@ARTICLE{26583204_63252641_2012, 
	author = {Y. Kuznetsov}, 
	keywords = {, Model of the initial data, optimum digitization of the data, optimum data base parameters, forecastpredicting operators},
	title = {Forecasting of economic processes on the definition basis of their optimum base parameters.},
	journal = {},
	year = {2012},
	number = {3(21)},
	pages = {17-23},
	url = {https://bijournal.hse.ru/en/2012--3(21)/63252641.html},
	publisher = {},
	abstract = {Yegor Kuznetsov - Postgraduate Student, Department of Computer Technologies in Design and Manufacturing, Institute of Radio Electronics and Information Technologies, Nizhniy Novgorod State Technical University n.a. R.E. Alekseev.Address: 24, Minina str., Nizhny Novgorod, 603950, Russian Federation.E-mail: yegor_s@rambler.ruAccording to the estimations of Russian and foreign specialists, nowadays there are more than a hundred methods of prediction. This fact gives rise to the problem of selecting a method which would provide correct predictions for studied systems and their processes. The experience shows that the difficulty of implementation of a particular method can be assessed if we have a clear mathematical description - a mathematical model of a particular method, expressed, for instance, in a linguistic form as a prediction operator.In practical researches the following functions are used as prediction operator: linear (ARMA, ARIMA), quadratic, power, exponential, logistic models. These models do not allow predicting all the processes, though in some cases they can be replaced by a linear combination of harmonic or other functions. Consequently, one of the objectives of the paper is to propose and prove a universal method that does not require the use of combinations of harmonic and linear functions .The research results if formulating a new prediction method of economic temporary series based on preliminary optimal sampling of initial data. In the context of his method, a predictive model of the operator was chosen under which its parameters would be consistent with each other, and could be identified by a universal criterion of specially introduced optimal basic parameters.The research studies key features of the new method as well as the algorithms of prediction  based on determining the most suitable basic parameters of processes, optimally sampled in terms of level and time into time series. It is shown that the information prediction systems, developed on the basis of the proposed method, can effectively predict the economic processes.The proposed method has worked well on the tasks of predicting series, in which a priori information does not allow to draw conclusions about the functional dependence of the predicted value on the previous ones. In the cases where there is a priori information (e.g. information on a seasonal component), "classic", more popular methods of forecasting should be used, allowing to take this information into account. },
	annote = {Yegor Kuznetsov - Postgraduate Student, Department of Computer Technologies in Design and Manufacturing, Institute of Radio Electronics and Information Technologies, Nizhniy Novgorod State Technical University n.a. R.E. Alekseev.Address: 24, Minina str., Nizhny Novgorod, 603950, Russian Federation.E-mail: yegor_s@rambler.ruAccording to the estimations of Russian and foreign specialists, nowadays there are more than a hundred methods of prediction. This fact gives rise to the problem of selecting a method which would provide correct predictions for studied systems and their processes. The experience shows that the difficulty of implementation of a particular method can be assessed if we have a clear mathematical description - a mathematical model of a particular method, expressed, for instance, in a linguistic form as a prediction operator.In practical researches the following functions are used as prediction operator: linear (ARMA, ARIMA), quadratic, power, exponential, logistic models. These models do not allow predicting all the processes, though in some cases they can be replaced by a linear combination of harmonic or other functions. Consequently, one of the objectives of the paper is to propose and prove a universal method that does not require the use of combinations of harmonic and linear functions .The research results if formulating a new prediction method of economic temporary series based on preliminary optimal sampling of initial data. In the context of his method, a predictive model of the operator was chosen under which its parameters would be consistent with each other, and could be identified by a universal criterion of specially introduced optimal basic parameters.The research studies key features of the new method as well as the algorithms of prediction  based on determining the most suitable basic parameters of processes, optimally sampled in terms of level and time into time series. It is shown that the information prediction systems, developed on the basis of the proposed method, can effectively predict the economic processes.The proposed method has worked well on the tasks of predicting series, in which a priori information does not allow to draw conclusions about the functional dependence of the predicted value on the previous ones. In the cases where there is a priori information (e.g. information on a seasonal component), "classic", more popular methods of forecasting should be used, allowing to take this information into account. }
}