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In this research, the combination of modal data is used to identify the damage of a FEM model using neural networks. The identification ability with different levels of noise and incomplete mode shapes are also investigated. It has been proved that the neural network using combination of modal parameters as input has a excellent identification ability with ideal error tolerance and robustness. Numberical...
This paper describes slide-bending formation of metallic sheet by using a neural network. The formation of parts made of very thin metallic sheets has become increasingly important miniaturizing industrial products, including electrical and mechanical devices. One of the authors proposed a new method called a slide-bending formation method for the bending of the metallic sheet. In this method, the...
Detecting the point in time where a dynamic fitness landscape changes is vital for a considerable number of diversity management schemes that used in evolutionary algorithms employed for solving dynamic optimization problems. Here, we introduce a change detector based on principles of artificial immune systems, namely a negative selection algorithm. We show in numerical experiments that such an immunological...
Recently a new method for recognition of isolated handwritten Persian digits, based on support vector machines (SVMs), has been introduced. In this research, this method was implemented for the same task with three new modifications, i.e. only one popular shape was considered for digits written in different shapes; sizes of glyphs normalized to digit boundaries; MLP (multi-layer perceptron), SVM/MLP...
Detecting and tracking fingertips are significant techniques for recognizing hand gestures. Many patterns and skin color information are used to extract and trace features. However, to find correct shapes is difficult and there is limitation to express the diversity of models. In this paper, we describe a method of detecting and tracking fingertips based on Active Shape Models (ASMs) and an ellipse...
This paper introduces a non-temporal multiple silhouettes in Hidden Markov Model (HMM) for offering view independent human posture recognition. The multiple silhouettes are used to reduce the ambiguity problem of posture recognition. A simple feature extraction of the 2D shape contour based histogram is used for image encoding and K-Means algorithm is applied for clustering and code-wording of eight...
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