IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v260y2015icp170-187.html
   My bibliography  Save this article

A hybrid PSO optimized SVM-based method for predicting of the cyanotoxin content from experimental cyanobacteria concentrations in the Trasona reservoir: A case study in Northern Spain

Author

Listed:
  • Nieto, P.J. García
  • Fernández, J.R. Alonso
  • Suárez, V.M. González
  • Muñiz, C. Díaz
  • García-Gonzalo, E.
  • Bayón, R. Mayo

Abstract

There is an increasing need to describe cyanobacteria blooms since some cyanobacteria produce toxins termed cyanotoxins and, as a result, anticipate its presence is a matter of importance to prevent risks. Cyanobacteria blooms occur frequently and globally in water bodies, and they are a major concern in terms of their effects on other species such as plants, fish and other microorganisms, but especially by the possible acute and chronic effects on human health due to the potential danger from cyanobacterial toxins produced by some of them in recreational or drinking waters. Therefore, the aim of this study is to build a cyanotoxin diagnostic model by using support vector machines (SVMs) in combination with the particle swarm optimization (PSO) technique from cyanobacterial concentrations determined experimentally in the Trasona reservoir (recreational reservoir used as a high performance training center of canoeing in the Northern Spain). The Trasona reservoir is near Aviles estuary and after a short tour, the brackish waters of the Aviles estuary empty into the Cantabrian sea. This optimization technique involves kernel parameter setting in the SVM training procedure, which significantly influences the regression accuracy. Bearing this in mind, cyanotoxin contents have been predicted here by using the hybrid PSO–SVM-based model from the remaining measured water quality parameters (input variables) in the Trasona reservoir (Northern Spain) with success. In other words, the results of the present study are two-fold. In the first place, the significance of each biological and physical–chemical variable on the cyanotoxin content in the reservoir is presented through the model. Second, a predictive model able to forecast the possible presence of cyanotoxins is obtained. The agreement of the PSO–SVM-based model with experimental data confirmed its good performance. Finally, conclusions of this innovative research work are exposed.

