1166 results about "Multiple Models" patented technology

A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving an input query; conducting a search to identify candidate answers to the input query, and producing a plurality of scores for each of the candidate answers. For each of the candidate answers, one, of a plurality of candidate ranking functions, is selected. This selected ranking function is applied to the each of the candidate answers to determine a ranking for the candidate answer based on the scores for that candidate answer. One or more of the candidate answers is selected, based on the rankings for the candidate answers, as one or more answers to the input query. In an embodiment, the ranking function selection is performed using information about the question. In an embodiment, the ranking function selection is performed using information about each answer.

A system and a method for creating a focus-exposure model of a lithography process are disclosed. The system and the method utilize calibration data along multiple dimensions of parameter variations, in particular within an exposure-defocus process window space. The system and the method provide a unified set of model parameter values that result in better accuracy and robustness of simulations at nominal process conditions, as well as the ability to predict lithographic performance at any point continuously throughout a complete process window area without a need for recalibration at different settings. With a smaller number of measurements required than the prior-art multiple-model calibration, the focus-exposure model provides more predictive and more robust model parameter values that can be used at any location in the process window.

Disclosed herein are systems and methods for demand forecasting that enable multiple-scenario comparisons and analyses by letting users create forecasts from multiple history streams (for example, shipments data, point-of-sale data, customer order data, return data, etc.) with various alternative forecast algorithm theories. The multiple model framework of the present invention enables users to compare statistical algorithms paired with various history streams (collectively referred to as “models”) so as to run various simulations and evaluate which model will provide the best forecast for a particular product in a given market. Once the user has decided upon which model it will use, it can publish forecast information provided by that model for use by its organization (such as by a downstream supply planning program). Embodiments of the present invention provide a system and method whereby appropriate demand responses can be dynamically forecasted whenever given events occur, such as when a competitor lowers the price on a particular product (such as for a promotion), or when the user's company is launching new sales and marketing campaigns. Preferred embodiments of the present invention use an automatic tuning feature to assist users in determining optimal parameter settings for a given forecasting algorithm to produce the best possible forecasting model.

System and method for asynchronous distributed optimization of an enterprise. The system includes multiple computer systems coupled over a network, which store and implement multiple models, including one or more dynamic models representing respective sub-systems or processes of the enterprise. At least two of the models are interdependent. The system also includes an optimizing system that includes multiple optimizers, at least two of which are interdependent, and constraints and / or objectives, and is operable to receive information related to the enterprise from multiple information sources, and use one or more of the plurality of models to generate a solution subject to the one or more constraints and / or objectives, which is usable in managing the enterprise. Some or all of the system operates in an asynchronous manner. Various portions of the system, e.g., the models, data sources, optimizers, constraints and / or objectives, etc., may be updated, e.g., asynchronously, as desired.

Disclosed are an apparatus for recognizing voice using multiple acoustic models according to the present invention and a method thereof. An apparatus for recognizing voice using multiple acoustic models includes a voice data database (DB) configured to store voice data collected in various noise environments; a model generating means configured to perform classification for each speaker and environment based on the collected voice data, and to generate an acoustic model of a binary tree structure as the classification result; and a voice recognizing means configured to extract feature data of voice data when the voice data is received from a user, to select multiple models from the generated acoustic model based on the extracted feature data, to parallel recognize the voice data based on the selected multiple models, and to output a word string corresponding to the voice data as the recognition result.

The invention details methods and apparatus for a routing system or router that includes a model. The model can be in many different forms including but not limited to: resolution enhancement technologies such as OPC; lithography model including but not limited to aerial image; pattern-dependent functions; functions for timing / signal integrity / power; manufacturing process variations; and measured silicon data. In one embodiment, the model can be described as input to the system and the model calculator can interact either with the data structure or the query engine of the detail router or both. The model calculator can accept input as a set of geometry description and produce output to guide the query functions. An example technique called set intersection is disclosed herein to combine multiple models in the system. A preferred embodiment of this invention includes a full chip grid-based router being aware of manufacturability.

