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A clustering model based on an evolutionary algorithm for better energy use in crop production

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Abstract

Energy consumption and its negative environmental impacts are of interesting topics in the recent centuries. Agricultural systems are both energy users and suppliers in the form of bio energy and play a key role in world economics as well as food security. A high amount of energy from different sources is used in this sector while researchers who investigated energy flow in crops production especially in developing countries, have reported a high degree of inefficiency. In order to differentiate between efficient and inefficient farms, a clustering model based on imperialist competitive algorithm (ICA) has been developed and the surveyed watermelon farms have been clustered based on three features, i.e. greenhouse gas (GHG) emission, input energy and farm size. The results showed that of the three developed clusters, the best cluster performed 20 and 46 % better than the two other clusters in energy and 22 and 52 % in CO2 emissions. The average of total energy input and GHG emissions for the best cluster were calculated as 43,423 MJ per ha and 8,120 CO2eq. The results of this study demonstrate the successful application of ICA for better use of energy in cropping systems which can lead to a better environmental and energy performance.

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Acknowledgments

The authors would like to thank University of Tehran for its financial supports. Also, Authors would like to thank University Malaya for partially funding the research work using the research grant UM.C/625/1/HIR/MOE/FCSIT/03.

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Authors and Affiliations

  1. Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran

    Benyamin Khoshnevisan & Elham Bolandnazar

  2. Young Researchers and Elite Club, Ardabil branch, Islamic Azad University, Ardabil, Iran

    Sasan Barak

  3. Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Shahaboddin Shamshirband & Abdullah Gani

  4. Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran

    Hamid Maghsoudlou

  5. Department of Computer Science, Riyadh Community College, King Saud University, P.O. Box 50996, Riyadh, 11533, Saudi Arabia

    Torki A. Altameem

  6. Department of Computer Science, Chalous Branch, Islamic Azad University (IAU), Chalous, Mazandaran, 46615-397, Iran

    Shahaboddin Shamshirband

Authors
  1. Benyamin Khoshnevisan
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  2. Elham Bolandnazar
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  3. Sasan Barak
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  4. Shahaboddin Shamshirband
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  5. Hamid Maghsoudlou
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  6. Torki A. Altameem
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  7. Abdullah Gani
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Corresponding authors

Correspondence to Benyamin Khoshnevisan, Sasan Barak or Shahaboddin Shamshirband.

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Khoshnevisan, B., Bolandnazar, E., Barak, S. et al. A clustering model based on an evolutionary algorithm for better energy use in crop production. Stoch Environ Res Risk Assess 29, 1921–1935 (2015). https://doi.org/10.1007/s00477-014-0972-6

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