Diagnosis and Prognosis of Cardiovascular Diseases on the Basis of Neural Networks
A neural expert network system for diagnostis and prognosis of cardiovascular diseasas was developed.
The article presents a comparative analysis of neural network modeling and regression analysis for forecasting the S & P 500 index. Initially, the forecast of the absolute value of the index is provided, then we justify the use of stationery data, that is, the return of S & P 500. The comparison of two methods is carried out in two stages. Firstly methods are compared by the coefficient of determination on the periods of three and twelve months, and by the quality of trend predictions. Note that the choice of model and its testing is performed at different time intervals (the so-called in-sample and out-of-sample periods). Taking into account the fact that the primary desire of a typical trader is to gain a profit at the second stage we have chosen such trading criteria as profit and profit, weighted on risk (drawdown). On a longer time interval (12 months) regression shows the best results, but in terms of economic gains neural network win. When we consider a shorter period (3 months) neural network has better results. Thus, neural networks are able to assess the dynamics of the stock due to its flexibility and ability to find non-linear patterns.
On the Russian market of insurance services life insurance is one of the fastest growing segments. Identifying among the clients of the insurance company risk groups composed of individuals more prone to other termination of the contract of life insurance, allows to conduct purposeful work on their retention, which ultimately should lead to reduction of customer churn and, as a consequence, have a positive impact on the financial performance of the insurance company. The solution is achieved through the development of a model that predicts premature termination of life insurance contracts. In this work a comparative analysis of regression models and neural network models the termination of contracts of life insurance.
This proceedings publication is a compilation of selected contributions from the “Third International Conference on the Dynamics of Information Systems” which took place at the University of Florida, Gainesville, February 16–18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and academia in order to exchange new discoveries and results in a broad range of topics relevant to the theory and practice of dynamics of information systems. Dynamics of Information Systems: Mathematical Foundation presents state-of-the art research and is intended for graduate students and researchers interested in some of the most recent discoveries in information theory and dynamical systems. Scientists in other disciplines may also benefit from the applications of new developments to their own area of study.
The intellectual three-channel frequency-code converter with high vitality is considered. Autodiagnostics and autocalibration of converter are performed without current convertions interruption.
A form for an unbiased estimate of the coefficient of determination of a linear regression model is obtained. It is calculated by using a sample from a multivariate normal distribution. This estimate is proposed as an alternative criterion for a choice of regression factors.