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Volumn 2687, Issue , 2003, Pages 401-408

Neuro-fuzzy modeling applied to GIS: A case study for solar radiation

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURE; COMPUTATION THEORY; CONCRETES; GEOGRAPHIC INFORMATION SYSTEMS; IRRIGATION; SOFT COMPUTING; AGRICULTURAL ENGINEERING; COMPUTER SCIENCE; NEURAL NETWORKS; SOLAR ENERGY; SUN; WATER SUPPLY;

EID: 35248865715     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44869-1_51     Document Type: Article
Times cited : (1)

References (9)
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    • Piero Bonissone. Soft computing: The convergence of emerging reasoning techniques. Journal of Soft Computing, 1, 1997.
    • (1997) Journal of Soft Computing , vol.1
    • Bonissone, P.1
  • 2
    • 0004622087 scopus 로고    scopus 로고
    • Predicting irrigation water needs using soft computing techniques
    • Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics, Orlando, Florida. USA, July
    • J. A. Botía, A. Gómez-Skarmeta, A. Padilla, G. Sánchez, and M. Valdés. Predicting irrigation water needs using soft computing techniques. In Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics, volume VIII Computer Sciences and Engineering: Part II, pages 330-335, Orlando, Florida. USA, July 2000.
    • (2000) Computer Sciences and Engineering: Part II , vol.8 , pp. 330-335
    • Botía, J.A.1    Gómez-Skarmeta, A.2    Padilla, A.3    Sánchez, G.4    Valdés, M.5
  • 4
    • 0010135649 scopus 로고
    • FAO (Food and Agricuture Organization of the United Nations), Trainning Manual 3. Was available online
    • C. Brouwer and M. Heibloem. Irrigation Water Management: Irrigation Water Needs. FAO (Food and Agricuture Organization of the United Nations), 1986. Trainning Manual 3. http://www.fao.org/docrep/S2022E/s2022E00. htm (Was available online on January the first, 2001).
    • (1986) Irrigation Water Management: Irrigation Water Needs
    • Brouwer, C.1    Heibloem, M.2
  • 5
    • 84974743850 scopus 로고
    • Fuzzy model identification based on cluster estimation
    • S.L. Chiu. Fuzzy model identification based on cluster estimation. Journal of the Intelligent and Fuzzy Systems, 2(3):267-278, 1994.
    • (1994) Journal of the Intelligent and Fuzzy Systems , vol.2 , Issue.3 , pp. 267-278
    • Chiu, S.L.1
  • 6
    • 0035686903 scopus 로고    scopus 로고
    • Neural network models for predicting organic matter content in Saskatchewan soils
    • HR. Ingleby and T.G. Crowe. Neural network models for predicting organic matter content in Saskatchewan soils. Canadian BioSystems Engineering, 43(7), 2001.
    • (2001) Canadian BioSystems Engineering , vol.43 , Issue.7
    • Ingleby, H.R.1    Crowe, T.G.2
  • 7
    • 0027601884 scopus 로고
    • Anfis: Adaptive-network-based fuzzy inference systems
    • J.S. Jang. Anfis: Adaptive-network-based fuzzy inference systems. IEEE Trans. on Systems, Man, and Cybernetics, 23(03):665-685, 1993.
    • (1993) IEEE Trans. on Systems, Man, and Cybernetics , vol.23 , Issue.3 , pp. 665-685
    • Jang, J.S.1
  • 9
    • 35248841810 scopus 로고
    • Artificial Neural Networks in Agricultural Machinery Applications
    • Chicago, Illinois, ASAE
    • M. L. Stone and G. A. Kranzler. Artificial Neural Networks in Agricultural Machinery Applications. In ASAE Paper AETC 95052, Chicago, Illinois, 1995. ASAE.
    • (1995) ASAE Paper AETC 95052
    • Stone, M.L.1    Kranzler, G.A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.