13 research outputs found

    Web-based CBR (case-based reasoning) as a tool with the application to tooling selection

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    Over the past few years, manufacturing companies have had to deal with an increasing demand for feature-rich products at low costs. The pressures exerted on their existing manufacturing processes have lead manufacturers to investigate internet-based solutions, in order to cope with growing competition. The decentralisation phenomenon also came up as a reason to implement networked-application, which has been the starting point for internet/intranet–based systems. Today, the availability of powerful and low cost 3D tools, database backend systems, along with web-based technologies, provides interesting opportunities to the manufacturing community, with solutions directly implementable at the core of their businesses and organisations. In this paper a web-based engineering approach is presented to developing a design support system using case-based reasoning (CBR) technology for helping in the decision-making process when choosing cutting tools. The system aims to provide on-line intelligent support for determining the most suitable configuration for turning operations, based on initial parameters and requirements for the cutting operation. The system also features a user-driven 3D turning simulator which allows testing the chosen insert for several turning operations. The system aims to be a useful e-manufacturing tool being able to quickly and responsively provide tooling data in a highly interactive way

    Knowledge maintenance in myCBR

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    CBR systems, being knowledge based systems, process knowledge. Due to changes in the environment a CBR system’s knowledge model can become outdated, thus creating a need for constant maintenance of said knowledge model. In this paper, we describe an implementation of (semi-)automatic knowledge maintenance of two of the four knowledge containers of CBR systems, specifically case base maintenance and maintenance of similarity measures within the CBR system development SDK myCBR. We describe our approach to create, elicit and manage quality measures that are used to trigger maintenance actions if the quality measures fall below defined thresholds, indicating a declining efficiency/accuracy of a case base or particular similarity measure. We further detail on the implementation of our approach into myCBR Workbench to enable a knowledge engineer to incorporate the notion of maintenance already at the design stage of a CBR system. The approach relies on the notion of maintenance attributes to be able to measure the quality of case bases and similarity measures. Initial experiments using the newly introduced quality measurement attributes indicate that our approach is promising

    Learning to assess from pair-wise comparisons

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    In this paper we present an algorithm for learning a function able to assess objects. We assume that our teachers can provide a collection of pairwise comparisons but encounter certain difficulties in assigning a number to the qualities of the objects considered. This is a typical situation when dealing with food products, where it is very interesting to have repeatable, reliable mechanisms that are as objective as possible to evaluate quality in order to provide markets with products of a uniform quality. The same problem arises when we are trying to learn user preferences in an information retrieval system or in configuring a complex device. The algorithm is implemented using a growing variant of Kohonen’s Self-Organizing Maps (growing neural gas), and is tested with a variety of data sets to demonstrate the capabilities of our approac

    Maintenance d'un système de raisonnement à partir de cas.

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    International audienceLa maintenance des systèmes de Raisonnement à partir de cas intéresse un certain nombre de travaux, dont nous dressons un état de l'art. Parmi les méthodes déployées ayant trait particulièrement à la maintenance de la base de cas, nous situons notre contribution dans la réduction de la base de cas, et plus particulièrement sur une stratégie de suppression de cas basée sur un critère : la compétence. Une mesure est proposée inspirée des travaux existant dans la littérature et est illustrée par un premier test fait sur une base de 69 cas

    Case Base Maintenance Approach.

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    International audienceCase base Maintenance is an active Case Based Reasoning research area. The main stream focuses on the method for reducing the size of the case-base while maintaining case-base competence. This paper gives an overview of these works, and proposes a case deletion strategy based on competence criteria using a novel approach. The proposed method, even if inspired from existing literature, combines an algorithm with a Competence Metric (CM). A series of tests are conducted using two standards data-sets as well as a locally constructed one, on which, three Case Base Maintenance approaches were tested. This experimental study shows how this technique compares favourably to more traditional strategies across two standard data-sets

    The use of machine learning algorithms for the study of business profitability : a new approach based on preferences

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    In recent years, researchers in the Field of Artificial Intelligence have developed a learning technique, namely, preference learning, that is suitable to be used for economic analysis. The present research empirically tests one of these models, which consists of a combination of LACE and RFE algorithms. The problem of forecasting the profitability of Spanish companies upon the basis of a set of financial ratios is used as a benchmark. The model provides forecasted rankings, which are a kind of information that is more useful for the economic analysts than the forecasted class memberships that traditional machine learning techniques provide.En los últimos años, investigadores del campo de la Inteligencia Artificial han desarrollado una técnica de aprendizaje llamada “aprendizaje de referencia”, que puede usarse para el análisis económico. Esta investigación pone a prueba de manera empírica uno de estos modelos, que consiste en la combinación de algoritmos LACE y RFE. El problema de investigar los posibles beneficios de compañías españolas por encima de la base de un set de ratios financieros se usa como limitación. El modelo proporciona rankings pronosticados, los cuales son un tipo de información que es más útil para los analistas económicos que para los miembros que las técnicas que el aprendizaje tradicional proporciona

    The Use Of Machine Learning Algorithms for the Study of Business Profitability A New Approach Based on Preferences

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    Internet-enabled fixture design system using case-based reasoning technology

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    Master'sMASTER OF ENGINEERIN
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