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This paper is concerned with a new architecture of an optimized FCM-based interval type-2 fuzzy neural network classifier developed with aid of Fuzzy C-Means (FCM) clustering and Particle Swarm Optimization (PSO). The premise part of the rules of this architecture is realized by two FCM clustering algorithms. These FCM clustering algorithms run for several values of the fuzzification coefficient subsequently...
In this paper we introduce a method for classifying terrains and for predicting friction coefficient on terrains by applying visual information. Coefficient of friction on a terrain is very important for autonomous mobile robots in driving on road and traversing over obstacle. Our algorithm is based on terrain classification for visual image. To predict friction coefficient from given image, we divide...
A wireless networked multi-site triaxial accelerometry system has been devised to estimate activity energy expenditure during daily life. A notable feature of the devised system is the utilisation of activity classification based on multi-site acceleration signals. During performance evaluation tests on a single subject, the proposed method showed higher correlation (adjusted R2 = 0.952) and smaller...
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