118 results about "Model description" patented technology

Apparatus and methods for high-level neuromorphic network description (HLND) framework that may be configured to enable users to define neuromorphic network architectures using a unified and unambiguous representation that is both human-readable and machine-interpretable. The framework may be used to define nodes types, node-to-node connection types, instantiate node instances for different node types, and to generate instances of connection types between these nodes. To facilitate framework usage, the HLND format may provide the flexibility required by computational neuroscientists and, at the same time, provides a user-friendly interface for users with limited experience in modeling neurons. The HLND kernel may comprise an interface to Elementary Network Description (END) that is optimized for efficient representation of neuronal systems in hardware-independent manner and enables seamless translation of HLND model description into hardware instructions for execution by various processing modules.

Method and framework for identifying optimal allocations of computing resources in a complex, distributed data processing environment. A plurality of server models are established, with each server model including one or more server nodes and each server node having an associated set of capacity attributes. Similarly, a plurality of service models are established, each service model including one or more service nodes and each service node having an associated set of demand attributes. The server models are defined with a layered relationship as are the service models. A node that is part of a model in one layer corresponds to a model in the next-lower layer. The invention generates optimized mappings of service nodes that are described in user-selected service models to server nodes that are described in user-selected server models, as a function of the associated sets of demand and capacity attributes.

The invention discloses a method for calibrating external parameters of a monitoring camera by adopting reference height, which comprises the following steps of: far vanishing point and lower vanishing point-based vision model description and related coordinate system establishment; projected coordinate calculation of reference plumb information-based far vanishing points and lower vanishing points in an image plane; reference height calibration-based camera height, overhead view angle and amplification factor calculation; design of a reference plumb direction-based horizon inclination angle calibration tool; and design and use of perspective projection model-based three-dimensional measurement software and three tools for three-dimensional measurement, namely an equal height change scale, a ground level distance measurement scale and a field depth reconstruction framework. The calibrating method is simple and convenient in operation, quick in calculation and high in measurement precision. The reference can be a pedestrian, furniture or an automobile; and a special ground mark line is not needed. The method allows the camera to be arranged at a low place, and the shooting overhead view angle is slightly upward as long as the bottom of the reference can be seen clearly in the video and the ground level coordinate system is definite.

The invention discloses a system and a method for optimizing overall planning of distributed energy. The system comprises a matrix laboratory (MATLAB) optimization analysis part, and a Microsoft EXCEL system input part and a Microsoft EXCEL system output part which are combined with the MATLAB optimization analysis part. The optimization method comprises the following steps of: (1) predicting andanalyzing; (2) modeling and outputting an optimization variable, a performance parameter and a system power flow network chart by using a combined cooling heating and power (CCHP) energy system; (3) starting a scheme optimization process by using a CCHP energy overall planning optimization module; (4) verifying and evaluating an optimization scheme by using a system constraint subsystem; and (5) outputting an optimization scheme. Modeling description is effectively performed on thermal equipment in combination with a mathematical modeling measure, an overall evolutionary algorithm with high performance is optimized and microscopic configuration optimization, and annual operating strategy optimization are performed on the entire system; the system and the method support optimization of a simple cyclic energy system and a more complicated combined cyclic energy system; and the efficiency and economic benefit of the entire energy system are improved.

The invention discloses an electric heating comprehensive energy system scheduling method based on improved weak robustness optimization. According to the invention, the model description of the powerdemand response (DR) is compared and expanded to the electric heating comprehensive demand response (IDR), and the price type and excitation type comprehensive demand response is modeled; Under the low-carbon background, an electric heating comprehensive energy low-carbon dispatching model containing a combined heat and power generation unit, a pumped storage electric boiler, a heat storage electric boiler and a heat storage device is established, and the electric power constraint condition and the thermal power constraint condition are determined with the minimum comprehensive energy operation cost and the maximum benefit of a carbon emission transaction model as objective functions; Considering the uncertainty of wind power and comprehensive demand response, and the improved weak robustoptimization is utilized to process the uncertainty of the source load side to obtain an improved weak robust low-carbon scheduling model of the electric heating comprehensive energy system; And finally, an improved bacterial population drug tendency algorithm (BCC) is adopted for solving, and the effectiveness of the proposed model and algorithm is verified through examples.

