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Chongqing, renowned as the Mountain City of China, is a place attracting numerous visitors from all over the world for its cultural heritage and natural beauty. The 8th International Conference on Natural Computation (ICNC'12) has come to this beautiful and lively city. Chongqing is to proudly host this important international forum, offering the city's best to all the participants.
As a multi-layer forwarding network, the back propagation neural network (BPNN) with manifold derived structures has been most widely used in artificial intelligence applications. Based on the given non-linear system and the BPNNs of varying internal structures, this paper quantitatively reports the findings in the correlation between the number of hidden layers and the BPNN performance. The selection...
A three layer artificial neural network model with the structure of 3×5×1 has been established by the MATLAB neural network toolbox to simulate the heat transfer coefficient of a novel evaporator for wheat straw black liquor — a three-phase circulating fluidized bed evaporator. The LM algorithm has been selected from four kinds of training functions: BFGS quasi-newton, LM, BR and GD by comparing their...
A soft sensor modeling method based on k-nearest neighbor and RBF neural network is presented to diminish the effects of outliers on the developed soft sensor model. Firstly, the anomaly degree of each modeling data pairs is calculated by using the k-nearest neighbor algorithm. Then, the weight of each modeling data pairs is determined according to the calculated anomaly degrees. Lastly, a soft sensor...
We propose an FPGA Array structure that is designed to the scalable structure for executing brain processes and numerical computation for 3-D problem, and the circuits in FPGA Array are controlled from the application program running in host PC directly. Many circuits for brain processes are designed to evaluate the 3-D FPGA, also we implement arithmetic circuits that calculate 2D Poisson equation...
Agricultural system is a typical complex system. However, available complexity science failed to reveal the essence of complex system. In this paper, based on a virtual reality of world and a new thermodynamic law, a novel model for evolution and evaluation of complex agricultural system is constructed. Basing on a simulation technique on how our world is just an image thrown up from the virtual realty,...
In this paper, a class of Cohen-Grossberg-type fuzzy neural networks with distributed delays and impulses is investigated. By employing differential inequality and M-matrix theory, some sufficient conditions ensuring the existence and global exponential stability of the periodic oscillatory solution for Cohen-Grossberg-type fuzzy neural networks with distributed delays and impulses are obtained. An...
In recent years, learning from imbalanced datasets has attracted much attention both in academic and industrial fields. The kernel modification method based on Riemannian metric is an effective method to handle the class imbalance problem. But it cannot deal with the outliers and noise in the imbalanced datasets. However, Fuzzy Support Vector Machine (FSVM) can deal with the outliers and noise in...
In this paper, a new fuzzy membership function for fuzzy support vector machine is presented. It provides an effective approach to deal with the over-fitting problem when outliers exist in the training data set. Combining with the concept of the K-nearest neighbor algorithm, we give a definition of the new fuzzy membership function. Then, fuzzy support vector machine with some improvements is successfully...
This paper propose a new method for wood recognition based on texture analysis. At first, wood texture images are divided into several blocks in our method. Secondly, wood features are extracted from these blocked grey-scale images using different mask, which is knows as higher-order local autocorrelation (HLAC). Finally, Support Vector Machine (SVM) was used to verify the performance of the method...
For the problems of fuzzy object's edges and computation complexity for video object segmentation, an improved SVM algorithm is proposed in this paper. We have adopted the adaptive change detection method to get the original video object, whose pixels constitute the samples set for SVM training, and then we improved the SVM by using the idea of active learning, and finally we built the video object...
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