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Volumn 24, Issue 3, 2003, Pages 323-330

A comparison of three different approaches to tourist arrival forecasting

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; FORECASTING METHOD; TOURISM MANAGEMENT; TRAVEL DEMAND;

EID: 0041813336     PISSN: None     EISSN: 02615177     Source Type: Journal    
DOI: 10.1016/S0261-5177(02)00068-7     Document Type: Article
Times cited : (237)

References (13)
  • 3
    • 26444565569 scopus 로고
    • Finding structure in time
    • Elamn, J. L. (1990). Finding structure in time. Cognitive Science, 14, 179-211.
    • (1990) Cognitive Science , vol.14 , pp. 179-211
    • Elamn, J.L.1
  • 7
    • 0042323898 scopus 로고    scopus 로고
    • Performance of Neural Networks in managerial forecasting
    • R. R. Trippi, and E. Turban (Eds.), Revisited Edn Chicago: IRWIN
    • Jhee, W. C., & Lee, J. K. (1996). Performance of Neural Networks in managerial forecasting. In R. R. Trippi, & E. Turban (Eds.), Neural Networks in finance and investing, Revisited Edn (pp. 703-733). Chicago: IRWIN.
    • (1996) Neural Networks in Finance and Investing , pp. 703-733
    • Jhee, W.C.1    Lee, J.K.2
  • 11
    • 0003510257 scopus 로고    scopus 로고
    • World Tourism Organization Spain: Madrid
    • World Tourism Organization (1996). Tourism 2020 vision. Spain: Madrid.
    • (1996) Tourism 2020 Vision


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.