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Architectural Study on Undergraduate Teaching System of Hydrology and Water Resources Major

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Knowledge Discovery and Data Mining

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 135))

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Abstract

Hydrology and water resource engineering major is a new-opened major in our university in 2008. So we need constantly study and research it on new major of basic education, practice education, modification and formulation of teaching plan, location of training objective and direction, and course offered.

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References

  1. Li, D., Li, F.-B., Fang, X.-F.: Discussion on the Practice Teaching for the Specialty of Hdrology and Water Resources Engineering. Journal of Shijazhuang University of Economics 31, 127–129 (2008)

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  2. Zhou, X.: Some Ideas on the Modification of Undergraduate Programs of the Speciality of Hydrology and Water Resources Engineering. Chinese Geological Education (1), 56–581 (2005)

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  3. Wang, M., Gao, Z.-J.: Teaching and Reforming on Professional English for Hydrogeology Specialty. Chinese Geological Education (4), 162–164 (2009)

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  4. Dou, M., Zuo, Q.-T., Li, G.-Q.: The Course Construction and Teaching Study of Water Resources Planning and Management. Journal of Architectural Education in Institutions of Higher Learning (6), 91–93 (2008)

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Author information

Authors and Affiliations

  1. School of Earth and Environment and Foreign Languages, Anhui University of Science and Technology, Huainan, 232001, China

    Xiaolong Li, Jinxiang Yang & Xiaojun Zhang

Authors
  1. Xiaolong Li
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  2. Jinxiang Yang
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  3. Xiaojun Zhang
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Corresponding author

Correspondence to Xiaolong Li .

Editor information

Editors and Affiliations

  1. , School of Electronic Engineering, Wuhan Institute of Technology, Lvting yajing 10-3-102, Wuhan, 430079, China, People's Republic

    Honghua Tan

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© 2012 Springer-Verlag GmbH Berlin Heidelberg

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Li, X., Yang, J., Zhang, X. (2012). Architectural Study on Undergraduate Teaching System of Hydrology and Water Resources Major. In: Tan, H. (eds) Knowledge Discovery and Data Mining. Advances in Intelligent and Soft Computing, vol 135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27708-5_45

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  • DOI: https://doi.org/10.1007/978-3-642-27708-5_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27707-8

  • Online ISBN: 978-3-642-27708-5

  • eBook Packages: EngineeringEngineering (R0)

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