484 results about "Performance model" patented technology

Methods and systems are provided that may be utilized to make completion design an integral part of the well planning process by enabling the rapid evaluation of completion performance. This integration may include an earth model and may specify wellpath parameters, completion parameters, and other parameters in a simulation of operations using the earth model. The simulation generates well performance measures, which may be optimized depending on well performance technical limits. The optimization may be used to maximize an objective function. The system may include multiple users at the same or different locations (e.g. over a network) interacting through graphic user interfaces (GUI's).

An apparatus and method for monitoring the performance of an interactive voice response (IVR) system used by an automated call processing center generates logs of call activity, determines routing information from the logs, notes predetermined significant activity in agent-caller dialog portions of calls routed to an agent in the logs, and determines at least one quantity correlated to a true intention of callers. A performance model of the IVR system is generated from the logs. The logs, the routing information, the quantity correlated to the true intention of the callers, and the performance model are analyzed to determine a performance value of the IVR system, which is used to monitor the IVR system.

A system and method for automatically creating performance models of complex information technology (IT) systems. System components and elements are subject to periodic monitoring associated with performance thresholds. A continuity analysis is performed by synchronizing testing functions associated with the predetermined system performance thresholds. Resulting data is accumulated and data mined for component and functional relations within the IT system. Models of the system may then be adapted with results generated from the analysis.

A method of network merchandising incorporates contextual and personalized advertising with human input to deliver relevant retail offers to interested online consumers efficiently and intelligently. Catalog content from retailers is downloaded, semantically analyzed and merged. The merged content is filtered using machine- and human-generated specifications to produce a merchandisable universe of products (MUP). Marketers and publishers create and modify corner store ad units and specify product offers from the MUP to display in those units. Publishers deploy the ad units on their web pages. Compensation of publishers by retailers can use a pay-for-performance model. Users visit the publisher's pages, viewing the product offers in the rendered ad unit. Performance data related to context, history, network and geo-location, product attributes and product combinations is derived from server log files is used to dynamically optimize and refine product placement in real time, providing a highly personalized experience for the user.

A system and method for performance modeling for an information technology (IT) system having a server(s) for performing a number of types of transactions includes receiving data for system topology and transaction flows and receiving performance measurement data for the IT system. The measurement data is clustered into multiple regimes based on similarities. Service demand and network delay parameters may be inferred based on clustered data.

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.

A method and system for targeted in-store advertising content is disclosed. In order to improve the success of advertising content on a group of customers, the present invention monitors and records items as they are purchased from the store. These records generate data that is used to categorize customers into defined segments. Segments are matched to pre-defined profiles, which describe certain demographic characteristics common to customers in a particular segment. Advertisers can create advertising campaigns directed to these profiles, and when a certain number of matching segments appear within a certain amount of time within the store, the present invention will display the matching media content. The present invention tracks segment frequency, and applies a weighted T-distribution analysis to determine the likelihood of certain frequencies of segments appearing at a certain time. The present invention also tracks the number of times certain media content has been displayed within a certain amount of time to prevent content overexposure. Use of the present invention's data will help advertisers by introducing a pay for performance model where advertisers pay to deliver content to their target demographic, and by providing information on whether or not an advertising campaign was successful.

A system and method of calculating athlete performance, may include receiving information relating to at least one date of performance of physical activity and generating a proposed training schedule, including one or more training sessions, corresponding to the at least one date of performance of physical activity. Further, the system and method may include receiving information relating to records of the athlete's prior performances, and determining a performance model including predicted athlete performance based on the calculated training schedule and the prior performances.

A method for monitoring consumable performance in a processing tool comprises storing a performance model of the processing tool; receiving a consumable item characteristic of a consumable item in the processing tool; determining a predicted processing rate for the processing tool based on the consumable item characteristic and the performance model; determining an actual processing rate of the processing tool; and determining a replacement interval for the consumable item based on at least the actual processing rate. A processing system includes a processing tool and an automatic process controller. The processing tool is adapted to process wafers and includes a consumable item.

A capability predictor that comprises a database 15 of capability of multiple designs is disclosed. The process capability data includes costs, quality, cycle time, and performance models. The process owner (expert) provides the data. The developer inputs equations necessary to calculate the predictions based in the selected design characteristics and the user selects the design. A processor 11 calculates the prediction based on the selected design and a display, such as monitor 11a or printer 16, displays the results of the predictions.

