نتایج جستجو برای: artificial neural network and genetic programming
تعداد نتایج: 17059087 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...
production of highly viscous tar sand bitumen using steam assisted gravity drainage (sagd) with a pair of horizontal wells has advantages over conventional steam flooding. this paper explores the use of artificial neural networks (anns) as an alternative to the traditional sagd simulation approach. feed forward, multi-layered neural network meta-models are trained through the back-error-propaga...
The Intelligent Model for Stock Investment with Buffett Strategy, Classifier System, Neural Network and Linear Programming” was studied for developing an intelligent model which can learn more knowledge regarding to stock investment with artificial intelligence technology. Classifier system, neural network, fundamental financial investment factors and linear programming are the fundamental comp...
Predicting stock prices is complicated; various components, such as the general state of the economy, political events, and investor expectations, affect the stock market. The stock market is in fact a chaotic nonlinear system that depends on various political, economic and psychological factors. To overcome the limitations of traditional analysis techniques in predicting nonlinear patterns, ex...
the metal sheets play an important role in the mechanical design, particularly in the aerospace structures. the rivet connections are frequently used to connect these sheets. the riveting quality greatly influences the rupture of the rivet and the sheet. the various parameters affect the quality of this operation. in this paper, the optimization of the parameters contributing to the riveting qu...
background : in medical studies, when the joint prediction about occurrence of two events should be anticipated, a statistical bivariate model is used. due to the limitations of usual statistical models, other methods such as artificial neural network (ann) and hybrid models could be used. in this paper, we propose a hybrid artificial neural network-genetic algorithm (ann-ga) model to predictio...
background: the purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. methods: data from the second national health survey were considered in this investigation. this data includes the information of low back pain and its associated risk factors among iranian people aged 15 years a...
in this study the wavelet neural network (wnn) and artificial neural network (ann) were used to simulate barley breakage percentage in combine harvester. the models have been trained using the same data conditions. air temperature, thresher cylinder speed, distance between thresher cylinder and concave (back and forth) and the percentage of barely moisture were as the input variables. the resul...
Among artificial intelligence approaches, artificial neural networks (ANNs) and genetic algorithm (GA) are widely applied for modification of materials property in engineering science in large scale modeling. In this work artificial neural network (ANN) and genetic algorithm (GA) were applied to find the optimal conditions for achieving the maximum hardness of Al6061 reinforced by multiwall car...
estimating the final price of products is of great importance. for manufacturing companies proposing a final price is only possible after the design process over. these companies propose an approximate initial price of the required products to the customers for which some of time and money is required. here using the existing data of already designed transformers and utilizing the bayesian anal...
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