Forecasting integrated circuit output using multivariate grey model and grey relational analysis

Expert Systems with Applications

Volumn 36, Issue 2 PART 1, 2009, Pages 1403-1409

  Hsu, Li Chang ^a   Wang, Chao Hung ^a  

^a LING TUNG UNIVERSITY   (Taiwan)

Author keywords

Forecasting; Grey relational analysis; Integrated circuit; Multivariate grey model

Indexed keywords

ECONOMIC ANALYSIS; FORECASTING; TECHNOLOGICAL FORECASTING; TIMING CIRCUITS;

FORECASTING TECHNIQUES; FUTURE RESEARCH DIRECTIONS; GREY RELATIONAL ANALYSIS; HIGH TECHNOLOGY INDUSTRIES; INTEGRATED CIRCUIT INDUSTRIES; MANAGERIAL IMPLICATIONS; MULTIVARIATE GREY MODEL; UNIVARIATE TIME SERIES;

INTEGRATED CIRCUITS;

EID: 56349105740     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.11.015     Document Type: Article

References (43)

1. Allen P.G., and Fields R.A. Econometric forecasting strategies and techniques. In: Armstrong J.S. (Ed). Principles of forecasting: A handbook for researchers and practioners (2001), Kluwer Academic Press, USA
2. Alvim C.F. Capital productivity: A further limitation to Brazilian growth. Economy and Energy 44 June-July (2004)
3. Andras T.L., and Srinivasan S.S. Advertising intensity and R&D intensity: Differences across industries and their impact on firm's performance. International Journal of Business and Economics 2 2 (2003) 167-176
4. Bidarkota P.V. The comparative forecast performance of univariate and multivariate models: An application to real interest rate forecasting. International Journal of Forecasting 14 4 (1998) 457-468
5. Bodyanskiy Y., and Popov S. Neural network approach to forecasting of quasiperiodic financial time series. European Journal of Operational Research 175 3 (2006) 1357-1366
6. Chen L.H., and Liaw S.Y. Investigating resource utilization and product competence to improve production management: An empirical study. International Journal of Operations and Production Management 21 9 (2001) 1180-1194
7. Davis J.H. An annual index of US industrial production, 1790-1915. Quarterly Journal of Economics 119 (2004) 1177-1215
8. Deng J.L. Control problems of grey systems. Systems and Control Letters 1 5 (1982) 288-294
9. Deng J.L. Introduction to grey system theory. The Journal of Grey System 1 1 (1989) 1-24
10. Dessyllas, P., & Hughes, A. (2005). R&D and patenting activity and the propensity to acquire in high technology industries. ESRC Centre for Business Research. University of Cambridge Working Paper No. 298.
11. Dobrzański L.A., Kowalski M., and Madejski J. Methodology of the mechanical properties prediction for the metallurgical products from the engineering steels using the artificial intelligence methods. Journal of Materials Processing Technology (2005) 1500-1509
12. Freitas P.S.A., and Rodrigues A.J.L. Model combination in neural-based forecasting. European Journal of Operational Research 173 3 (2006) 801-814
13. Fukao K., Ishido H., and Ito K. Vertical intra-industry trade and foreign direct investment inst East Asia. Journal of Japanese and International Economics 17 (2003) 468-506
14. Hsia K.H., and Wu J.H. A study on the data processing in grey relational analysis. Journal of Chinese Grey System 1 1 (1998) 47-53
15. Hsu C.I., and Wen Y.U. Improved grey prediction models for trans - pacific air passenger market. Transportation Planning and Technology 22 (1998) 87-107
16. Hsu C.I., and Wen Y.U. Application of grey theory and multiobjective programming towards airline network design. European Journal of Operational Research 127 (2000) 44-68
17. Hsu L.C. Applying the grey prediction model to the global integrated circuit industry. Technological Forecasting and Social Change 70 (2003) 563-574
18. Huang Y.P., Huang C.C., and Hung C.H. Determination of the preferred fuzzy variables and applications to the prediction control by the grey modeling. The Second National Conference on Fuzzy Theory and Application (1994) 406-409