A system and method for testing robustness of a simulation model of a cyber-physical system includes computing a set of symbolic simulation traces for a simulation model for a continuous time system stored in memory, based on a discrete time simulation of given test inputs stored in memory. Simulation errors are accounted for due to at least one of numerical instabilities and numeric computations. The set of symbolic simulation traces are validated with respect to validation properties in the simulation model. Portions of the simulation model description are identified that are sources of the simulation errors.

The invention relates to a composite layered anti-interference controller, in particular to a design of the composite layered anti-interference controller in a type of multisource jamming control system. The anti-interference controller is designed aiming at the multisource jamming control system containing external model description disturbance, random disturbance and energy-bounded disturbance. Firstly, a reduced-order disturbance observer is structured to estimate and counteract the external model description disturbance of the multisource jamming control system; secondly, the controller having H infinity and guaranteed cost performance index is structured, wherein, the H infinity performance index can be used for inhibiting the energy-bounded disturbance in the system, and the guaranteed cost performance index can be used for inhibiting the random disturbance in the system as well as optimizing the upper bound of variance; the composite layered anti-interference controller can be formed by the reduced-order disturbance observer and the feedback controller with a state of robust H infinity and guaranteed cost; finally, based on convex optimization algorithm, gain array of the composite layered anti-interference controller can be solved. The invention has the advantages of strong anti-interference property, convenient design and the like, and can be applied to a navigation and control system of aerospaceplane, etc.

The invention relates to a system and method for expanding the model driving development capability by applying a plug-in. In the system and the method, a'model and plug-in' combined mode is provided to describe and establish a software system, firstly a model designing tool is used for establishing basic model description of the software system and then establishing a plurality of reusable plug-pin model for further describing a basic model object, the plug-in model can be expanded randomly on various basic model objects, and the plug-in can complete a software function with any complexity, therefore, the expansion of the model driving development capability is realized. By utilizing the invention, the technical problems of the existing model driving development method that because a fixed model is adopted, the describing capability of complex service system is poor, and the software system with the model driving development can not be established, expanded and maintained visually and dynamically under the operating state and the like are solved. The system developed by using the method has the advantages that the development complexity degree is low, the development speed is fast, the reusable degree of technology is high, the expansion is flexible, the maintenance is convenient and the reliability is high.

Method and apparatus for optimizing allocation of computer resources between server and service models. A server model is established in response to user input data. The server model includes one or more server nodes, and each server node has an associated set of capacity attributes. In addition, a service model is established that includes one or more service nodes. Each service node has an associated set of demand attributes. In response to a user selection, one of a plurality of optimization methods and one of a plurality of optimization policies, as embodied in objective functions, are selected for mapping the server nodes and service nodes. An optimized mapping is then generated of the server nodes in the server model to the service nodes in the service model using the selected optimization method, along with the demand and capacity attributes.

A method and system create a geometric object model for use in machine vision inspection. A pixel image representation of an object is acquired. Based on this pixel image representation, part models for the parts of the object are generated. Each part model corresponds to a different part of the object. From the part models of the object, a model for the entire object can be created. Using this created object model, a test inspection is performed on a set of test images, and each of the test images is associated with a set of known inspection measurements. The test inspection produces a set of testing inspection measurements. If the test inspection yields satisfactory performance, the object models created are stored.

The invention discloses an impulsive neural network operation system and method for brain-like intelligence and cognitive calculation. The system comprises a model description module, a parameter database, a configuration description module, a configuration manager, a rule manager, a data manager, a network builder, a network manager, an operation manager, a scheduler, a log manager, an operationmonitoring module and an imaging display module. The system provides a function of automatically executing synapse and neuron clipping and neogenesis according to certain conditions and rules; and multiple flexible rules for starting trigger conditions and execution processes of clipping and neogenesis processes are provided, so that the burden that a neural network developer needs to compile synapses and neuron clipping and neogenesis programs by himself / herself is avoided, and some problems existing in an existing brain-like pulse neural network operation framework are effectively solved.

