35 results about "Rule based inference" patented technology

A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and / or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

The present invention provides systems and methods for dynamic detection and prevention of electronic fraud and network intrusion using an integrated set of intelligent technologies. The intelligent technologies include neural networks, multi-agents, data mining, case-based reasoning, rule-based reasoning, fuzzy logic, constraint programming, and genetic algorithms. The systems and methods of the present invention involve a fraud detection and prevention model that successfully detects and prevents electronic fraud and network intrusion in real-time. The model is not sensitive to known or unknown different types of fraud or network intrusion attacks, and can be used to detect and prevent fraud and network intrusion across multiple networks and industries.

A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and / or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and / or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

A method for providing recommendations to a user based on user activity. A plurality of activity data tracking a plurality of activities of a user is obtained. The activity data may be obtained over a wide area network such as the internet or downloaded from a data card which stores activity data whenever the user participates in an activity. The activity data is either stored on the data card or transmitted over the network whenever the user uses a card when participating in any activity such as when making a purchase of goods, paying for services, watching television, etc. The activity data is processed to identify a plurality of user patterns. The user patterns are used to form a user profile and may include user habit data. Recommendations specific to the user based on the user patterns are then created for and provided to the user. The recommendations are provided to a user when the user logs onto a computer network such as the internet. The recommendations may also be provided by electronic mail, electronic pager or other methods. The recommendations are provided by various data analysis techniques including rule based inference engines and other forms of artificial intelligence.

A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and / or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

A method and system for adding processes to print production workflows utilizing asset metadata and automated reasoning system is disclosed. The asset metadata can be extracted from the resources associated with a print product description such as PDF files and image and artwork files. The asset metadata can be processed through an automated reasoning system in order to infer additional metadata. The inferred metadata can be utilized to add and parameterize a process node in order to build a more effective and useful process network. The reasoning system can be a rule based reasoning system and / or ontology based reasoning system.

The invention relates to a track profile irregularity amplitude estimation method employing optimal belief rules based inference. According to the method, the mapping relationship between parametric variable input and yield output is modeled by a belief rule base. A corresponding change relationship between vibration frequency domain characteristic data of different measurement points and a track profile irregularity amplitude is described by building the belief rule base. By a sequence linear programming method, an initial belief rules based (BRB) model is optimized through limited historical data; and the effects on the model caused by subjective factors are reduced. According to the sequence linear programming (SLP) method, a nonlinear optimization problem of an original model is converted into a step-by-step linear optimization problem; and various parameters of the optimization model can be relatively simply and rapidly calculated, so that the track profile irregularity amplitude can be accurately and rapidly estimated through belief inference under the condition of given vibration frequency domain characteristic. According to the track profile irregularity amplitude estimation method, the estimation accuracy and the calculation efficiency of the model are improved; and the method has the advantage of being relatively efficient on a track profile irregularity system which needs to be monitored in real time.