65 results about "Extended model" patented technology

The invention discloses a method for simulating water injection well water pressure drive fracture extension dynamic. The method comprises the following steps that an oil reservoir geological characteristic parameter of a target water injection well with fractures is obtained according to the oil reservoir geological study; a water injection well water pressure drive hydraulic fracture extended model is established with the integration of a Darcy leak-off model, a continuity equation, a matter balance equation and an initial condition; fluid volume filtered into a stratum is used as a source item based on an oil-water two-phrase seepage model of a seepage mechanics theory, the boundary condition is established by combining the fluid pressure in the fracture, a hole elastic deformation relationship between a fluid body and a rock is established by being combined with a boundary condition established by the fluid pressure in the fracture, that is, a fluid-solid coupling model is established, and the formation pore pressure is calculated and strain and a pore penetration change which are caused by a change in the fluid pressure are obtained; and then the fracture extension dynamic after the action of the fluid-solid coupling is obtained, then the obtained new parameter is used as an initial condition to be repeated, and finally the fracture extension dynamic is obtained. Accordingto the method for simulating the water injection well water pressure drive fracture extension dynamic, the dynamic extension condition of the fracture in a water injection well and the dynamic changecondition of the parameter in a reservoir can be forecasted according to the construction and geological parameters.

The invention discloses a crowd-evacuation simulating method based on an extended BDI model. The crowd-evacuation simulating method, on the basis of the extended BDI model and with the cellular automaton and multi-agent technologies, can simulate the crowd evacuation in a public place in emergency (e.g. a fire, etc.) according to the plane layout of a building. The extended BDI structure provides a certain support for the factors in the spiritual aspect, so the method fully considers the influence of the psychological state of the people on the evacuation in the process of crowd simulation; the method is used for simulation of a crowd with incomplete environmental information; and the method can conform better to the practice. The method has an extensive application prospect in simulation studies of safe and fast evacuation of a large crown in a building and can test design proposals or responding proposals, and therefore the invention is an economical and feasible crowd-evacuation simulating method.

The present invention is concerned with the estimation of health parameters p(k) representing symptoms of a slowly degrading system, in particular industrial gas turbines. According to the invention, an estimation of a true health or independent parameter vector at time step k uses the estimation of the true health or parameter vector at a previous time step k−1 as a starting value for the production of a predicted health parameter vector at time step k. Based on the latter and a set of measured values of input variables of an extended model of the system, a prediction of output variables of the model is produced. This predicted model output is compared with measured values of the output variables to yield an error. From this error, a health parameter estimator in turn produces a health parameter estimate as a revision of the predicted health parameters. Preferably, the estimation of a true health or independent parameter vector at time step k includes a generalized process noise representing stochastic uncertainty and / or a-priori knowledge of an evolution of the health parameters.

Methods and corresponding apparatuses for compressing, monitoring, decompressing or analyzing multidimensional data in a computer system. A sequence of multidimensional input data is received from a data generating process and is processed by using an approximation model to project respective blocks of input data on a subspace. For each block of data, a residual representing the difference between said data block and a reconstruction of the data block from the projection of the data block on said subspace is calculated. The calculated residual is stored in a repository while the projection of the data block is appended to previously stored projections of data blocks in an output buffer. The approximation model may be extended through analysis of the repository of residuals in order to detect significant patterns. If a significant pattern is found, the pattern may be added as an extension to the approximation model. The extension to the model may be stored or transmitted as a transform packet which defines a transformation from an earlier model to the extended model.

The embodiment of the invention provides a fault tree generation method for an extended UML class diagram model of a safety-critical system. The method comprises the steps of constructing the UML class diagram model of the safety-critical system, wherein all classes in the UML class diagram model comprise attributes and operations and have a certain relation, and the element semantics of the model is extended by a stereotype; storing the UML class diagram model into a file with a set format, analyzing the file with the set format corresponding to the UML class diagram model by a set information extraction algorithm to extract all the classes and the attributes and the operation information which correspond to all the classes in the UML class diagram model, and generating a fault tree of the UML class diagram model according to a set fault tree generation algorithm. According to the method disclosed by the embodiment of the invention, relevant safety analysis information is successfully embedded into the designed model of the safety-critical system, so that automatic conversion between the designed model of the system and a safety model of the system is realized, and the design fault of the safety-critical system can be effectively overcome.

The invention discloses a method for setting checkpoints and recovering a failure process based on message number checking and non-blocking, which is used for solving the problems of overlarge information control expenditures and excessive loss in the failure process owing to rollback calculation in the establishment process of the checkpoints of the previous distributed system. For the problems of excessive number of control messages and process blockage during the establishment process of the checkpoints of the distributed system, the invention adopts quantitative analytical judgment of the message number instead of the qualitative analytical judgment based on causal relationship in the previous studies, provides the method for setting the synchronous checkpoints and recovering the collapse process based on an extended model of the distributed system and message number checking and non-blocking, really realizes non-blocking operation of all the processes in the course of setting the checkpoints, and really realizes the minimum system rollback for rollback recovery of the collapse process when a certain process collapses, thus achieving the purpose of improving the performance of the distributed system.

