By Sarah Jane Delany, Pádraig Cunningham, Alexey Tsymbal, Lorcan Coyle (auth.), Professor Ann Macintosh BSc, CEng, Richard Ellis BSc, MSc, Dr Tony Allen (eds.)
APPLICATIONS AND concepts IN clever structures XII
The papers during this quantity are the refereed software papers provided at AI-2004, the Twenty-fourth SGAI overseas convention on cutting edge recommendations and functions of man-made Intelligence, held in Cambridge in December 2004.
The papers current new and cutting edge advancements within the box, divided into sections on Synthesis and Prediction, Scheduling and seek, prognosis and tracking, category and layout, and research and Evaluation.
This is the twelth quantity within the functions and strategies sequence. The sequence serves as a key reference at the use of AI expertise to let businesses to unravel complicated difficulties and achieve major enterprise benefits.
The Technical flow papers are released as a significant other quantity below the name learn and improvement in clever structures XXI.
Read Online or Download Applications and Innovations in Intelligent Systems XII: Proceedings of AI-2004, the Twenty-fourth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence PDF
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Extra info for Applications and Innovations in Intelligent Systems XII: Proceedings of AI-2004, the Twenty-fourth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
The data consisted solely of globally weighted Boolean features, and each case was measured across the same features in query and case base (no contrast). It is expected that the modified methods (especially MCR) would be more useful when the data representation is more complex. The features selected are under review also, as is the most appropriate way to weight the features. An important consideration in this domain is that time stamping crime is difficult as the time of occurrence, for instance of a burglary or motor vehicle theft, may not be known exactly.
Binary logistic regression with the * Single victimisations* and 'First in a series of victimisations*^ as the dependent groups were executed with the set of crime scene variables of Tables 1 and 2. e. within 365 days), the use of force, searching behaviour, type of property, place of entry, place of exit, alarm activation and use of bogus official strategy are discriminating features. In this way we are able to identify the features of a 'first' burglary which are predictive of a revictimisation.
It is expected that the modified methods (especially MCR) would be more useful when the data representation is more complex. The features selected are under review also, as is the most appropriate way to weight the features. An important consideration in this domain is that time stamping crime is difficult as the time of occurrence, for instance of a burglary or motor vehicle theft, may not be known exactly. Therefore, it is useful to view crime events as singularities of variable length along the time line.