Suggested Citation

  • Nieto, P.J. García & Fernández, J.R. Alonso & Suárez, V.M. González & Muñiz, C. Díaz & García-Gonzalo, E. & Bayón, R. Mayo, 2015. "A hybrid PSO optimized SVM-based method for predicting of the cyanotoxin content from experimental cyanobacteria concentrations in the Trasona reservoir: A case study in Northern Spain," Applied Mathematics and Computation, Elsevier, vol. 260(C), pages 170-187.
    • Handle: RePEc:eee:apmaco:v:260:y:2015:i:c:p:170-187
    DOI: 10.1016/j.amc.2015.03.075
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300315003896
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2015.03.075?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. AfDB AfDB, . "The AfDB Statistics Pocketbook 2007," AfDB Statistics Pocketbook, African Development Bank, number 2 edited by Koua Louis Kouakou.
    2. N/A, 2007. "Statistical Appendix," National Institute Economic Review, National Institute of Economic and Social Research, vol. 199(1), pages 126-126, January.
    3. J. Vilán Vilán & J. Alonso Fernández & P. García Nieto & F. Sánchez Lasheras & F. de Cos Juez & C. Díaz Muñiz, 2013. "Support Vector Machines and Multilayer Perceptron Networks Used to Evaluate the Cyanotoxins Presence from Experimental Cyanobacteria Concentrations in the Trasona Reservoir (Northern Spain)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3457-3476, July.
    4. N/A, 2007. "Statistical Appendix," National Institute Economic Review, National Institute of Economic and Social Research, vol. 199(1), pages 126-135, January.
    5. Zeng, Jianwu & Qiao, Wei, 2013. "Short-term solar power prediction using a support vector machine," Renewable Energy, Elsevier, vol. 52(C), pages 118-127.
    6. -, 2007. "Major statistical publications: abstracts," Sede Subregional de la CEPAL para el Caribe (Estudios e Investigaciones) 27648, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    7. N/A, 2007. "Statistical appendix," National Institute Economic Review, National Institute of Economic and Social Research, vol. 201(1), pages 119-128, July.
    8. N/A, 2007. "Statistical Appendix," National Institute Economic Review, National Institute of Economic and Social Research, vol. 200(1), pages 118-127, April.
    9. Hamid Safavi & Mahdieh Esmikhani, 2013. "Conjunctive Use of Surface Water and Groundwater: Application of Support Vector Machines (SVMs) and Genetic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2623-2644, May.
    10. AfDB AfDB, . "Selected Statistics on African Countries 2007," Selected Statistics on African Countries, African Development Bank, number 75 edited by Koua Louis Kouakou.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lahmiri, Salim, 2018. "Minute-ahead stock price forecasting based on singular spectrum analysis and support vector regression," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 444-451.
    2. Xuejiao Ma & Dandan Liu, 2016. "Comparative Study of Hybrid Models Based on a Series of Optimization Algorithms and Their Application in Energy System Forecasting," Energies, MDPI, vol. 9(8), pages 1-34, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. García Nieto, P.J. & García-Gonzalo, E. & Sánchez Lasheras, F. & de Cos Juez, F.J., 2015. "Hybrid PSO–SVM-based method for forecasting of the remaining useful life for aircraft engines and evaluation of its reliability," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 219-231.
    2. Nane, Gabriela F. & Larivière, Vincent & Costas, Rodrigo, 2017. "Predicting the age of researchers using bibliometric data," Journal of Informetrics, Elsevier, vol. 11(3), pages 713-729.
    3. Lyons Russell, 2011. "The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis," Statistics, Politics and Policy, De Gruyter, vol. 2(1), pages 1-29, May.
    4. Xing-Fang Huang & Ting Zhang & Yang Yang & Tao Jiang, 2017. "Ruin Probabilities in a Dependent Discrete-Time Risk Model With Gamma-Like Tailed Insurance Risks," Risks, MDPI, vol. 5(1), pages 1-14, March.
    5. Feng, Runhuan & Jing, Xiaochen, 2017. "Analytical valuation and hedging of variable annuity guaranteed lifetime withdrawal benefits," Insurance: Mathematics and Economics, Elsevier, vol. 72(C), pages 36-48.
    6. Ching-Sung Wu & Chih-Sheng Hsu, 2013. "Linking International High-Tech New Ventures' Firm Life Cycle To Internationalization, Organizational Learning, And Alliance Networks," Journal of Enterprising Culture (JEC), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 175-197.
    7. Dan Pirjol & Lingjiong Zhu, 2016. "Discrete Sums of Geometric Brownian Motions, Annuities and Asian Options," Papers 1609.07558, arXiv.org.
    8. Shi, Li., 2008. "Rural migrant workers in China : scenario, challenges and public policy," ILO Working Papers 994204063402676, International Labour Organization.
    9. Xu Bai & Jinxi Wu & Yun Liu & Yihan Xu, 2020. "Research on the impact of global innovation network on 3D printing industry performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1015-1051, August.
    10. Shujie Yao & Dan Luo & Stephen Morgan, 2008. "Shanghai Stock Exchange Composite Index and Bank Stock Prices in China: A Causality Analysis," Discussion Papers 08/25, University of Nottingham, GEP.
    11. Liang, Xiaoqing & Tsai, Cary Chi-Liang & Lu, Yi, 2016. "Valuing guaranteed equity-linked contracts under piecewise constant forces of mortality," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 150-161.
    12. Pirjol, Dan & Zhu, Lingjiong, 2016. "Discrete sums of geometric Brownian motions, annuities and Asian options," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 19-37.
    13. C. Iglesias & J. Martínez Torres & P. García Nieto & J. Alonso Fernández & C. Díaz Muñiz & J. Piñeiro & J. Taboada, 2014. "Turbidity Prediction in a River Basin by Using Artificial Neural Networks: A Case Study in Northern Spain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 319-331, January.
    14. Rashidi, S. & Bovand, M. & Abolfazli Esfahani, J., 2015. "Structural optimization of nanofluid flow around an equilateral triangular obstacle," Energy, Elsevier, vol. 88(C), pages 385-398.
    15. Mico Apostolov, 2016. "Cobb–Douglas production function on FDI in Southeast Europe," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 5(1), pages 1-28, December.
    16. T. Fowe & I. Nouiri & B. Ibrahim & H. Karambiri & J. Paturel, 2015. "OPTIWAM: An Intelligent Tool for Optimizing Irrigation Water Management in Coupled Reservoir–Groundwater Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3841-3861, August.
    17. Peter Lindelöf, 2011. "Formal Institutional Contexts As Ownership Of Intellectual Property Rights And Their Implications For The Organization Of Commercialization Of Innovations At Universities — Comparative Data From Swede," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 15(05), pages 1069-1092.
    18. M. Sridharan, 2023. "Generalized Regression Neural Network Model Based Estimation of Global Solar Energy Using Meteorological Parameters," Annals of Data Science, Springer, vol. 10(4), pages 1107-1125, August.
    19. Mariz B. Arias & Sungwoo Bae, 2020. "Design Models for Power Flow Management of a Grid-Connected Solar Photovoltaic System with Energy Storage System," Energies, MDPI, vol. 13(9), pages 1-14, April.
    20. Santamaría-Bonfil, G. & Reyes-Ballesteros, A. & Gershenson, C., 2016. "Wind speed forecasting for wind farms: A method based on support vector regression," Renewable Energy, Elsevier, vol. 85(C), pages 790-809.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:260:y:2015:i:c:p:170-187. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.