Assessing seawater quality with a variable fuzzy recognition model
With the rapid development of the marine economy industry, human exploitation of marine resources is increasing, which is contributing to the growing trend of eutrophication and frequent occurrence of red tide. Accordingly, investigations of seawater quality have attracted a great deal of attention....
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| Veröffentlicht in: | Chinese journal of oceanology and limnology 2014-05, Vol.32 (3), p.645-655 |
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| container_title | Chinese journal of oceanology and limnology |
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| creator | 柯丽娜 王权明 盖美 周惠成 |
| description | With the rapid development of the marine economy industry, human exploitation of marine resources is increasing, which is contributing to the growing trend of eutrophication and frequent occurrence of red tide. Accordingly, investigations of seawater quality have attracted a great deal of attention. This study was conducted to construct a seawater environmental quality assessment model based on the variable fuzzy recognition model. The uncertainty and ambiguity of the seawater quality assessment were then considered, combining the monitoring values of evaluation indicators with the standard values of seawater quality. Laizhou Bay was subsequently selected for a case study. In this study, the correct variable model for different parameters was obtained according to the linear and nonlinear features of evaluation objects. Application of the variable fuzzy recognition model for Laizhou Bay, water quality evaluation and comparison with performance obtained using other approaches revealed that the generated model is more reliable than traditional methods, can more reasonably determine the water quality of various samples, and is more suitable for evaluation of a multi-index, multi-level, nonlinear marine environment system; accordingly, the generated model will be an effective tool for seawater quality evaluation. |
| doi_str_mv | 10.1007/s00343-014-3117-3 |
| format | Article |
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Application of the variable fuzzy recognition model for Laizhou Bay, water quality evaluation and comparison with performance obtained using other approaches revealed that the generated model is more reliable than traditional methods, can more reasonably determine the water quality of various samples, and is more suitable for evaluation of a multi-index, multi-level, nonlinear marine environment system; accordingly, the generated model will be an effective tool for seawater quality evaluation.</description><identifier>ISSN: 0254-4059</identifier><identifier>ISSN: 2096-5508</identifier><identifier>EISSN: 1993-5005</identifier><identifier>EISSN: 2523-3521</identifier><identifier>DOI: 10.1007/s00343-014-3117-3</identifier><language>eng</language><publisher>Heidelberg: Springer-Verlag</publisher><subject>algal blooms ; Bays ; case studies ; Chemical analysis ; Earth and Environmental Science ; Earth Sciences ; Economic development ; Environmental quality ; Environmental quality assessment ; Eutrophication ; Evaluation ; humans ; industry ; Marine ; Marine conservation ; Marine environment ; Marine resources ; monitoring ; Oceanography ; Physics ; Quality assessment ; Quality control ; Red tide ; Red tides ; Seawater ; uncertainty ; Underwater resources ; Water analysis ; Water quality ; 可变 ; 模型评价 ; 模糊识别模型 ; 水体富营养化 ; 海水水质 ; 海洋经济 ; 质量评价模型 ; 非线性特性</subject><ispartof>Chinese journal of oceanology and limnology, 2014-05, Vol.32 (3), p.645-655</ispartof><rights>Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag Berlin Heidelberg 2014</rights><rights>Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag Berlin Heidelberg 2014.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c399t-15eb7fc2c411e56b268414db69e5b7217b0748d53f2eaab763e5863acd1769383</citedby><cites>FETCH-LOGICAL-c399t-15eb7fc2c411e56b268414db69e5b7217b0748d53f2eaab763e5863acd1769383</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/84119X/84119X.jpg</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1520554821/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1520554821?