The Experts below are selected from a list of 20763 Experts worldwide ranked by ideXlab platform

Jesus Garcia - One of the best experts on this subject based on the ideXlab platform.

  • the application of deep models in Industrial Expert systems
    Expert Systems With Applications, 1991
    Co-Authors: J Cardenosa, F Alonso, J Castellanos, Jesus Garcia
    Abstract:

    Abstract This article differentiates between the four main knowledge levels of a human Expert: namely, structural, conceptual, heuristic, and epistemological knowledge. The conceptual relationships between these various types of knowledge are constituent elements of the deep knowledge encountered in Industrial systems. We present advice as to how to recognize such deep knowledge in order to produce a better quality knowledge base. Finally, a prototype developed in a Industrial area is describe, in which the components that affirm the existence of deep knowledge are identified, detailing the concepts mentioned above.

J Cardenosa - One of the best experts on this subject based on the ideXlab platform.

  • the application of deep models in Industrial Expert systems
    Expert Systems With Applications, 1991
    Co-Authors: J Cardenosa, F Alonso, J Castellanos, Jesus Garcia
    Abstract:

    Abstract This article differentiates between the four main knowledge levels of a human Expert: namely, structural, conceptual, heuristic, and epistemological knowledge. The conceptual relationships between these various types of knowledge are constituent elements of the deep knowledge encountered in Industrial systems. We present advice as to how to recognize such deep knowledge in order to produce a better quality knowledge base. Finally, a prototype developed in a Industrial area is describe, in which the components that affirm the existence of deep knowledge are identified, detailing the concepts mentioned above.

J Castellanos - One of the best experts on this subject based on the ideXlab platform.

  • the application of deep models in Industrial Expert systems
    Expert Systems With Applications, 1991
    Co-Authors: J Cardenosa, F Alonso, J Castellanos, Jesus Garcia
    Abstract:

    Abstract This article differentiates between the four main knowledge levels of a human Expert: namely, structural, conceptual, heuristic, and epistemological knowledge. The conceptual relationships between these various types of knowledge are constituent elements of the deep knowledge encountered in Industrial systems. We present advice as to how to recognize such deep knowledge in order to produce a better quality knowledge base. Finally, a prototype developed in a Industrial area is describe, in which the components that affirm the existence of deep knowledge are identified, detailing the concepts mentioned above.

F Alonso - One of the best experts on this subject based on the ideXlab platform.

  • the application of deep models in Industrial Expert systems
    Expert Systems With Applications, 1991
    Co-Authors: J Cardenosa, F Alonso, J Castellanos, Jesus Garcia
    Abstract:

    Abstract This article differentiates between the four main knowledge levels of a human Expert: namely, structural, conceptual, heuristic, and epistemological knowledge. The conceptual relationships between these various types of knowledge are constituent elements of the deep knowledge encountered in Industrial systems. We present advice as to how to recognize such deep knowledge in order to produce a better quality knowledge base. Finally, a prototype developed in a Industrial area is describe, in which the components that affirm the existence of deep knowledge are identified, detailing the concepts mentioned above.

Xavier Hamery - One of the best experts on this subject based on the ideXlab platform.

  • Industrial Expert system acquired by machine learning
    Applied Artificial Intelligence, 1994
    Co-Authors: Mouna El Attar, Xavier Hamery
    Abstract:

    Abstract This paper describes SERP, an Expert system for repairing helicopter blades, Although very useful, it cannot evolve automatically with advances in technology and Expert knowledge. To address this problem, we have designed an inductive learning system ( MEA) that uses rules or preclassified examples in order to incrementally build production rules. These rules are of the following form: if description of the fault & xrArr; repair and can be used by KEE ( knowledge engineering environment), an Expert system generator. Both MEA and SERP use a representation based on structured objects. In this paper some aspects of MEA will be described, and the way MEA can extend andlor improve the iterative dichotomiier ( ID3) algorithm will be explained. MEA has been tested on a real-life application concerning the repairing of helicopter blades. Results show that it is efficient, simple to use, and helpful to the Expert.