The ultrasonic sensor is the most replied sensor in mobile robot to get environmental information and avoid obstacles. In fact, this type of sensors offers satisfactory results with affordable cost. However, one senso...
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The ultrasonic sensor is the most replied sensor in mobile robot to get environmental information and avoid obstacles. In fact, this type of sensors offers satisfactory results with affordable cost. However, one sensor is insufficient for a better perception of the environment. In this paper we opt for the conception of an ultrasonic sensor network to extract as much information as possible for measuring the distance between the robot and the obstacle. The algorithm for distance calculation is based on the measurement of the time of flight for the ultrasonic wave. The experimental results show a good performance of the conceived system for the distinction between different shapes of obstacles.
The purpose of this paper is to provide a path for designing a tool for decision support to ensure the effectiveness of Quality Management system (QMS). For this, we propose a Fuzzy-Neural Networks (FNN) approach for ...
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The purpose of this paper is to provide a path for designing a tool for decision support to ensure the effectiveness of Quality Management system (QMS). For this, we propose a Fuzzy-Neural Networks (FNN) approach for improving the efficiency of such system. The aim of this approach is to classify the objectives for a real-world case study which presents a major problem for controlling the quality levels of its production lines. This approach provided a significant improvement when the testing data are various or complex.
There are many areas where objects with very complex and sometimes interdependent features are to be classified; similarities and dissimilarities are to be evaluated. This makes a complex decision model difficult to c...
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There are many areas where objects with very complex and sometimes interdependent features are to be classified; similarities and dissimilarities are to be evaluated. This makes a complex decision model difficult to construct effectively. This paper presents a Hierarchical Fuzzy Signatures (HFS) approach for improving the effectiveness and efficiency of quality-management system (QMS). The goal is to classify the objectives for a real-world case study. The latter was chosen because it presents a major problem for controlling the quality levels of its production lines. With the use of this fuzzy signature structure, complex decision models in the quality management field should be able to be constructed more effectively. In fact, this study provides a path for designing a tool for decision support to ensure the effectiveness of a corporate QMS.
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