Method and apparatus for service level management, wherein business processes are composed of services. A state of the service is defined by one or more service parameters, and the service parameters depend upon performance of network components that support the service, e.g., component parameters. The state of the service may depend, for example, on a collection of service parameter values for availability, reliability, security, integrity and response time. A service level agreement is a contract between a supplier and a customer that identifies services supported by a network, service parameters for the services, and service levels (e.g., acceptable levels) for each service parameter.

Service level management

An automated system ( 100 ) and method for evaluating the probable impact of user-specified or system generated changes in business value drivers on the components of value, revenue, expense and capital change, of a commercial enterprise Value drivers are identified using predictive models that define the value drivers associated with each element of the enterprise After the causal value drivers are identified using causal models, the system completes a detailed valuation of the firm using predictive models to determine the relative impact of each causal value driver on the overall valuation The detailed valuation results are then used to define a probabilistic financial simulation model such as a Markov Chain Monte Carlo model The financial simulation model then analyzes the impact of user specified changes in value drivers on the components of value performance and optionally generates a list of recommended changes to value drivers that achieve a user specified financial goal

Detailed method of and system for modeling and analyzing business improvement programs

The present invention provides systems, methods, computer program products, and combinations and subcombinations thereof for scoring items based on user sentiment and for determining the proficiency of a predictor and for aiding an investment decision on an item by an individual. The invention includes one or more user devices and a prediction system server having a sentiment rating module, a user proficiency ranking module, a content creation module, and a database. Devices access the prediction system server directly via a communications medium or indirectly through links provided on a third party server.

System, method, and computer program product for scoring items based on user sentiment and for determining the proficiency of predictors

An Aviation Weather Awareness and Reporting Enhancements (AWARE) system provides situational awareness by effectively filtering, analyzing and visualizing aviation weather data and specific hazard alerts in preflight, in-cockpit and controller applications. The AWARE system includes a temporal-spatial databases that filters weather data and a Bayesian network that assesses specific hazards in the filtered weather data in the context of pilot preferences, aircraft properties and airport properties. The filtered weather data and hazard alerts are then displayed on a client.

Aviation weather awareness and reporting enhancements (AWARE) system using a temporal-spatial weather database and a bayesian network model

A system and method for assessing risk, monitoring risk, and managing caseloads of individuals under risk assessment is provided. The system includes a network server computer that stores into memory information regarding each individual's environment, behavior, physical condition, personal relationships, and/or mental state of being. Similar information regarding other individuals associated with the individual being assessed for risk also may be stored in the server memory. Individuals under risk assessment, individuals associated with individuals under risk assessment, and workers responsible for overseeing individuals under risk assessment may input this information into the server memory. The server processes this information for input into a risk assessment application that may include a fuzzy logic, neural network, neuro-fuzzy, or other artificial intelligence software or hardware to compute a composite risk score. The system provides workers an alarm signal when an individual's assessed score exceeds a predetermined level. The system provides workers an alarm signal when an assessed score of an individual exceeds a predetermined level or falls into a predetermined classification category. Worker caseloads are automatically updated and/or prioritized by the system in accordance with alarm signals present in the server database. The system and method also provide individuals accessing the system with helpful resources based on information they provide the system server, and a means for communication between system users.

Method and system for dynamic risk assessment, risk monitoring, and caseload management

System and method for improving the performance of learning agents such as neural networks, genetic algorithms and decision trees that derive prediction methods from a training set of data. In part of the method, a population of learning agents of different classes is trained on the data set, each agent producing in response a prediction method based on the agent's input representation. Feature combinations are extracted from the prediction methods produced by the learning agents. The input representations of the learning agents are then modified by including therein a feature combination extracted from another learning agent. In another part of a method, the parameter values of the learning agents are changed to improve the accuracy of the prediction method. A fitness measure is determined for each learning agent based on the prediction method the agent produces. Parameter values of a learning agent are then selected based on the agent's fitness measure. Variation is introduced into the selected parameter values, and another learning agent of the same class is defined using the varied parameter values. The learning agents are then again trained on the data set to cause a learning agent to produce a prediction method based on the derived feature combinations and varied parameter values.

System and method for combining multiple learning agents to produce a prediction method

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System and method for combining multiple learning agents to produce a prediction method