The invention provides a mixed storage system and method for supporting solid-state disk cache dynamic distribution. The mixed storage method is characterized in that the mixed storage system is constructed through a solid-state disk and a magnetic disk, and the solid-state disk serves as a cache of the magnetic disk; the load characteristics of applications and the cache hit ratio of the solid-state disk are monitored in real time, performance models of the applications are built, and the cache space of the solid-state disk is dynamically distributed according to the performance requirements of the applications and changes of the load characteristics. According to the solid-state disk cache management method, the cache space of the solid-state disk can be reasonably distributed according to the performance requirements of the applications, and an application-level cache partition service is achieved; due to the fact that the cache space of the solid-state disk of the applications is further divided into a cache reading section and a cache writing section, dirty data blocks and the page copying and rubbish recycling cost caused by the dirty data blocks are reduced; meanwhile, the idle cache space of the solid-state disk is distributed to the applications according to the cache use efficiency of the applications, and therefore the cache hit ratio of the solid-state disk of the mixed storage system and the overall performance of the mixed storage system are improved.

The invention discloses a performance prediction and fault alarm method for a photovoltaic power station. The method comprises the following steps of: a, setting the station of the power station; b, setting the operation mode of the power station; c, judging whether required real-time data or historical data exists or not; d, predicting the performance of the power station through an experience model if the state in the step a is that a new photovoltaic power station is required to be designed and the required real-time data or historical data in the step c does not exist, and predicting the performance of the power station through a data drive performance model if the required real-time data or historical data in the step c exists; e, predicting the performance of the power station through the data drive performance model or a polynomial regression model if the photovoltaic power station in the step a is operated and the required real-time data or historical data in the step c exists, and predicting the performance of the power station through the experience model if the required real-time data or historical data in the step c does not exist; f, comparing actual performance with the predicted performance, and performing fault alarm; and g, correcting the models on line by a Kalman filtering method and returning to the step c, and otherwise, directly returning to the step e. By the method, solar energy resources can be utilized to the maximum extent, and power utilization cost can be reduced; and the accuracy of performance prediction and fault diagnosis is improved.

The invention relates to a microservice-oriented container level flexible resource supply system and method. The system comprises a data acquisition device, a performance modeling device, a feedforward controller, a response time predictor and a container scheduler. According to the system and method, the deficiencies of difficulty in suitability for a sudden load mode and difficulty in user service quality guarantee in an existing method are made up for.

Systems and methods are disclosed for monitoring and managing data transactions, such as SQL transactions. In certain examples, a management subsystem generates an alert identifying degrading database transactions to facilitate preventative tuning or other maintenance. In particular, a monitor module tracks performance measurements (e.g., logical reads) of select transactions. A modeler correlates the performance measurements and assigns first performance model(s) to represent the performance measurements and predicted performance measurements of a particular transaction. A trend change module detects a significant change in a trend and / or variance of the performance measurements and can cause the modeler module to generate a second performance model to represent at least a portion of the performance measurements and the predicted performance measurements of the particular transaction. An interface module triggers an alert when the second performance model indicates that the predicted performance measurements of the particular transaction are degrading at or above a threshold rate.

<heading lvl="0">Abstract of Disclosure< / heading> A method for managing railcar movement in a railyard based on the flow of railyard tasks, using a system that includes a computer including a processor, a memory device, and a database. The railyard includes six subyards including a surge yard, a receiving yard, a receiving inspected (RI) yard, a classification yard, a departure yard and a departure inspected (DI) yard. The method uses initial parameters, input to the computer, to simulate railyard task flow utilizing a yard performance model. Based on the simulation, the method determines if a train schedule can be met.

The invention belongs to the technical field of electronic information, big data, cloud computing and the like, and particularly relates to a data sensing-based Spark configuration parameter automatic optimization method. The method comprises the steps of predetermining a Spark application and parameters influencing Spark performance; randomly configuring the parameters to obtain a training set; building a performance model by the training set through a random forest algorithm; and searching out optimal configuration parameters through a genetic algorithm. According to the method, under the condition that a user is not required to understand a Spark running mechanism, a parameter meaning effect, a value range, application characteristics and an input set, the optimal configuration parameters of a specific application running in a specific cluster environment can be found for the user; compared with a conventional parameter configuration method, the automatic optimization method is simpler and quicker; and the used random forest algorithm combines the advantages of machine learning and statistical reasoning, so that relatively high precision can be achieved by using relatively few training sets.

