نتایج جستجو برای: interval prediction neural networks
تعداد نتایج: 1045591 فیلتر نتایج به سال:
This study evaluates the performance of feed-forward neural networks to model and forecast recovery rates of defaulted bank loans. In order to guarantee that the predictions are mapped into the unit interval, the neural networks are implemented with a logistic activation function in the output neuron. The statistical relevance of explanatory variables is assessed using the bootstrap technique. ...
Simultaneous spectrophotometric estimation of Fluoxetine and Sertraline in tablets were performed using UV–Vis spectroscopic and Artificial Neural Networks (ANN). Absorption spectra of two components were recorded in 200–300 (nm) wavelengths region with an interval of 1 nm. The calibration models were thoroughly evaluated at several concentration levels using the spectra of synthetic binary mix...
the proposed iafc neural networks have both stability and plasticity because theyuse a control structure similar to that of the art-1(adaptive resonance theory) neural network.the unsupervised iafc neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. this fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. the supervised iafc ...
One of the most important issues in designing coastal and offshore structures is the prediction of wave and current forces on slender cylinders. Such forces are often considered as dominate loadings. Many analytical and empirical methods such as Morison equation have been suggested for estimation of waves and current forces. Such methods, however, have shown inaccuracies in predicting hydrodyna...
The problem of optimal portfolio selection has attracted a great attention in the finance and optimization field. The future stock price should be predicted in an acceptable precision, and a suitable model and criterion for risk and the expected return of the stock portfolio should be proposed in order to solve the optimization problem. In this paper, two new criterions for the risk of stock pr...
Artificial Neural Networks are information processing systems. Over the past several years, these algorithms have received much attention for their applications in pattern completing, pattern matching and classification and also for their use as a tool in various areas of problem solving. In this work, an Artificial Neural Network model is presented for predicting the tensile properties of co...
Introduction: The features of a cell can be extracted from its gene expression profile. If the gene expression profiles of future descendant cells are predicted, the features of the future cells are also predicted. The objective of this study was to design an artificial neural network to predict gene expression profiles of descendant cells that will be generated by division/differentiation of h...
Gas hydrate formation in production and transmission pipelines and consequent plugging of these lines have been a major flow-assurance concern of the oil and gas industry for the last 75 years. Gas hydrate formation rate is one of the most important topics related to the kinetics of the process of gas hydrate crystallization. The main purpose of this study is investigating phenomenon of gas hyd...
This paper presents the prediction of vehicle's velocity time series using neural networks. For this purpose, driving data is firstly collected in real world traffic conditions in the city of Tehran using advance vehicle location devices installed on private cars. A multi-layer perceptron network is then designed for driving time series forecasting. In addition, the results of this study are co...
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