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Fuzzy linear regression and its applications to forecasting in uncertain environment. (English) Zbl 0566.62099
Linear regression has been used for many years in developing mathematical models for application in marketing, management, and sales forecasting. In this paper, two different sales forecasting techniques are discussed.
The first technique involves non-fuzzy abstract methods of linear regression and econometrics. A study of the international market sales of cameras, done in 1968 by J. S. Armstrong [Long-range forecasting for a consumer durable in an international market. Diss. MIT (1968)], utilized these non-fuzzy forecasting techniques. The second sales forecasting technique uses fuzzy linear regression introduced by H. Tanaka, S. Uejima and K. Asai [see IEEE Trans. Syst. Man Cybern. SMC-12, 903-907 (1982; Zbl 0501.90060)].
In this paper, a study of the computer and peripheral equipment sales in the United States is discussed using fuzzy linear regression. Moreover, fuzzy linear regression is applied to forecasting in an uncertain environment. Finally, some possible improvements and suggestions for further study are mentioned.

62P20 Applications of statistics to economics
Full Text: DOI
[1] Armstrong, S.J., Long-range forecasting for a consumer durable in an international market, Diss. MIT, (1968)
[2] Armstrong, S.J., Long-range forecasting from crystal ball to computer, (1978), John Wiley & Sons New York
[3] (), 66-75
[4] Bails, D.G.; Peppers, L.C., Business fluctuations: forecasting techniques and applications, (1982), Prentice-Hall New York
[5] Byte, July-December, 1977-1981.
[6] ()
[7] Datapro survey of the microcomputers, (1982)
[8] Dixon, W.J., BMDP statistical software (biomedical programs), (1981), University of California Press
[9] Economic report of the president, (1966-1982)
[10] Electronics, Vol. 55, No. 1, 124, (January 13, 1982)
[11] Fieldman, L., Minis in small business, (), 58-64
[12] Gross, C.W.; Peterson, R.T., Business forecasting, (1976), Houghton Miffin Company Boston
[13] Grumman, G.S.; Cowen, (), 154, (11)
[14] Ingwerson, M., Mathematics goes soft around the edges, The Christian science monitor, 810-811, (June 24, 1981)
[15] Kandel, A.; Byatt, W.J., Fuzzy sets, fuzzy algebra, and fuzzy statistics, (), 1619-1639, (12)
[16] Mead, C.; Conway, L., Introduction to VLSI systems, (1978), Addison-Wesley Reading, MA
[17] Miller, F.W., Desk-top computers are for real, Datamation, 27, 5, 58-62, (1981)
[18] Miller, F.W., Small business computers Mean business, Datamation, 28, 6, 54-60, (1982)
[19] Payne, J., Minicomputers: big bucks from small systems, Datamation, 25, 5, 118, (1979)
[20] Platt, J.R., Strong inference, Science, 146, 347-353, (October 1964)
[21] Standard and poors, industry report, Vol. 1 and Vol. 2, (1974-1982)
[22] Tanaka, H.; Uejima, S.; Asai, K., Fuzzy linear regression model, IEEE trans. systems man cybernet., 10, 4, 2933-2938, (1980)
[23] Tanaka, H.; Uejima, S.; Asai, K., Linear regression analysis with fuzzy model, IEEE trans. systems man cybernet., 12, 6, 903-907, (1982) · Zbl 0501.90060
[24] (), 12-24
[25] Wiegner, K.K., Tomorrow has arrived, Forbes, (February 15, 1982)
[26] Wright, P., The datamation 100, Datamation, 26, 6, 96, (1981)
[27] Zadeh, L.A., Fuzzy sets, inform. and control, 8, 338-353, (1965) · Zbl 0139.24606
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