نتایج جستجو برای: combined neural network
تعداد نتایج: 1181623 فیلتر نتایج به سال:
Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...
Land use classification and mapping mostly use remotely sensed data. During the past decades, several advanced classification methods such as neural network and support vector machine (SVM) have been developed. In the present study, Landsat TM images with 30m spatial resolution were used to classify land uses through two classification methods including support vector machine and neural network...
In a daily power market, price and load forecasting is the most important signal for the market participants. In this paper, an accurate feed-forward neural network model with a genetic optimization levenberg-marquardt back propagation (LMBP) training algorithm is employed for short-term nodal congestion price forecasting in different zones of a large-scale power market. The use of genetic algo...
Combining multiple neural networks appears to be a very promising approach for improving neural network generalization since it is very difficult, if not impossible, to develop a perfect single neural network. Therefore in this paper, a nonlinear model predictive control (NMPC) strategy using multiple neural networks is proposed. Instead of using a single neural network as a model, multiple neu...
We present an architecture for 3D-object recognition based on the integration of neural and semantic networks. The architecture consists of mainly two components. A neural object recognition system generates object hypotheses, which are veriied or rejected by a semantic network. Thus the advantages of both paradigms are combined: in the low level eld adaptivity and the ability to learn from exa...
Today for the expedition of the identification and timely correction of process deviations, it is necessary to use advanced techniques to minimize the costs of production of defective products. In this way control charts as one of the important tools for the statistical process control in combination with modern tools such as artificial neural networks have been used. The artificial neural netw...
In this paper, we propose a novel approach for evolving the architecture of a multi-layer neural network. Our method uses combined ART1 algorithm and Max-Min neural network to self-generate nodes in the hidden layer. We have applied the proposed method to the problem of recognizing ID number in identity cards. Experimental results with a real database show that the proposed method has better pe...
one of the most important issues always facing banks and financial institutes is the issue of credit risk or the possibility of failure in the fulfillment of obligations by applicants who are receiving credit facilities. the considerable number of banks’ delayed loan payments all around the world shows the importance of this issue and the necessary consideration of this topic. accordingly, many...
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