System and method for creating a graphical program that uses multiple models of computation (MoC). A first plurality of graphical program elements is assembled in a graphical program in response to first input, where the assembled first plurality of graphical program elements have a first MoC. A structure is displayed in the graphical program indicating use of a second MoC for graphical program elements comprised within the interior of the structure. A second plurality of graphical program elements is assembled within the structure in response to second input, where the assembled second plurality of graphical program elements have the second MoC. The graphical program is executable to perform a function, for example, by executing the assembled first plurality of graphical program elements in accordance with the first model of computation, and executing the assembled second plurality of graphical program elements in accordance with the second model of computation.

Methods and systems relating to efficient shoe manufacturing that reduce the specialized human labor required to manufacture a pair of shoes while avoiding the high costs and special maintenance requirements often associated with highly automated manufacturing equipment are provided. Systems and methods in accordance with the present invention may be used to produce multiple models of custom shoes at a single shoe manufacturing facility using overlapping workflows, thereby reducing the physical footprint of the manufacturing facility. Additionally, embodiments of the invention may provide methods and systems for efficiently producing shoes to meet the demands of a particular geographic location, thereby eliminating the need to import shoes produced in other locations.

Modeling systems and methods for constructing one or more models of a computing system using collected data. Certain model-based systems build topology models and / or model instances by transforming collected performance data into a collection-location independent form. In certain examples, systems include at least one agent for collecting performance data from monitored resource(s), canonical data transform (CDT) configurations, and a data transformation module for performing data transform operation(s) on the performance data based on at least one CDT configuration. The data transform operation may include generating and / or updating a topology model, assigning metrics to model object(s), updating properties of model object(s), creating associations between existing model objects, or the like. Certain systems and methods also allow for a single piece of data to be processed by multiple models or for pieces of data collected from different locations to be matched and / or associated with the same model object.

The invention discloses an image text description method based on a visual attention model. The main content comprises the followings: image inputting, loss function training, stylizing, image enhancing and image thinning; and the processes are as follows: an input image is firstly adjusted as a content image (256*256) with a dual-linear down-sampling layer, and then stylized through a style subnet; and then a stylized result as the first output image is up-sampled as an image in the size of 512*512, and then the up-sampled image is enhanced through an enhancement subnet to obtain the second output image; the second output image is adjusted as the image in the size of 1024*1024, and finally, a thinning subnet deletes locally pixelated artifact and further thins the result to obtain a high-resolution result. By use of the image style migration method disclosed by the invention, the brushwork of the artwork can be simulated more closely; multiple models are combined into a network so as to process the image with bigger and bigger size shot by a modern digital camera; and the method can be used for training the combined model to realize the migration of multiple artistic styles.

The invention aims to provide a method and equipment for testing a mobile terminal. The test equipment is used for testing the mobile terminal by generating a test executing script and acquiring a test executing script to obtain a practical operating result image which is displayed on the mobile terminal and corresponds to test operation, and is further used for comparing the practical operating result image with a corresponding desired result image to obtain a test result. Compared with the prior art, the invention has the advantages that: test operation is directly performed on the mobile terminal in a way of recording the operating process of a mechanical device on the mobile terminal for generating and obtaining the test executing script and the like to realize automatic test of a mobile phone, so that the same effect of manual test is achieved without artificial participation, comprehensive test of multiple models is realized through an image recognition technology, the test quality is improved greatly, the test efficiency is increased greatly, and the test cost is further lowered.

In one embodiment, a system is provided for managing a centrally managed master repository for core enterprise reference data associated with an enterprise. A centralized master repository contains the reference data, the reference data being associated with multiple schemas, each schema including one or more data models for reference data, each data model including one or more fields. A data management services framework coupled to the repository provides services for managing the reference data in the repository. The services framework supports a master schema including a union of multiple models and associated fields in the multiple schemas. The services framework also supports a thesaurus including, for each field in the master schema, a set of synonyms each representing a mapping between the field in the master schema and a corresponding field in a particular one of the multiple schemas. The master schema and thesaurus facilitate centralized management of the reference data in the repository across multiple heterogeneous external operational systems that have different associated data models and are provided indirect access to the reference data in the repository for operational use of the reference data according to associated business workflows.