A method, system and apparatus for extending an existing model-to-model transformation. A method for extending a model-to-model transformation can include merging an extension to the model-to-model transformation with the model-to-model transformation to produce an extended model-to-model transformation. Specifically, the merging step can include identifying insertion points for specified transform elements in the model-to-model transformation and inserting the specified transform elements at the identified insertion points in the model-to-model transformation to produce an extended model-to-model transformation. Subsequently, the extended model-to-model transformation can be dynamically applied to a source model in order to produce a target model.

Embodiments of the invention are directed to a method of performing computerized simulations of image-guided procedures. The method may include producing a digital image-based model of an anatomical structure based on medical image data, producing, based on the image-based model and extrapolated data, an extended model that represents the anatomical structure and adjacent anatomical regions not included in the medical image data, displaying a graphical representation of the extended model and performing a computerized simulation of an image-guided procedure using the extended model.

The invention discloses a method for constructing an UDDI (universal description, discovery and integration) extended model in a cloud computing environment. When a cloud service provider registers, basic information, quality information and resource information of service are registered into an extended UDDI model, and a register agent receives the information and processes the information; and when a cloud service user queries, querying is carried out in the extended UDDI model by virtue of the basic information, the quality information and the resource information of the service, and a query agent receives the information and processes the information. The method disclosed by the invention considers the characteristic of the cloud computing environment, the quality information and the resource information of the cloud service are extended into the existing UDDI model, and when the cloud service provider registers the service, the quality information and the resource information of the cloud service also can be registered; and the cloud service user also can screen the service by utilizing the quality information and the resource information of the service as constraint conditions by virtue of the extended UDDI model.

Provided are a token-based database system and method of interfacing with the token-based database system. In accordance therewith, a token database is accessed in a memory. The token database includes a core model, which includes one or more core model tokens that provide default functionality. An extended model is generated in the token database. The extended model includes one or more non-core extended model tokens, which conform to the core model and reference the core model tokens. Thereafter, one or more non-core instance tokens are generated in the token database. The instance tokens conform to the extended model and reference the extended model tokens, wherein each of the instance tokens is configured to have zero or more connections connecting other instance tokens, and wherein the token database comprises a plurality of tokens that includes the core model tokens, the extended model tokens, and the instance tokens.

An information processing system includes a receiving apparatus receiving a broadcast signal; and a data generating unit creating notice information relating to download for update data multiplexed with the broadcast signal for transmission and updating software in the receiving apparatus. The data generating unit includes a device operable to describe a prescribed model ID defined by a predetermined standard in the notice information and to describe an extended model ID used in combination with the prescribed model ID in the notice information; and a device operable to generate the notice information having the IDs described. The receiving apparatus includes a device operable to determine whether the prescribed model ID matches an owned prescribed model ID; a device operable to determine whether the extended model ID matches the owned extended model ID when the prescribed model ID is so determined; and a device operable to acquire update data when the extended model ID is so determined.

The invention discloses a channel prediction method combining deep learning and a basis extension model in the technical field of wireless communication. The channel prediction method comprises the following steps of: step 1, acquiring a correlation matrix of a channel according to channel information at a historical moment; step 2, carrying out eigenvalue decomposition on the correlation matrix to obtain an optimal primary function; step 3, modeling a channel by using the basis expansion model; step 4, acquiring a basis coefficient estimation value based on historically received pilot signals and an optimal basis function; step 5, constructing a training sample set according to the basis coefficient estimation value; step 6, training a BP neural network by using the training sample set; step 7, acquiring a channel prediction model with an optimal weight and an optimal threshold value; step 8, performing online prediction based on the channel prediction model; and step 9, converting the basis coefficient estimation value into a frequency domain channel matrix. The channel prediction method has low calculation complexity and high prediction precision, and is suitable for efficient acquisition of time-varying channel information in a high-speed mobile environment in the future.

The invention discloses a network unknown threat detection method based on a feature extension CNN, and the method comprises the steps: constructing a feature extension CNN model according to the characteristics that many network unknown threats and known threats are from the same family, and are represented as sample features are similar, firstly carrying out the convolution operation of original data at each layer of the CNN, and obtaining a native feature map; performing linear random operation on the native feature map to obtain an extended feature map; finally, combining the two to obtain extended reconstruction data of the original data, the dimension of which is lower than that of the original data, and realizing dimension reduction extended reconstruction of the data; and constructing a security data classification model based on a shallow machine learning algorithm to realize detection of unknown threats in the network security big data. According to the network unknown threat detection method based on the feature extension CNN provided by the invention, the generated extension reconstruction feature not only realizes dimension reduction, but also expands the data representation of the unknown threat, realizes high-precision detection of the unknown threat, and also reduces the calculation complexity.

The invention discloses an extension model generation method and device, and a medium. The method comprises the steps that a basic model in a database is determined and displayed in the form of a visual control, and the basic model comprises at least one of a table, a view and a storage process; receiving a dragging operation for the displayed basic model; setting an association relationship between the basic models according to the dragging operation; and generating an extension model according to the association relationship. According to the method, the extension model can be visually and conveniently constructed in a graphical dragging mode, the extension model can more conveniently and visually display the data among multiple tables, the threshold of data query operation can be reduced, and a user is helped to query the data more efficiently.