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Investigation of Intelligent Technologies for Formation Forecasting Models
Author(s) -
E. Umamaheswari
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.2.14563
Subject(s) - computer science , fuzzy logic , block (permutation group theory) , information technology , data science , management science , risk analysis (engineering) , artificial intelligence , business , engineering , geometry , mathematics , operating system
Actually much attention is paid to the development of new intelligent information technologies for solving forecasting problems in different subject areas. The goal of solving the problem of forecasting dynamic indicators is in most cases to increase the effectiveness of making managerial decisions in conditions of uncertainty for complex distributed systems, which include economic entities. The modern global business environment dynamically forms new markets, which in turn require the use of new innovative technologies, without which it is impossible to have a competitive efficient economy in general and successful business groups in particular. In paper the research of intellectual information technologies of construction of predictive models on the basis of modified adaptive prediction methods is carried out: a neuro-network group method of  data handling and a hybrid genetic algorithm with fuzzy predictive block with the purpose of justification of their use for different subject areas. Exactly  these technologies  are relevant and promising for improving the accuracy of forecasts. 

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