Abstract: Patterns of change in system operating parameters are identified which may be used to identify unexpected operational conditions and to trigger an appropriate alert or action. A network is controlled using operating data for the network. Network operating data is received and divided into sequential time periods. A structural description such as an association rule is determined for the received data in each time period and a change pattern in the determined structural description is identified over the time periods. The network is then controlled using a predetermined action corresponding to a predetermined structural description change pattern in response to the identified structural description change pattern matching the predetermined structural description change pattern.

Abstract: The performance of a computer-controlled system (1) operating under the control of a first process (2), is monitored (4) by comparison (5) with a predetermined set of requirements (15, 25), to identify whether the performance of the system (1) meets the predetermined requirements. If the performance does not meet those requirements, an alternative program (22) may be selected, or generated from program elements stored in a library (60), to replace the current controller process (2).

Abstract: The present invention relates to identifying patterns of change in system operating parameters which may be used to identify unexpected operational conditions and to trigger an appropriate alert or action. The present invention provides a method (300) for controlling a network (350) using operating data for the network, the method comprising: receiving the network operating data (110); dividing the received data into sequential time periods (305); determining a structural description such as an association rule for the received data in each time period (310); identifying a change pattern in the determined structural description over the time periods (315); controlling the network (325) using a predetermined action corresponding to a predetermined structural description change pattern in response to the identified structural description change pattern matching the predetermined structural description change pattern (320).

Abstract: The performance of a computer-controlled system (1) operating under the control of a first process (2), is monitored (4) by comparison (5) with a predetermined set of requirements (15, 25), to identify whether the performance of the system (1) meets the predetermined requirements. If the performance does not meet those requirements, an alternative program (22) may be selected, or generated from program elements stored in a library (60), to replace the current controller process (2).

Abstract: Data from a monitoring system is analyzed for monitoring characteristics of a dynamic system. Characteristic data in respect of a dynamic system is monitored and provided with at least one known normal state. Characteristic data is received from a monitoring system and confirmation information from an operator when the dynamic system is in a known normal state. A normality model is derived including comprising data indicative of known normal states in response to received characteristic data and confirmation information. Future characteristic data is predicted from the normality model a difference function is provided indicating an acceptable difference between predicted and received characteristic data. Predicted characteristic data is compared with received characteristic data in conjunction with the difference function and an abnormality signal is produced if the difference exceeds the difference function.

Abstract: Data analysis methods are characterized in terms of tangible and non-tangible parameters such as user-friendliness, accuracy, simplicity, interpretability, speed, cost, comprehensibility, and transparency, and then matched to pre-specified requirements. A data analysis method is selected in accordance with a user preference, wherein the user preference relates to a feature of the data analysis method and is represented by a fuzzy set comprising a range of values.

Abstract: Methods and systems for analysing data from a monitoring system for monitoring characteristics of a dynamic system, said monitoring system providing characteristic data in respect of a dynamic system with at least one known normal state, the analysis system comprising: means (100) for receiving characteristic data from the monitoring system, means (101) for receiving confirmation information from an operator when the dynamic system is in a known normal state, normality modelling means (105) for deriving a normality model comprising data indicative of known normal states in response to received characteristic data and confirmation information, prediction generating means (105) for predicting future characteristic data from the normality model, difference function providing means (105) for providing a difference function indicating an acceptable difference between predicted and received characteristic data, and comparison means (105) for comparing predicted characteristic data with received characteristic data

Abstract: With known systems, when performing analysis of data, users typically have a solution-oriented view: there is a problem, and data has been collected with a view to providing some information about the problem. Usually a method is selected, based on vague knowledge about some feature of the problem. This is often sub-optimal, because the user can be assumed to be an expert in the application area, but not in data analysis. Embodiments of the invention provide a means of characterising data analysis methods in terms of tangible and non-tangible parameters such as user-friendliness, accuracy, simplicity, interpretability, speed, cost, comprehensibility, and transparency, and then matching these to some pre-specified requirements. This means is provided by a method of selecting a data analysis method in accordance with a user preference, wherein the user preference relates to a feature of the data analysis method and is represented by a fuzzy set comprising a range of values.