The invention relates to a composite layered anti-interference filter, in particular to a design of the composite layered anti-interference filter in a type of multisource jamming system. The anti-interference filter is designed aiming at the multisource jamming system containing random disturbance, energy-bounded disturbance and external model description disturbance. Firstly, a disturbance observer is structured to estimate and counteract the external model description disturbance of the multisource jamming system; secondly, the filter having H infinity and guaranteed cost performance index is structured, wherein, the H infinity performance index can be used for inhibiting the energy-bounded disturbance in the system, and the guaranteed cost performance index can be used for inhibiting the random disturbance in the system as well as optimizing and estimating the upper bound of error variance; the composite layered anti-interference filter can be formed by the disturbance observer and the filter with the robust H infinity and the guaranteed cost; finally, based on convex optimization algorithm, gain array of the composite layered anti-interference filter can be solved. The invention has the advantages of strong anti-interference property, high filtration accuracy and the like, and can be applied to a navigation and control system of aerospaceplane, etc.

A data processing model construction method and device, a server and a client are provided in that present specification. The method comprises the following steps: acquiring model description parameters and sample data of the target data processing model; determining a basic model according to the model description parameters and the sample data; training the basic model according to the sample data to obtain a target data processing model. In the embodiment of that present specification, the model description parameters are obtained in a targeted manner, and based on the model description parameters, the server is able to accurately determine the modeling requirements of the user, and automatically matches the appropriate model as the basic model according to the user's modeling requirements, and then the corresponding data processing model is constructed, so that users do not have to do tedious test, feature engineering, model selection, model parameter search and other operations tofind the appropriate basic model, the difficulty of user operation is reduced, and the processing efficiency is improved.

A method for verifying a software implementation generated from a model that includes a plurality of model elements is described. The method includes converting a model description into a textual representation of model elements and interconnections between the model elements, defining a series of assembler macros that implement the functionality of the model elements as sequences of assembly instructions for a target processor, compiling the textual representation into an object code image associated with a target processor using the macros, describing the object code image in a context-free grammar, and reproducing the model description from the object code image and the context-free grammar.

The invention discloses a production simulation model for power generation. The production simulation model for power generation comprises an operation simulation basic procedure sub-model, a model description sub-model, a calculating module, a process sub-model, a unit combination sub-model, an economic dispatch sub-model and an auxiliary problem processing sub-model. The production simulation model for power generation can overcomes the defects that in the prior art, the calculation amount is large, the application range is small, the simulation effect is poor and other defects, and has the advantages of being small in calculation amount, large in application range and good in simulation effect.

The invention discloses an interactive shoe last modeling method based on foot feature size, and the shoe last modeling method based on foot key size is to build a key contour curve through inputting the foot key size of a user and combine the contour curve into a shoe last curve frame for building shoe last sub-curves in blocks, and the shoe last sub-curves are spliced and faired for obtaining a whole shoe last curve; the shoe last modeling method based on a foot scanning model of the user introduces a user foot model, builds a foot feature model and a corresponding shoe last feature template, and combines the shoe last feature template and the contour curve to subdivide the initial grid surface of the shoe last feature template for obtaining a shoe last surface prototype; builds a unified shoe last model description; and adopts two modes of adjustment to the shoe last surface based thereon: scaling of the shoe last model based on size control or partial surface modification by adopting control points for adjustment. The invention realizes the shoe last modeling method without solid last.

The invention provides a heterogeneous network perception model division and task placement method in assembly line distributed deep learning, which mainly comprises three parts, namely deep learningmodel description, model division and task placement and assembly line distributed training. According to the method, firstly, for resource requirements of deep learning application in the GPU training process, corresponding indexes such as calculation time, intermediate result communication quantity and parameter synchronization quantity in the training execution process of the deep learning application are described and serve as input of model division and task placement; then indexes and heterogeneous network connection topology of the GPU cluster are obtained according to model description, a dynamic programming algorithm based on min-max is designed to execute model division and task placement, and the purpose is to minimize the maximum value of task execution time of each stage afterdivision so as to ensure load balance. And finally, according to a division placement result, performing distributed training by using assembly line time-sharing injection data on the basis of modelparallelism, thereby realizing effective guarantee of training speed and precision.

The invention discloses a vehicle tracking method combining target information and motion estimation. The vehicle tracking method includes the following steps that step1, a target center pixel point coordinate x0 and a tracking window width h1 (1, w) are initialized; step2, motion information of a target is extracted, the color probability model Piu of the target is calculated; step3, a next frame of image sequence i is read, dimension changes of the target are determined in combination with motion information, and h1 (1, w) is updated; step4, a Kalman filter is used for estimating the predicated position y0^, in the current frame, of the target; step5, The position y1, in the current frame, of a target is positioned nearby the predicated position y0^ by the utilization of a Mean-Shift progress positioning; step6, the Kalman filter is updated, and then the method skips to the step3 to be continued. According to the dimension changes of the target and the background interference problem, in combination with the motion information of the target vehicle, model description is optimized, the window width of an MS algorithm kernel function is changed in a self-adaptation mode according to a dimension judgment mechanism, motion estimation is performed on the target through the Kalman filter, an MS algorithm initial search center is optimized, and the problem that an MS algorithm can not track a shielded vehicle is solved.