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21386,21387,21388,21389,23254,27922,27923,33528,33701,33742,34003,34312,43657,43785,43803,43951,44065,64383,64387,72239,73874,74053,74072,74243,74360</link.rule.ids></links><search><creatorcontrib>柯丽娜 王权明 盖美 周惠成</creatorcontrib><title>Assessing seawater quality with a variable fuzzy recognition model</title><title>Chinese journal of oceanology and limnology</title><addtitle>Chin. J. Ocean. Limnol</addtitle><addtitle>Chinese Journal of Oceanology and Limnology</addtitle><description>With the rapid development of the marine economy industry, human exploitation of marine resources is increasing, which is contributing to the growing trend of eutrophication and frequent occurrence of red tide. Accordingly, investigations of seawater quality have attracted a great deal of attention. This study was conducted to construct a seawater environmental quality assessment model based on the variable fuzzy recognition model. The uncertainty and ambiguity of the seawater quality assessment were then considered, combining the monitoring values of evaluation indicators with the standard values of seawater quality. Laizhou Bay was subsequently selected for a case study. In this study, the correct variable model for different parameters was obtained according to the linear and nonlinear features of evaluation objects. Application of the variable fuzzy recognition model for Laizhou Bay, water quality evaluation and comparison with performance obtained using other approaches revealed that the generated model is more reliable than traditional methods, can more reasonably determine the water quality of various samples, and is more suitable for evaluation of a multi-index, multi-level, nonlinear marine environment system; accordingly, the generated model will be an effective tool for seawater quality evaluation.</description><subject>algal blooms</subject><subject>Bays</subject><subject>case studies</subject><subject>Chemical analysis</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Economic development</subject><subject>Environmental quality</subject><subject>Environmental quality assessment</subject><subject>Eutrophication</subject><subject>Evaluation</subject><subject>humans</subject><subject>industry</subject><subject>Marine</subject><subject>Marine conservation</subject><subject>Marine environment</subject><subject>Marine resources</subject><subject>monitoring</subject><subject>Oceanography</subject><subject>Physics</subject><subject>Quality assessment</subject><subject>Quality control</subject><subject>Red tide</subject><subject>Red tides</subject><subject>Seawater</subject><subject>uncertainty</subject><subject>Underwater resources</subject><subject>Water analysis</subject><subject>Water quality</subject><subject>可变</subject><subject>模型评价</subject><subject>模糊识别模型</subject><subject>水体富营养化</subject><subject>海水水质</subject><subject>海洋经济</subject><subject>质量评价模型</subject><subject>非线性特性</subject><issn>0254-4059</issn><issn>2096-5508</issn><issn>1993-5005</issn><issn>2523-3521</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kEtP3DAUhS0EUgfKD-iKVN10k_ZeP-J4CagvCYkFsLaczE0wysSMnYCGX1-PgirUBYuru_m-o6PD2CeEbwigvycAIUUJKEuBqEtxwFZojCgVgDpkK-BKlhKU-cCOU3rItJFgVuziPCVKyY99kcg9u4lisZ3d4Kdd8eyn-8IVTy561wxUdPPLy66I1IZ-9JMPY7EJaxo-sqPODYlOX_8Ju_v54_byd3l1_evP5flV2QpjphIVNbpreSsRSVUNr2qJct1UhlSjOeoGtKzXSnScnGt0JUjVlXDtGnVlRC1O2Ncl9zGG7UxpshufWhoGN1KYk0XFpUQBIDP65T_0IcxxzO32FCgla46ZwoVqY0gpUmcfo9-4uLMIdr-qXVa1eVW7X9WK7PDFSZkde4pvkt-Rzhapc8G6Pvpk7254BiCfqfW-yufXKvdh7Lc5-V8XaRRWQqD4C4-pjQg</recordid><startdate>20140501</startdate><enddate>20140501</enddate><creator>柯丽娜 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| subjects | algal blooms Bays case studies Chemical analysis Earth and Environmental Science Earth Sciences Economic development Environmental quality Environmental quality assessment Eutrophication Evaluation humans industry Marine Marine conservation Marine environment Marine resources monitoring Oceanography Physics Quality assessment Quality control Red tide Red tides Seawater uncertainty Underwater resources Water analysis Water quality 可变 模型评价 模糊识别模型 水体富营养化 海水水质 海洋经济 质量评价模型 非线性特性 |
| title | Assessing seawater quality with a variable fuzzy recognition model |
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