle; S3, updating the particle speed and position; s4, calculating a new particle fitness value, and updating a particle individual extreme value and a global extreme value; s5, judging whether the maximum number of iterations is met or not, if yes, outputting globally optimal particles, and otherwise, returning to the step S3; and S6, obtaining an optimal parameter combination of the electroencephalogram frequency band according to the globally optimal particles output in the step S5. The invention provides a convenient and efficient neuron group model parameter adjustment method, the parameter identification accuracy is improved, and theadjustment time is shortened.