The invention discloses a knowledge management system, to be concrete, it is a kind of software to manage and demonstrate the knowledge, in this invented method, the knowledge is in the form of discrete and is neatened through the tree models; the knowledge applications are implemented via the tree nodes. Tree model which is adapted to the business processes, workflow, organizational structure, position structure, application process and so forth, can be described by the order and branches of Enterprise Application logic, tree model has its own model attributes, tree model consists of a series of nodes in a model. The tree model attributes include: model description, model attributes, model priority, model managers and other attribute information; the node model is divided into two categories: general-node model and macro-node model. In the process of implementing, the model should meet the relations between the data structures, and then based on this fundamental relations we can build more extensive tree model with attributes correlation, finally creating the lush tree structure, that is how to implement the function of combining the complex processes and knowledge and displaying them in the way of knowledge maps.

The invention relates to a cloud manufacture capacity service modeling method based on a meta-model. The method comprises the following steps: (1) constructing a system achieving the method, enabling the system to comprise a manufacture capacity service meta-model description module, an interactive type manufacture capacity service description expansion module and a manufacture capacity service script file generating module; (2) enabling the manufacture capacity service meta-model description module to abstract the manufacture capacity service meta-model; (3) enabling the interactive type manufacture capacity service description expansion module to expand and perfect various contents of the manufacture capacity service meta-model; and (4) enabling the manufacture capacity service script file generating module to generate a service description script file which can be processed by a cloud manufacture serve engine. According to the cloud manufacture capacity service modeling method based on the meta-model, the service description script file which can be processed by the cloud manufacture service engine can be fast and effectively produced through conversion, and efficiency of capacity knowledge acquisition and model construction is ensured.

The invention relates to a reusable simulation model interface design and butt joint method and device, a medium and computer equipment. The method comprises the steps of obtaining a simulation modelheader file or a model description file from a working space, and generating a simulation model frame according to the simulation model header file or the model description file; according to the simulation model frame, generating a simulation model tree to be displayed in a model operation interface; receiving model modification data input by the corresponding simulation model tree, modifying thesimulation model frame according to the model modification data, and obtaining a reusable simulation model; when a data output instruction input by the corresponding simulation model tree is received, obtaining the model file according to the reusable simulation model and performing display in the model operation interface. The model data editing operation is performed in a visual model editing interface, the reusable simulation model frame can be rapidly constructed and generated, a model developer does not need to pay attention to code details of reusable model development norms, more energy can be put in model function development, and the model design and butt-joint efficiency and reusability are improved.

The invention discloses a fractional-order neural network modeling method based on a smooth Group Lasso penalty term, and the method comprises the following steps: selecting a neural network model, and determining an error function; Updating a training network weight through employing a fractional-order steepest descent method, i.e., updating the weight value in a fractional-order negative gradient of the error function relative to the weight value; obtaining the network parameters of a neural network model according to the fractional-order steepest descent method at step 2; and calculating the precision of the neural network model through employing a testing sample. The beneficial effects of the invention are that the method carries out the training of the network weight value through employing the fractional-order steepest descent method; compared with an integer-order derivation gradient algorithm, the method is higher in precision because the fractional-order model description is more accurate than integer-order model description.

The invention provides a model online method and device, relates to the field of communication, and can improve the model online efficiency. The method comprises the following steps: receiving a datamodeling instruction input by a user, wherein the data modeling instruction is used for requesting to create a machine learning model; creating a machine learning model according to the data modelinginstruction, and generating a serialized model file and a model description file of the machine learning model with the serialized model file being a file in a serialized format of the machine learning model and the model description file being a file representing attributes of the machine learning model; receiving a model deployment instruction input by a user; generating a new service script according to the universal service script template and the model description file; generating a mirror image of the model according to the new service script and the serialized model file; and generatingmodel service POD according to the mirror image of the model, so that the machine learning model is deployed online.