The invention relates to a method and a system for detecting a road barrier. The invention discloses a first barrier detection model based on a video pick-up device, a second barrier detection model based on the video pick-up device and a millimeter-wave radar, and a third barrier detection model based on a three-dimensional laser radar and an infrared pick-up device, wherein complementary detection for the multiple models is formed through a rough set based fuzzy neural network algorithm, so that characteristic information of the road barrier can be obtained in real time. The method and system for detecting the road barrier can carry out real-time and effective road barrier detection under the conditions of different road scenes and different weathers to obtain parameters such as the travelling speed and direction of different barriers exactly, can extract and analyze surrounding environment information of vehicles from the road traffic environment, and can judge abnormal traffic behaviors so as to relieve the current urban traffic pressure and improve traffic management efficiency.

Methods for three-dimensionally characterizing a reservoir while drilling a high angle or horizontal wellbore through the reservoir are disclosed. An initial reservoir model for the reservoir is selected and a section is extracted for a planned trajectory of the wellbore. A secondary model is generated by performing secondary modeling for at least part of the planned trajectory. An area of interest is identified within the secondary model where statistical uncertainty is high. Possible causes of the statistical uncertainty are identified for the area of interest within the secondary model that are not present or accounted for in the initial reservoir model. A set of parameters for the area of interest are defined at that are based on the possible causes of statistical uncertainty. The area of interest is logged with at least one logging while drilling LWD tool. Sensitivities of the LWD tool response to the subset of parameters are evaluated by performing at least one tertiary model for a range of the subset of parameters. The most sensitive parameters from the subset of parameters and corresponding measurements are identified. One or more real-time LWD measurements to be used for proactive well placement along the planned trajectory are identified and are based on the most sensitive parameters. The initial reservoir model is updated while drilling with information from the tertiary model. The model update is based on physics-based modeling or on inversion and on running multiple models and selection of a best candidate model based on correlations between the tool measurements and modeled results for each geologic model.

The invention relates to mobile tracking of vehicle targets in the communication and transportation field. A self-adapting interactive multiple model mobile target tracking method comprises the following steps of establishing mixed initialized input. including a covariance matrix of a mixed initial condition and a mixed initial state. of each model; establishing constant velocity (CV) and constant acceleration (CA) motion models; updating: calculating covariance matrix and innovation of an error according to a Kalman filter formulation; constructing a likelihood function of a target motion module by utilizing the innovation of a Kalman filter result, and calculating a Markov state transition probability matrix; carrying out estimation output after being fused by utilizing the Markov state transition probability matrix as weight of switch among each motion model. According to the self-adapting interacting multiple model mobile target tracking method disclosed by the invention, the problem that the error is increased or the tracking is failed caused by non-matching of a filter model and a target motion model due to the motion of a target in the traditional interactive multiple model algorithm is solved; the self-adapting interacting multiple model mobile target tracking method has the advantages of low calculation complexity and good tracking effect, and can be applied to target tracking of motor vehicles in the communication and transportation field.

A computer method and apparatus for adaptive model predictive control (MPC) of multivariable processes is disclosed. The adaptive MPC system can perform automatic implementation for a new MPC controller, and, for an existing MPC controller, it can perform automatic maintenance when necessary. The adaptive MPC system consists of three modules: an MPC control module, an online identification module and a control monitor module. In MPC implementation, the online identification module and the MPC control module work together and perform various steps in MPC implementation automatically and efficiently. When the MPC controller is online, the control monitor module continuously monitors the MPC performance and model quality. When control performance becomes poor and considerable model degradation is detected, monitor module will start the maintenance by activating the online identification module. The identification module will re-identify the model and replace the old model. For strongly nonlinear process units, multiple models are identified and used in control.

