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Trondheim, Norway

Sormo F.,Verdande Technology
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

In the last two years, Verdande Technology has branched out from our first application in monitoring drilling operations of oil and gas wells to look at other use-cases of case-based reasoning (CBR). In particular, we have looked at monitoring applications that use real-time sensor data and require a person in the decision making loop. © Springer International Publishing Switzerland 2014.


Gundersen O.E.,Verdande Technology | Gundersen O.E.,Norwegian University of Science and Technology
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

Traditional sequence similarity measures have a high time complexity and are therefore not suitable for real-time systems. In this paper, we analyze and discuss properties of sequences as a step toward developing more efficient similarity measures that can approximate the similarity of traditional sequence similarity measures. To explore our findings, we propose a method for encoding sequence information as a vector in order to exploit the advantageous performance of vector similarity measures. This method is based on the assumption that events closer to a point of interest, like the current time, are more important than those further away. Four experiments are performed on both synthetic and real-time data that show both disadvantages and advantages of the method. © 2012 Springer-Verlag.


Patent
Verdande Technology | Date: 2012-11-21

The present invention provides a computer-implemented software tool that is adapted to listen continuously to data streams from a drilling operation and to process the data to generate a situation description for a current drilling situation in a form useful for automated continuous matching with a set of past cases stored in a knowledge database. The invention implements a case-based reasoning (CBR) approach to match the current drilling situation as defined by the situation description with one or more stored past cases having a degree of similarity above a predetermined threshold level. Matching cases are displayed to the drilling engineer as symbols on a case radar, allowing the drilling engineer to retrieve and view the details of a past case and take appropriate action based on drilling advice provided within the past case.


Patent
Verdande Technology | Date: 2013-10-17

Disclosed herein is a computer-implemented method in case-based reasoning, CBR, for creating components of a comparison agent for monitoring a situation, the method comprising: obtaining one or more parameter values and comparison information for each of a plurality of features of a case, wherein the comparison information of each feature defines a configuration of a computation unit; and creating, for each of the plurality of features, a computation unit in dependence on the obtained one or more parameter values and the comparison information of the feature, such that the created computation unit is configured to generate an output in dependence on the obtained one or more parameter values and the comparison information of the feature.


Patent
Verdande Technology | Date: 2013-10-17

Disclosed herein is a computer-implemented method of creating a new case in a case-based reasoning (CBR) system for monitoring a situation, the method comprising: determining a set of one or more cases from a plurality of cases in dependence on a received data stream comprising information on a monitored situation, wherein each case comprises information describing a problem and information describing a solution to the problem and the process of determining the set of one or more cases is performed without comparing the description of the problems of any of the plurality of cases with a previously generated current case comprising information describing the monitored situation; generating information describing a solution in dependence on information obtained from the determined set of one or more cases and/or in dependence on information received from a user interface; generating a current case comprising information describing the monitored situation in dependence on the received data stream; and generating a new case in dependence on the generated information describing a solution and the generated current case.

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