The present invention discloses a multi-source heterogeneous system emulation method and apparatus. According to the method, a corresponding element model is called from a pre-created element model library according to a system structure of a multi-source heterogeneous system, wherein each element model comprises: physical description information, mathematical description information and a solver functional emulation model, which are used for describing a corresponding subsystem, a model description document used for describing parameter information of the subsystem, and an interface standardization document used for describing a connection relationship between an input / output interface of the element model and input / output interfaces of other element models. An operator can perform modification on model information of the element models according to the corresponding model description documents, so that emulation of each subsystem is implemented according to the corresponding functional emulation model, and data interaction between the element models is implemented by means of the interface standardization documents, and thus, an emulation model of the multi-source heterogeneous system is formed and emulation of the multi-source heterogeneous system is implemented.

A method includes accessing a structure model defining a cross-sectional profile of a structure on a sample. The cross-sectional profile is at least partially defined using a set of blocks. Each of the blocks includes a number of vertices. One or more of the vertices are expressed using one or more algebraic relationships between a number of parameters corresponding to the structure. Information is evaluated from the structure model to produce expected metrology data for a scatterometry-based optical metrology. The expected metrology data is suitable for use for determining one or more of the number of parameters corresponding to the structure. Apparatus are also disclosed.

The invention discloses a method for mapping between a CIM (common information model) and a relational database. The method comprises the steps as follows: building meta-model descriptions of a class and an object respectively to remove semantic differences related with the class and the object from the meta-model systems of the class and the object; and mapping meta-models to a relational database so as to build the database tables of the two meta-models, namely a pattern relation table collection (called as a pattern library) formed by mapping the class meta-model and an object relation table collection (called as an object library) formed by mapping the object meta-model. The database built by the method has limited number of tables; and as the meta-models are universal, the situation means that the table struture is stable and the arbitrary expansion requirement and the referential integrity constraint on an infomation model in a CIM appliation can be met.

The invention discloses an electric-gas distribution network flexible planning method considering a flexible constraint and full cycle cost. The method comprises the following steps of 1) establishingan electric-gas distribution network typical planning model based on CCHP coupling, which includes establishing a target function and a constraint condition; 2) introducing flexible planning elements, which includes a flexible power flow constraint and full-cycle planning cost; and 3) forming a flexible planning model and solving, which includes flexible planning model description and call MOSEKsolution. A CCHP-coupled electric-gas distribution network power flow model based on a second-order cone model is established. In the model, non-convex and nonlinear terms in a traditional power flowequation are eliminated and effective solution can be performed while calculation accuracy is ensured. For various uncertainties in planning, the concept of the flexible constraint is introduced intothe planning model, which improves the robust adaptability of a planning scheme to various uncertain factors.

The invention discloses a CIM (common informatoin model) mapping method which comprises the steps as follows: building meta-model descriptions of a class and an object respectively to remove semantic differences related wtih the class and the object from the meta-model systems of the class and the object; and mapping meta-models to a relational database so as to build the database tables of the two meta-models, namely a pattern relation table collection (called as a pattern library) formed by mapping the class meta-model and an object relation table collection (called as an object library) formed by mapping the object meta-model. The database built by the method has limited number of tables; and as the meta-models are universal, the situation means that the table struture is stable and the arbitrary expansion requirement and the referential integrity constraint on an infomation model in a CIM appliation can be met.

The invention belongs to the technical field of computers, relating to fault diagnosis system and method of an encoder based on logic compatibility and aiming to provide an automatic fault diagnosis device of an encoder and a diagnosis solving method thereof. The fault diagnosis system comprises a user interface unit, a model description unit, a language analysis unit, a conflict recognition unit, a diagnosis solving unit, a fault positioning unit and a digital communication unit. The system is specially characterized in that the structure, function and component behavior of the encoder is prescriptively described by using a model description language according to an encoder constitution principle, accordingly, the expected behavior of the encoder under normal circumstances is deduced, differences exist between the expected behavior and an actual observation when a fault occurs, and then a component set triggering the fault is confirmed by using logical deduction. In the invention, from the conflict recognition to the generation of candidate diagnosis, the whole operation process is simple and needs short time, and the discrimination and positioning of the system on a fault point does not depend on the experience of an operator or an expert, thereby the limitations of the traditional diagnosis method are overcome.