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RETRACTED ARTICLE: Soft computing methodologies for estimation of energy consumption in buildings with different envelope parameters

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This article was retracted on 07 December 2018

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Abstract

In this study, soft computing methods are designed and adapted to estimate energy consumption of the building according to main building envelope parameters such as material thicknesses and insulation K-value. In order to predict the building energy consumption, novel intelligent soft computing schemes, support vector regression (SVR), and adaptive neuro-fuzzy inference system (ANFIS) are used. The polynomial, linear, and radial basis function (RBF) is applied as the kernel function of the SVR to estimate the optimal energy consumption of buildings. The performance of proposed optimizers is confirmed by simulation results. The SVR results are compared with the ANFIS, artificial neural network (ANN), and genetic programming (GP) results. The computational results show that an improvement in predictive accuracy and capability of generalization can be achieved by the ANFIS approach in comparison to the SVR estimation. Based on the simulation results, the effectiveness of the proposed optimization strategies is verified. The data used in soft computing were obtained from 180 simulations in EnergyPlus for variations of building envelope parameters.

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Change history

  • 07 December 2018

    The Editor-in-Chief has retracted this article (Naji et al. 2016a) because validity of the content of this article cannot be verified. This article showed evidence of substantial text overlap (most notably with the articles cited (Naji et al. 2014, 2016b; Akib et al. 2015)), peer review and authorship manipulation.

  • 07 December 2018

    The Editor-in-Chief has retracted this article (Naji et al. 2016a) because validity of the content of this article cannot be verified. This article showed evidence of substantial text overlap (most notably with the articles cited (Naji et al. 2014, 2016b; Akib et al. 2015)), peer review and authorship manipulation.

  • 07 December 2018

    The Editor-in-Chief has retracted this article (Naji et al. 2016a) because validity of the content of this article cannot be verified. This article showed evidence of substantial text overlap (most notably with the articles cited (Naji et al. 2014, 2016b; Akib et al. 2015)), peer review and authorship manipulation.

  • 07 December 2018

    The Editor-in-Chief has retracted this article (Naji et al. 2016a) because validity of the content of this article cannot be verified. This article showed evidence of substantial text overlap (most notably with the articles cited (Naji et al. 2014, 2016b; Akib et al. 2015)), peer review and authorship manipulation.

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Acknowledgments

The authors are grateful to University of Malaya for the financial support through the University of Malaya Research Grant with Project No RP018-2012B: Development of geo-polymer concrete for structural application.

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Authors and Affiliations

  1. Department of Civil Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia

    Sareh Naji, U. Johnson Alengaram, Mohd Zamin Jumaat & Mohsen Amirmojahedi

  2. Department of Computer System and Technology, Faculty of Computer Science and Information Technology, 50603, Kuala Lumpur, Malaysia

    Shahaboddin Shamshirband

  3. Faculty of Engineering, Seraj University, Tabriz, Iran

    Hamed Basser

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  1. Sareh Naji
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  2. Shahaboddin Shamshirband
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  3. Hamed Basser
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  4. U. Johnson Alengaram
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  5. Mohd Zamin Jumaat
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  6. Mohsen Amirmojahedi
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Correspondence to Sareh Naji or Shahaboddin Shamshirband.

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The Editor-in-Chief has retracted this article because validity of the content of this article cannot be verified. This article showed evidence of substantial text overlap peer review and authorship manipulation. None of the authors agree to this retraction.

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Naji, S., Shamshirband, S., Basser, H. et al. RETRACTED ARTICLE: Soft computing methodologies for estimation of energy consumption in buildings with different envelope parameters. Energy Efficiency 9, 435–453 (2016). https://doi.org/10.1007/s12053-015-9373-z

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  • DOI: https://doi.org/10.1007/s12053-015-9373-z

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