1246 results about "Analytic model" patented technology

Methods and systems for analyzing the success of a marketing campaign by using campaign results and an original campaign database are disclosed. The method includes the steps of profiling results of the marketing campaign against a list of user defined dimensions (analytic models may be used to derive dimensions) and assigning a score to the results of the marketing campaign.

A system and method for collecting, filtering, analyzing, distributing and effectively utilizing highly relevant events (such as key business events) in real time, from huge quantities of data. The present invention analyzes both historic and real-time data stemming from operational activity, by interfacing with internal data repositories (such as Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM)), external data sources (such as suppliers and clients), and real time operational systems in order to create an Active Intelligence Platform. This Active Intelligence Platform is positioned as a layer between the organization's data sources and its applications, monitoring inputs and relaying only the important data items to the relevant individuals and/or systems. This allows individuals and systems to respond immediately and effectively to key events.

A computer-implemented method, a system, and a network include receiving network data from a network and non-network sourced data from one or more external sources relative to the network; performing data mining on the network data and the non-network sourced data; developing a predictive analytics model based on the data mining; and performing predictive analytics on the network data and the non-network sourced data using the predictive analytics model to detect likely future failures in the network. The network can include a Software Defined Network (SDN) operating at any of Layers 0, 1, 2 and/or 3.

A system for automated concurrency configuration of multi-threaded programs comprises one or more processors and memory coupled to the processors. The memory stores program instructions executable by the processors to implement a resource management tool. The resource management tool is configured to determine respective target values for one or more concurrency configuration parameters to be set in a deployment of an application using an analytic model and a set of performance metrics obtained from the application (e.g., values of throughput, response times, and corresponding resource utilization measurements), and to deploy the application with the concurrency configuration parameters set to the target values.

A real time decisioning service comprising a set of powerful tools accessible in ASP mode allowing an end user to create, configure, test, and deploy decision engines to automate real time decisions, comprising both expert and custom analytic models used within decision strategies, and comprising systems integration and strategy consulting is provided. An exemplary decision system is described.

An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.

Methods, systems, and computer program products for monitoring, aggregating, and correlating business events in real time and acting on the results with near zero latency, wherein each event is processed in the first order relative to the event density, are described herein. In an embodiment, the method operates by receiving historical values comprising keys and data fields at an analytic model. Rules associated with actions are applied to the historical values. Actions including updating data are executed pursuant to the rules, and then the method determines whether additional rules are to be applied; and performs actions associated with these additional rules until there are no remaining rules to apply. The method stores updated data in a database.

The invention provides a universal machine learning data analysis platform. The universal machine learning data analysis platform comprises an interface module, a data storage module, a preprocessing module, a feature extraction module, a feature conversion module, an algorithm module and a selection optimization module, wherein the feature extraction module extracts feature parameters from to-be-analyzed data according to the feature parameters set by a user; the feature conversion module is used for converting features set by the user to be in a representation form required by the user; the algorithm module comprises a plurality of algorithm models for the user to select and build, and the user builds at least one group of models; the selection optimization module selects out an optimal model and an optimal parameter from the built models and then stores the optimal model; and data generated by the modules is stored in the data storage module. According to the platform, the user can freely combine and use the modules and the algorithm models, and also can build a complex model and quickly and iteratively develop a novel analytic model, so that the working efficiency is greatly improved.

Disclosed is an improved method and system for implementing DBMS server performance optimization. According to some approaches, the method and system incorporates DBMS wizards recommendations with analytical queuing network models for purpose of evaluating different alternatives and selecting the optimum performance management solution with a set of expectations, enhancing autonomic computing by generating periodic control measures which include recommendation to add or remove indexes and materialized views, change the level of concurrency, workloads priorities, improving the balance of the resource utilization, which provides a framework for a continuous process of the workload management by means of measuring the difference between the actual results and expected, understanding the cause of the difference, finding a new corrective solution and setting new expectations.

Arrangements and methods characterize the calorimetric response of a display device. These arrangements and methods use an analytic model selected based on the type of the display device to characterize the calorimetric response of the display device. A lookup table compensates for individual characteristics of the particular display device by receiving a set of indices and providing a set of adjusted values as inputs to the analytic model.

Method for evaluating an underground reservoir production scheme taking account of uncertainties.

Flow simulator input parameters characterizing the reservoir and the production scheme are selected. An approximate analytical model allowing the reservoir responses to be predicted is constructed. A desired degree of accuracy D_p is defined, this degree of accuracy D_p measuring the difference between the responses of the model and those of the simulator. The degree of accuracy D_p(M) of the predictions of the model is calculated. A design of experiments is constructed so as to select simulations to be performed, pertinent for adjustment of the model. The simulations selected by the design of experiments are carried out, then, for each response simulated by the simulator, the analytical model is adjusted by means of an approximation method. This operation is repeated until the desired degree of accuracy D_p is reached. Finally, the production scheme is evaluated by analyzing the reservoir responses predicted by the approximate analytical model.

Application: notably to the development of petroleum reservoirs for example.

A system and associated method for continuously optimizing data archive management scheduling. A job scheduler receives, from an archive management system, inputs of task information, replica placement data, infrastructure topology data, and resource performance data. The job scheduler models a flow network that represents data content, software programs, physical devices, and communication capacity of the archive management system in various levels of vertices according to the received inputs. An optimal path in the modeled flow network is computed as an initial schedule, and the archive management system performs tasks according to the initial schedule. The operations of scheduled tasks are monitored and the job scheduler produces a new schedule based on feedbacks of the monitored operations and predefined heuristics.

The invention discloses a simulating design system for city expressway interchanges, comprising: data acquisition, model calibration, a data-out module, an evaluation and analysis module connecting with the model calibration module and data-out module respectively, and a data amendment module connecting between the evaluation and analysis module and the model calibration module. Meanwhile a model building and design method using the design system is disclosed too, which comprises: collecting the characteristic parameter of the traffic flow of typical expressway basic sections, interchange triage/confluence area, cutting area and various ramps; building the corresponding database and traffic capacity theoretical analysis model; demarcating and amending speed and density model with determinate service level; building traffic capacity analysis model suiting the traffic flow characteristic of the city expressway interchange. At last, the design of the lectotype of the city expressway interchanges conducted by the design model comprises analyzing and forecasting the traffic, raising a preliminary scheme, calculating the traffic capacity of the interchange, analyzing the suitability, selecting a rational strategy.

The invention relates to a shopping search recommending and alarming method and system and relates to the technical field of Internet. The method comprises the following steps: in a background pre-treatment stage, S101, capturing raw information from shopping websites by virtue of a crawler system; S102, directly storing the raw information so as to update a database center; S103, obtaining the sum X of negative comments according to a predefined semantic analysis model; S104, calculating the cheating rate P1; S105, calculating to obtain the sum Z of positive comments according to the predefined semantic analysis model; S106 calculating to obtain a recommendation level P3; storing the cheating rate P1 and the recommendation level P3 in the data center so as to update the data center; S109, providing information to the client by virtue of the search websites after the data center is updated in real time; S110, providing browsing for users by the client according to the cheating rate P1 and the recommendation level P3 provided. The interactive shopping search recommending system comprises a crawler system, a pre-treatment center, a data center and search and result display websites; the risk that the user is cheated in shopping is reduced.

A method for estimating a response time by combining metrics from networking and application layers. This is achieved by placing correlation tags in data collected at these layers so that the data can later be identified as corresponding to a single web page download or a web session. Once data corresponding to a single web page download or a web session is identified, a splicing algorithm calculates client perceived response time by using analytical models of response time.