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

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A clustering model based on an evolutionary algorithm for better energy use in crop production. / Khoshnevisan, Benyamin; Bolandnazar, Elham; Barak, Sasan et al.
In: Stochastic Environmental Research and Risk Assessment, Vol. 29, No. 8, 12.2015, p. 1921–1935.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Khoshnevisan, B, Bolandnazar, E, Barak, S, Shamshirband, S, Maghsoudlou, H, Altameem, TA & Gani, A 2015, 'A clustering model based on an evolutionary algorithm for better energy use in crop production', Stochastic Environmental Research and Risk Assessment, vol. 29, no. 8, pp. 1921–1935. https://doi.org/10.1007/s00477-014-0972-6

APA

Khoshnevisan, B., Bolandnazar, E., Barak, S., Shamshirband, S., Maghsoudlou, H., Altameem, T. A., & Gani, A. (2015). A clustering model based on an evolutionary algorithm for better energy use in crop production. Stochastic Environmental Research and Risk Assessment, 29(8), 1921–1935. https://doi.org/10.1007/s00477-014-0972-6

Vancouver

Khoshnevisan B, Bolandnazar E, Barak S, Shamshirband S, Maghsoudlou H, Altameem TA et al. A clustering model based on an evolutionary algorithm for better energy use in crop production. Stochastic Environmental Research and Risk Assessment. 2015 Dec;29(8):1921–1935. Epub 2014 Oct 18. doi: 10.1007/s00477-014-0972-6

Author

Khoshnevisan, Benyamin ; Bolandnazar, Elham ; Barak, Sasan et al. / A clustering model based on an evolutionary algorithm for better energy use in crop production. In: Stochastic Environmental Research and Risk Assessment. 2015 ; Vol. 29, No. 8. pp. 1921–1935.

Bibtex

@article{abb409f16fdf4907b28a668856c495e7,
title = "A clustering model based on an evolutionary algorithm for better energy use in crop production",
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.",
author = "Benyamin Khoshnevisan and Elham Bolandnazar and Sasan Barak and Shahaboddin Shamshirband and Hamidreza Maghsoudlou and Altameem, {Torki A.} and Abdullah Gani",
year = "2015",
month = dec,
doi = "10.1007/s00477-014-0972-6",
language = "English",
volume = "29",
pages = "1921–1935",
journal = "Stochastic Environmental Research and Risk Assessment",
issn = "1436-3240",
publisher = "Springer New York",
number = "8",

}

RIS

TY - JOUR

T1 - A clustering model based on an evolutionary algorithm for better energy use in crop production

AU - Khoshnevisan, Benyamin

AU - Bolandnazar, Elham

AU - Barak, Sasan

AU - Shamshirband, Shahaboddin

AU - Maghsoudlou, Hamidreza

AU - Altameem, Torki A.

AU - Gani, Abdullah

PY - 2015/12

Y1 - 2015/12

N2 - 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.

AB - 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.

U2 - 10.1007/s00477-014-0972-6

DO - 10.1007/s00477-014-0972-6

M3 - Journal article

VL - 29

SP - 1921

EP - 1935

JO - Stochastic Environmental Research and Risk Assessment

JF - Stochastic Environmental Research and Risk Assessment

SN - 1436-3240

IS - 8

ER -