The present invention discloses an automatic optimization method for performance of a Spark platform. The method comprises: 1) creating a Spark application performance model according to an executing mechanism of a Spark platform; 2) for a set Spark application, selecting some data of the Spark application to be loaded and run on the Spark platform, and acquiring performance data when the Spark application is run; 3) inputting the acquired performance data into the Spark application performance model, so as to obtain a value of each parameter in the Spark application performance model when the Spark application is run; and 4) assigning the value that is of each parameter of the performance model and that is obtained in step 3) to the Spark application performance model, calculating performance (total execution time of the application) of the Spark platform when configuration parameters are combined in different ways, and then outputting a configuration parameter combination when the performance of the Spark platform is optimum. The method disclosed by the present invention has the advantages of a low threshold, easy extension, a low cost and high efficiency and the like.

A system and method for providing cloud performance capability estimation and supporting recommender systems by simulating bottleneck and its migration for any given complex application in a cost-efficient way are provided. To do this, first, the system and method builds an abstract performance model for an application based on the resource usage pattern of the application in an in-house test-bed (i.e., a white-box environment). Second, it computes relative performance scores of many different cloud configurations given from black-boxed clouds using a cloud metering system. Third, it applies the collected performance scores into the abstract performance model to estimate performance capabilities and potential bottleneck situations of those cloud configurations. Finally, using the model, it can support recommender systems by providing performance estimates and simulations of bottlenecks and bottleneck migrations between resource sub-systems while new resources are added or replaced.

A method, advertising network, and computer readable medium for forecasting ad traffic based on business metrics in performance-based display advertising. The method commences by defining a set of advertising campaign parameters, the advertising campaign parameters comprising target predicates, a campaign pricing model, and a campaign performance model. The method continues by forecasting a supply of impressions satisfying target predicates, based on a statistical analysis of a historical dataset containing impressions satisfying target predicates. Once a measure of forecasted supply is known, an auction model serves for calculating the likelihood of winning the forecasted impression at auction, based the campaign pricing model and the campaign performance model. Having a forecasted supply, and also an assessment of the likelihood of winning at auction, the method proceeds by determining values for various performance metrics. The performance metrics are displayed; the user makes changes to any one or more of the advertising campaign parameters.

A process for generating a performance model from a functional model for a system including a plurality of distributed hardware and software entities that engage to provide a service to at least one user. The process distributes the representative system requests in a finite number of groups and identifies, for each request group, the corresponding execution flow, formalizes the execution flows by a notation that makes it possible to highlight the causal relationships between the different software entities of the system that are involved in the execution flows and the data characterizing the system's resource consumption, develops an intermediate model, and automates the conversion of the developed intermediate model into a performance model.

A method and system for designing a part with improved fatigue life and resistance to stress corrosion cracking in which residual stresses existing in the part are accounted for. The performance criteria and operating conditions of the part are assessed and a total stress state is determined from the sum of the residual stresses and applied stresses acting on the part. Unified Fatigue Performance Model or Smith-Topper-Neuber parameters are used to determine fatigue life functions which, in turn, are used in conjunction with a fatigue design diagram to determine the appropriate residual stress to introduce in order to optimize the part's resistance to stress induced failure mechanisms. A residual stress distribution is then designed to avoid distortion of the part while still imparting the beneficial effects of compressive residual stress.

A method for identifying variations in aircraft operational parameters includes processing a four-dimensional (4D) aircraft trajectory for a flight along a defined route. The method also includes determining an aircraft intent corresponding to the flight along the defined route based at least in part on an aircraft performance model from a trajectory predictor. The aircraft intent includes multiple segments and corresponding intent parameters. In addition, the method includes adjusting the intent parameters such that a computed 4D trajectory substantially corresponds to the 4D aircraft trajectory. The method further includes determining a computed operational parameter based at least in part on the computed 4D trajectory and the aircraft performance model from the trajectory predictor. In addition, the method includes identifying variations between the computed operational parameter and a corresponding measured operational parameter.

