The adaptation of membership functions in a fuzzy system is a nonlinear optimization problem. Thus, the convergence of online learning algorithms is questionable. We demonstrate the convergence problems by analyzing t...
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The adaptation of membership functions in a fuzzy system is a nonlinear optimization problem. Thus, the convergence of online learning algorithms is questionable. We demonstrate the convergence problems by analyzing two types of spikes, the narrow basis function spikes and the non-monotonic basis function spikes, which can occur during the online adaptation. Further, we show how these spikes can be avoided by restricting the parameter variations of the widths and the distances of the membership functions. According to these restrictions we have to conclude that in most cases it is better solely to adapt the rule conclusions than to adapt the membership functions.
Neural network technology applications in automatic control system for laser welding are considered, fundamental concepts of neural network are outlined. Attention is drowning to the design of adaptive control of lase...
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ISBN:
(纸本)085296708X
Neural network technology applications in automatic control system for laser welding are considered, fundamental concepts of neural network are outlined. Attention is drowning to the design of adaptive control of laser welding technological process. Structural scheme of automatic control system is presented together with control algorithm.
Calculating surface vapor pressures of volatile inorganic components, nitric acid, hydrochloric acid and ammonia, is essential for modeling condensation and evaporation processes occurring in atmospheric aerosols. The...
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Calculating surface vapor pressures of volatile inorganic components, nitric acid, hydrochloric acid and ammonia, is essential for modeling condensation and evaporation processes occurring in atmospheric aerosols. The vapor pressure of these compounds depends on temperature, relative humidity, phase state, and particle composition, and their calculation consumes an enormous amount of computer time in Eulerian photochemical/aerosol models. Here we use a thermodynamic model to generate a large set of vapor pressure data as a function of aerosol composition, relative humidity, and temperature. These data are then used as a training set for neural networks. Once the networks memorize the data, interpolation of vapor pressures for intermediate compositions, temperatures and relative humidities is automatic. The neural network models are able to reproduce the values predicted by the thermodynamic models accurately and are 4-1200 times faster depending on atmospheric conditions and the assumptions employed in the thermodynamic calculations. Copyright (C) 1996 Elsevier Science Ltd.
The reproduction of color across different media and viewing condition requires color-appearance modeling. In order to obtain an effective and efficient mapping of color appearance, the authors define here a method to...
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The reproduction of color across different media and viewing condition requires color-appearance modeling. In order to obtain an effective and efficient mapping of color appearance, the authors define here a method to approximate the combination of the forward and reverse Hunt94 color-appearance models. The method consists in learning by examples the Hunt94 color mapping for each desired experimental setup. Learning is done by feed-forward neural networks trained with the back-propagation algorithm on training sets derived from the ANSI IT8 7.2 color target. Experimental results confirm the feasibility of the method. (C) 1997 John Wiley & Sons, Inc. Inc.
Artificial neural networks back-propagation algorithm was applied to the prediction of vibration frequencies of v1 and v2 modes of octahedral hexahalide (MX6(n-)). Three-layer networks with one and two output nodes we...
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Artificial neural networks back-propagation algorithm was applied to the prediction of vibration frequencies of v1 and v2 modes of octahedral hexahalide (MX6(n-)). Three-layer networks with one and two output nodes were used. Two inertia terms and training step controlling scheme were adopted to weights adjustment. The result of one output node networks has little difference from that of two output nodes networks. The frequencies of [Mof6]2-, [BiF6]- and [AuF6]- from literature are a great deal different from those calculated or predicted values.
The glass-forming region in the Sm-Si-Al-O-N system at 1700 degrees C was studied by using an artificial neural network (ANN). An artificial neural network (ANN) was trained and tested with fifty experimentally determ...
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The glass-forming region in the Sm-Si-Al-O-N system at 1700 degrees C was studied by using an artificial neural network (ANN). An artificial neural network (ANN) was trained and tested with fifty experimentally determined examples in the investigated system with a back-propagation algorithm. The results of all forty-two examples of the training set and the testing set of eight obtained from the ANN are in good agreement with experiments. The glass-forming boundaries on the planes of 25, 27.5, 30, 32.5, 35 and 40 eq% N were predicted with the trained network, which indicates the tendency of contraction towards the Si-rich region with increasing nitrogen content. The approach shows a considerable promise for applications to determination of nonlinear boundaries of glass-forming regions in complex material systems, in cases where thermodynamic calculations of phase equilibria are not effective.
In this paper, the popular training method back-propagation (BP) of Nueral Networks (NN) is modified by introducing two parameters into the procedure in order to speed learning and improve the convergence. The modifie...
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In this paper, the popular training method back-propagation (BP) of Nueral Networks (NN) is modified by introducing two parameters into the procedure in order to speed learning and improve the convergence. The modified algorithm is named as BPGM and is successfully used in forecasting the future pollution generation and the investment demand for the environment protection in China. Based on the predication of NN model, the future situation of environment of China is analyzed and the investment in environment protection is compared with the average level of the world. Some policies suggestions are proposed.
The performance of neural networks on control of a heating plant is investigated in this paper. back-propagation algorithm is used to train the network and the effect of training parameters to network performance is a...
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A variation of the back-propagation algorithm is described, using a log-likelihood cost function. Appropriate choices of learning parameters are discussed. An example is given where the range of initial weights leadin...
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A variation of the back-propagation algorithm is described, using a log-likelihood cost function. Appropriate choices of learning parameters are discussed. An example is given where the range of initial weights leading to proper convergence is increased, and the number of iterations required is significantly reduced.
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