System and method for parameterizing one or more steady-state models each having a plurality of model parameters for mapping model input to model output through a stored representation of an in-situ hydrocarbon reservoir. For each model, training data representing operation of the reservoir is provided including input values and target output values. A next input value(s) and next target output value are received from the training data. The model is parameterized with the input value(s) and target output value, and derivative constraints imposed to constrain relationships between the input value(s) and a resulting model output value, using an optimizer to perform constrained optimization on the parameters to satisfy an objective function subject to the derivative constraints. The receiving and parameterizing are performed iteratively, generating a parameterized model. Multiple models form an aggregate model of the system / process, which may be optimized to satisfy a second objective function subject to operational constraints.

The invention relates to an optimal control method for a ground source heat pump refrigerating system and belongs to the field of energy-saving optimal control for air conditioning systems of buildings. Multiple models are optimally combined, as along as a prediction model contains contrasting information of the system, the prediction model can be combined with multiple good prediction models for predicting even if the prediction model is poor in effect, and a predicting character of the system can still be improved; in order to improve final predicting precision, a control system operates a combined predicting method to comprehensively utilize information provided by various methods, loss of useful information caused by a single prediction module is avoided, randomness is reduced, and predicting precision is increased. The optimal value provided by the optimal control method is ensured to meet tail end load requirements and capable of minimizing energy consumption of the system. After the optimal set value is determined, a central refrigerating system of the ground source heat pump refrigerating system is controlled to operate in an optimal set working status.

The present invention relates to water events modeling including flood, the number one natural disaster in the world. Specifically, the present invention generates models of water events consist of one or multiple outputs from various modeling processes. It also generates analytics of water events, and integrating the water models for machine and human-eyes consumption. Further, the present invention produces derivatives, tools, and informational services for various purposes, such as, flood risk assessment; flood determination; and insurance rating. The present invention is the process and systems of producing one or multiple models of water events and derivatives, based on various inputs. For modeling water events at a given location and in a timely fashion, the present invention prepares, aggregates, integrates, and maintains all relevant inputs in one system. The input data include various information, such as, water events' extent, flooded areas, flood plain, inundated areas, and measurement of water condition. The input datasets also include various other data, such as, terrain elevation data, land use land cover data, soil conductivity, water gauge measurements, and hydrologic regression equations for calculating flows. The inputs further include hydrologic modeling algorithms, hydraulic modeling algorithms, geospatial algorithms, and local or remote data of real-time water conditions acquired through machine services.

The present invention relates to the field of target tracking and more generally to a method employing improved algorithms, which achieve excellent tracking performance for a high-g maneuvering target. The two-model Interacting Multiple Model algorithm and the Interacting Acceleration Compensation algorithm will be modified by introducing adaptive factors through the detection of the normalized innovation squared which is chi-square probability distributed. The implementation results show that the modified algorithms can handle the target sudden maneuver better and are more accurate than the original algorithms.

System and method for parameterizing one or more steady-state models each having model parameters for mapping model input to model output through a stored representation of a system / process. For each model, training data representative of operation of the system / process is provided including input values and target output values. A next input value(s) and next target output value are received from the training data. The model is parameterized with the input value(s) and target output value, and derivative constraints imposed to constrain relationships between the input value(s) and a resulting model output value, using an optimizer to perform constrained optimization on the model parameters to satisfy an objective function subject to the derivative constraints. The receiving and parameterizing are performed iteratively, generating a parameterized model which is stored. Multiple models form an aggregate model of the system / process, which may be optimized to satisfy a second objective function subject to operational constraints.

The invention provides a latent mobile phone changing user discovery method based on multiple-model fusion. The method mainly comprises the steps of acquiring and preprocessing user consumption data and mobile phone changing track data, characteristic constructing, model establishing and model fusing, predicating, etc. According to the method of the invention, diversity and difference of a machine learning algorithm are used for combining a plurality of models, obtaining better effect and realizing higher generalization capability of the fused model. Training is performed through historical data of the user and predication is performed based on a data set, thereby obtaining high-value users who will change the mobile phone, and accurately pushing mobile phone information to the user.