Disclosed is a Docker self-adaptive scheduling system with a task sensing function. A Docker self-adaptive scheduling method comprises the steps that a data collector collects the load of each container and the resource usage rate of a CPU and a memory system; based on a queuing theory and with the resource usage rate as a benchmark, a performance modeler constructs an application performance model and characterizes an association relationship of the load and response time; a response time predictor estimates parameters of the performance model during running through a Kalman filter, wherein estimation is conducted under a convergence condition of meeting a predicted and measured response error expectation; a feed-forward controller analyzes a residual mean and variance through a fuzzy controller to obtain a feed-forward adjustment value of a control parameter of the Kalman filter; a container scheduler judges whether or not a predicted value of the response time violates application service quality and conducts scheduling according to a scheduling algorithm; the container scheduler conducts container expansion or shrinkage or migration.

There are previously involved: a program source-into which a log output instruction for adjusting an application model is embedded; a simulation source for performance simulation corresponding to the program source; and initial parameter values for adjusting the application model. Software parts capable of storing a history of parameter values after adjustment are combined to create an application program and the application model. Logs obtained by executing the application program and the application model are compared, and the parameters of the application model are automatically adjusted in conformance with actual measurement results of the application program. The adjusting result is fed back to the application model, and added to the history of original software parts, in which the parameter initial values are changed at need.

Systems and methods for designing and generating integrated circuits using a high-level language are described. The high-level language is used to generate performance models, functional models, synthesizable register transfer level code defining the integrated circuit, and verification environments. The high-level language may be used to generate templates for custom computation logical units for specific user-determined functionality. The high-level language and compiler permit optimizations for power savings and custom circuit layout, resulting in integrated circuits with improved performance per watt of power consumption.

A method and apparatus for producing predictive performance and capacity information employing a type of factory to reduce the ongoing cost of providing simulation models to answer questions raised by the various business entities is provided. To achieve this, a continual process for providing on-going performance information is provided. The core concept is the development and long-term reuse of component models to create other, more broadly scoped performance models. This requires the implementation of standard simulation model constructs to facilitate reuse, processes for the development of models and their use by clients, and a stable yet flexible repository for component models. The invention comprises processes, standards, templates, and software tools that implement a performance service that consists of the long term maintenance of predictive performance models for repeated use by lines of business to provide capacity planning information.

Providing for dynamic resource provisioning in wireless communication is described herein. By way of example, various wireless performance metrics are collected by respective network access points as an aggregate measure of wireless network performance. Aggregated data can be utilized to generate a performance model for the network and for individual access points. Changes to the data are updated to the model to provide a steady-state characterization of network performance. Wireless resources are generated for respective access points in a manner that optimizes wireless performance. Additionally, resource assignments can be updated at various intervals to re-optimize for existing wireless conditions, whether event driven or based on performance metrics. Accordingly, a robust and dynamic optimization is provided for wireless network resource provisioning that can accommodate heterogeneous access point networks in a changing topology.

The invention discloses a network performance measurement diagnostic method based on a transmission control protocol (TCP). The method comprises the following steps: receiving a test request and target performance parameters transmitted by a client; transmitting detection flow to the client according to the test request, carrying out TCP network performance measurement and capturing background data packets to check a TCP network performance measurement result; analyzing the checked TCP network performance measurement result according to a TCP performance model and the target performance parameters; and gathering measurement data obtained in the TCP network performance measurement process and the TCP network performance measurement analysis result, and generating a TCP network performance measurement diagnostic report. By utilizing the network performance measurement diagnostic method and system based on the TCP provided by the embodiment of the invention, the problem that TCP hidden underlying errors and error symptoms are in proportion to the round-trip time is solved, the inference of the detection flow to network background flow is reduced, and the sensitiveness to local link errors is obviously improved.

Methods for creating and calibrating production and injection well models for a reservoir, are provided. An example of a method for creating and calibrating well models can include performing a comprehensive retrieval or gathering of required data components, feeding the gathered data into well performance software to thereby develop a model of the well, performing an initial calibration of the well model, performing a total system calibration on the well model, and performing a recalibration to fine tune the well model.