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TREE-TYPE IRRIGATION PIPE NETWORK PLANNING USING AN IMPROVED BAT ALGORITHM.

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Title: TREE-TYPE IRRIGATION PIPE NETWORK PLANNING USING AN IMPROVED BAT ALGORITHM.
Authors: Lyu, S.1, Wu, B.2, Li, Z.3 lizhen@scau.edu.cn, Hong, T.4, Wang, J.1, Huang, Y.2
Source: Transactions of the ASABE. 2019, Vol. 62 Issue 2, p447-459. 13p.
Subjects: Pipe, Water distribution, Irrigation, Water supply, Bats, Irrigation water, Algorithms
Abstract: A tree-type irrigation pipe network has a substantial role in saving water. To address the pipe network planning problem, an improved model is proposed by comprehensively considering the effects of various pipe network layouts and pipe diameters on the investment cost. The model can guarantee the water supply connectivity using the concept of highlevel water nodes. Meanwhile, an improved self-adaptive bat algorithm with step-controlled and mutation mechanisms is proposed herein. The performance of the proposed algorithm is examined using 12 unimodal and multimodal functions. The experimental results reveal that the improved bat algorithm can effectively avoid local optima and exhibits high solution accuracy. Moreover, planning experiments are performed on the two pipe network cases. Results reveal that the proposed pipe network planning using the improved bat algorithm has a good precision and extendibility. [ABSTRACT FROM AUTHOR]
Copyright of Transactions of the ASABE is the property of American Society of Agricultural & Biological Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 136124702
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Label: Title
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  Data: TREE-TYPE IRRIGATION PIPE NETWORK PLANNING USING AN IMPROVED BAT ALGORITHM.
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  Data: <searchLink fieldCode="AR" term="%22Lyu%2C+S%2E%22">Lyu, S.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Wu%2C+B%2E%22">Wu, B.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Li%2C+Z%2E%22">Li, Z.</searchLink><relatesTo>3</relatesTo><i> lizhen@scau.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Hong%2C+T%2E%22">Hong, T.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Wang%2C+J%2E%22">Wang, J.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Huang%2C+Y%2E%22">Huang, Y.</searchLink><relatesTo>2</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Transactions+of+the+ASABE%22">Transactions of the ASABE</searchLink>. 2019, Vol. 62 Issue 2, p447-459. 13p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Pipe%22">Pipe</searchLink><br /><searchLink fieldCode="DE" term="%22Water+distribution%22">Water distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Irrigation%22">Irrigation</searchLink><br /><searchLink fieldCode="DE" term="%22Water+supply%22">Water supply</searchLink><br /><searchLink fieldCode="DE" term="%22Bats%22">Bats</searchLink><br /><searchLink fieldCode="DE" term="%22Irrigation+water%22">Irrigation water</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: A tree-type irrigation pipe network has a substantial role in saving water. To address the pipe network planning problem, an improved model is proposed by comprehensively considering the effects of various pipe network layouts and pipe diameters on the investment cost. The model can guarantee the water supply connectivity using the concept of highlevel water nodes. Meanwhile, an improved self-adaptive bat algorithm with step-controlled and mutation mechanisms is proposed herein. The performance of the proposed algorithm is examined using 12 unimodal and multimodal functions. The experimental results reveal that the improved bat algorithm can effectively avoid local optima and exhibits high solution accuracy. Moreover, planning experiments are performed on the two pipe network cases. Results reveal that the proposed pipe network planning using the improved bat algorithm has a good precision and extendibility. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Transactions of the ASABE is the property of American Society of Agricultural & Biological Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.13031/trans.12885
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      – Code: eng
        Text: English
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        PageCount: 13
        StartPage: 447
    Subjects:
      – SubjectFull: Pipe
        Type: general
      – SubjectFull: Water distribution
        Type: general
      – SubjectFull: Irrigation
        Type: general
      – SubjectFull: Water supply
        Type: general
      – SubjectFull: Bats
        Type: general
      – SubjectFull: Irrigation water
        Type: general
      – SubjectFull: Algorithms
        Type: general
    Titles:
      – TitleFull: TREE-TYPE IRRIGATION PIPE NETWORK PLANNING USING AN IMPROVED BAT ALGORITHM.
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            NameFull: Wang, J.
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              Text: 2019
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              Y: 2019
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              Value: 62
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