19. Kendrick J.W. Understanding productivity (1997), Johns Hopkins University Press, Baltimore
20. Kermanshahi B., and Iwamiya H. Up to year 2020 load forecasting using neural nets. International Journal of Electrical Power and Energy Systems 24 9 (2002) 789-797
21. Law R., and Au N. A neural network model to forecast Japanese demand for travel to Hong Kong. Tourism Management 20 (1999) 89-97
22. Law R. Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting. Tourism Management 21 4 (2000) 331-340
23. Lewis C. Industrial and business forecasting methods (1982), Butterworth Scientific, London
24. Lin C.T., and Hsu P.F. Selection of advertising agencies using grey relational analysis and analytic hierarchy process. Journal of International Marketing and Marketing Research 26 3 (2001) 115-128
25. Malhorta N. Marketing research: An applied orientation. 3rd ed. (1999), Prentice-Hall, Sydney
26. Morán J., Granada E., Míguez J.L., and Porteiro J. Use of grey relational analysis to assess and optimize small biomass boilers. Fuel Processing Technology 87 2 (2006) 123-128
27. Nakamura E. Inflation forecasting using a neural network. Economics Letters 86 (2005) 373-378
28. Neslihan A. Notes on the merger strategy of high versus low-tech industries: Complementarities and moral hazard. Economics Bulletin 12 7 (2002) 1-12
29. Ong C.S., Huang J.J., and Tzeng G.H. A novel hybrid model for portfolio selection. Applied Mathematics and Computation 169 (2005) 1195-1210
30. Parantap B., Chandana C., and Derrick R. Liberalization, FDI, and growth in developing countries: A panel cointegration approach. Economic Inquiry 41 3 (2003) 510-516
31. Pereira M.F., Lanzer E.A., Silveira J.S., and Samohyl R.W. Productivity growth and technological progress in the Brazilian agricultural sector. Pesquisa Operacional 22 (2002) 133-146
32. Sharma K. How important is the processed food in intra-industry trade? The Australian experience. Journal of Economic Studies 29 2 (2002) 121-130
33. Strasheim J.J. Demand forecasting for motor vehicle spare parts (1992), University of Pretoria, South Africa
34. Streiner D.L., and Norman G.R. Health measurement scales: A practical guide to their development and use. 2nd ed. (1995), Oxford University Press, Oxford
35. Tae H.O. Alternative demand models and their elasticity estimates. Journal of Transport Economics and Policy 23 2 (1989) 163-187
36. Tseng, F. M., Tzeng, G. H., Yu, C. H., & Yuan, B. (1997). The comparison of four kinds of prediction methods: ARIMA, fuzzy time series, fuzzy regression time series and grey forecasting - an example of the prediction value forecast of machinery industry in Taiwan. 1997 Second National Conference on Grey Theory and Applications (Taiwan) (pp. 53-68).
37. Tzeng G.H., and Tsaur S.H. The multiple criteria evaluation of grey relation model. The Journal of Grey System 6 3 (1994) 87-104
38. Wang C.H. Predicting the tourism demand using fuzzy time series and hybird grey theory. Tourism Management 25 3 (2004) 367-374
39. Wang T.Y., and Huang C.Y. Improving forecasting performance by employing the Taguchi method. European Journal of Operational Research 176 2 (2007) 1052-1065
40. Young P. Technological growth curves - a comparison of forecasting models. Technological Forecasting and Social Change 44 (1993) 375-389
41. Zhang, J., Liu, X., & Shi, Y. (2004). The method of grey related analysis to multiple attribute decision making problems with interval numbers. The Forth Workshop on "Fuzzy Systems and Engineering".
42. Zhang K.H. Does foreign direct investment promote economic growth? Evidence from East Asia and Latin America. Contemporary Economic Policy 19 2 (2001) 175-185
43. Zhang G.P., and Qi M. Neural network forecasting for seasonal and trend time series. European Journal of Operational Research 160 2 (2005) 501-514