Embodiments relate to generating active links between model objects. A modeling client can host modeling logic and an application programming interface (API) to create, access, manipulate, and import / export modeling objects used in modeling applications, such as engineering, medical, financial, and other modeling platforms. The source data accepted into the modeling client can include consumer or business-level applications, whose spreadsheet, database or other content can be extracted and encapsulated in object-oriented format, such as extensible markup language (XML) format. Links can be inserted in the resulting model object to link to external resources, such as additional model objects, services, local or remote modeling tools, or other resources. The model object can share, exchange, or combine data from other model object(s), as well as instantiate functions hosted in other model object(s). Multiple links can be inserted to multiple model objects in linked list, node, or other configurations.

A method and system for use in monitoring / evaluating industrial processes such as, for example, plasma processes are provided. In one embodiment, a plasma process fault detection module (100) includes multiple sub-modules. A data selection sub-module (101) obtains selected optical emissions spectra (OES) data for each wafer that is processed. A model building / updating sub-module (102) constructs multiple models from the OES data for a number of wafers. A principal component analysis (PCA) analysis sub-module (103) utilizes PCA techniques to determine whether the OES data for a particular wafer differs significantly from an expected normal wafer as represented by the models. A model maintenance sub-module (104) saves and retrieves models for different processes, associating the current wafer with the correct process. A wafer categorization sub-module (105) categorizes each wafer based on a scalar metric characterizing the residual spectrum vector. A data output sub-module (106) outputs the results to a user.

The invention is applicable to glass panel edge defect detection, and provides an edge defect detection method for a glass panel. The method comprises the steps of: A. performing glass panel image acquisition and performing gray-scale conversion, then performing binarization processing so as to obtain a binarization image, and extracting a contour of a region of interest; B. processing the contour of the region of interest so as to obtain a center line image, and traversing the center line image to obtain point coordinates of each point on a center line; C. extracting a gray-scale image corresponding to the contour of the region of interest, and obtaining a gray-scale value corresponding to the point according to the point coordinates; and D. processing the gray-scale value of the center line, then computing a gray-scale difference mean value of the center line, and determining whether an edge defect exists or not according to the gray-scale difference mean value of the center line and marking the edge defect. According to the edge defect detection method for the glass panel, which is provided by the present invention, the contour of the region of interest of the edge is extracted according to contour features of the edge of the glass panel, and defect detection is performed on the edge of the glass panel based on the gray-scale mean value of an adjacent region of the center line of the contour of the region of interest; and the method can be used for detecting defects of edges of multiple models of glass panels.

A system and method for ontology-enhanced traceability in design and management applications employ ontology nodes embedded in a processor executable traceability link (network) coupling processor executable requirement modules to processor executable engineering object modules to facilitate in all stages of engineering object development. The engineering object development occurs through multiple models of computation, control, and visualization platform networked together via ontology-enhanced traceability mechanism. Processor executable design rule checking module embedded in the design concept nodes creates a pathway for the development process validation and verification at early stages of the object lifecycle. Linking of ontologies / meta-models is performed for the purposes of supporting ontology-enabled traceability across multiple domains.

The invention relates to a strip steel quality forecasting, furnace condition early-warning and fault diagnosis method, in particular to a strip steel quality forecasting, furnace condition early-warning and fault diagnosis method based on partial least square, comprising the following steps: model selection: multiple models are adopted to describe the process characteristics of corresponding steel types; data preprocessing: data alignment based on the model is carried out, synchronization relation of process input and quality output is built and data dimensionless treatment is carried out to eliminate effect of process data on modeling precision owning to non-unity of physical units; an off-line model building; a PLS (partial least square) model for strip steel quality and process variable is built by utilizing a great amount of historical data in normal working conditions; determining control limit of an monitor-control index; determining variable quantity control limit; and on-line forecasting and on-line detection and fault diagnosis. In the invention, the model for the strip steel quality and the process variable is built by PLS algorithm, so as to realize real-time quality forecasting, process monitoring and fault diagnosis.