Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill
Abstract Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minim...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kalibatiene, Diana [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© Taiwan Fuzzy Systems Association 2021 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of fuzzy systems - Taibei : Association, 2006, 24(2021), 1 vom: 22. Aug., Seite 425-439 |
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| Übergeordnetes Werk: |
volume:24 ; year:2021 ; number:1 ; day:22 ; month:08 ; pages:425-439 |
| Links: |
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| DOI / URN: |
10.1007/s40815-021-01145-3 |
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| Katalog-ID: |
SPR046177957 |
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| 520 | |a Abstract Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However, there is a lack of approaches for predicting oil spills in the geological environment. This paper proposes a new fuzzy model for predicting oil spills on the ground. It uses fuzzy set theory to express the uncertainty of the spilled oil volume and the specific oil capacity to make predictions more efficient and effective. It consists of the following parts: formulating a hypothesis based on initial oil spill data, fuzzy modelling of oil spill penetration, evaluating the hypothesis of whether the spilled oil will penetrate the ground layer and groundwater and finally evaluating the effectiveness of the proposition. The accuracy and reliability of the proposed model were assessed using synthetic data of oil spill penetrations into the ground and predictions of nine experts. The obtained experimental results show that the proposed fuzzy model is valid and does not contradict reality. Furthermore, statistical parameter (MAE and RMSE) shows that the proposed fuzzy model can predict the geological oil spill consequences with sufficient accuracy. It is practical and contributes to the body of knowledge in predicting geological oil spills. In addition, it will assist the practitioner in making decisions about how to respond to an oil spill. | ||
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10.1007/s40815-021-01145-3 doi (DE-627)SPR046177957 (SPR)s40815-021-01145-3-e DE-627 ger DE-627 rakwb eng Kalibatiene, Diana verfasserin (orcid)0000-0002-1317-6561 aut Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Taiwan Fuzzy Systems Association 2021 Abstract Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However, there is a lack of approaches for predicting oil spills in the geological environment. This paper proposes a new fuzzy model for predicting oil spills on the ground. It uses fuzzy set theory to express the uncertainty of the spilled oil volume and the specific oil capacity to make predictions more efficient and effective. It consists of the following parts: formulating a hypothesis based on initial oil spill data, fuzzy modelling of oil spill penetration, evaluating the hypothesis of whether the spilled oil will penetrate the ground layer and groundwater and finally evaluating the effectiveness of the proposition. The accuracy and reliability of the proposed model were assessed using synthetic data of oil spill penetrations into the ground and predictions of nine experts. The obtained experimental results show that the proposed fuzzy model is valid and does not contradict reality. Furthermore, statistical parameter (MAE and RMSE) shows that the proposed fuzzy model can predict the geological oil spill consequences with sufficient accuracy. It is practical and contributes to the body of knowledge in predicting geological oil spills. In addition, it will assist the practitioner in making decisions about how to respond to an oil spill. Fuzzy (dpeaa)DE-He213 Oil spill (dpeaa)DE-He213 Geological environment model (dpeaa)DE-He213 Prediction model (dpeaa)DE-He213 Burmakova, Anastasiya aut Enthalten in International journal of fuzzy systems Taibei : Association, 2006 24(2021), 1 vom: 22. Aug., Seite 425-439 (DE-627)612134636 (DE-600)2523322-1 2199-3211 nnns volume:24 year:2021 number:1 day:22 month:08 pages:425-439 https://dx.doi.org/10.1007/s40815-021-01145-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2021 1 22 08 425-439 |
| spelling |
10.1007/s40815-021-01145-3 doi (DE-627)SPR046177957 (SPR)s40815-021-01145-3-e DE-627 ger DE-627 rakwb eng Kalibatiene, Diana verfasserin (orcid)0000-0002-1317-6561 aut Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Taiwan Fuzzy Systems Association 2021 Abstract Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However, there is a lack of approaches for predicting oil spills in the geological environment. This paper proposes a new fuzzy model for predicting oil spills on the ground. It uses fuzzy set theory to express the uncertainty of the spilled oil volume and the specific oil capacity to make predictions more efficient and effective. It consists of the following parts: formulating a hypothesis based on initial oil spill data, fuzzy modelling of oil spill penetration, evaluating the hypothesis of whether the spilled oil will penetrate the ground layer and groundwater and finally evaluating the effectiveness of the proposition. The accuracy and reliability of the proposed model were assessed using synthetic data of oil spill penetrations into the ground and predictions of nine experts. The obtained experimental results show that the proposed fuzzy model is valid and does not contradict reality. Furthermore, statistical parameter (MAE and RMSE) shows that the proposed fuzzy model can predict the geological oil spill consequences with sufficient accuracy. It is practical and contributes to the body of knowledge in predicting geological oil spills. In addition, it will assist the practitioner in making decisions about how to respond to an oil spill. Fuzzy (dpeaa)DE-He213 Oil spill (dpeaa)DE-He213 Geological environment model (dpeaa)DE-He213 Prediction model (dpeaa)DE-He213 Burmakova, Anastasiya aut Enthalten in International journal of fuzzy systems Taibei : Association, 2006 24(2021), 1 vom: 22. Aug., Seite 425-439 (DE-627)612134636 (DE-600)2523322-1 2199-3211 nnns volume:24 year:2021 number:1 day:22 month:08 pages:425-439 https://dx.doi.org/10.1007/s40815-021-01145-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2021 1 22 08 425-439 |
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10.1007/s40815-021-01145-3 doi (DE-627)SPR046177957 (SPR)s40815-021-01145-3-e DE-627 ger DE-627 rakwb eng Kalibatiene, Diana verfasserin (orcid)0000-0002-1317-6561 aut Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Taiwan Fuzzy Systems Association 2021 Abstract Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However, there is a lack of approaches for predicting oil spills in the geological environment. This paper proposes a new fuzzy model for predicting oil spills on the ground. It uses fuzzy set theory to express the uncertainty of the spilled oil volume and the specific oil capacity to make predictions more efficient and effective. It consists of the following parts: formulating a hypothesis based on initial oil spill data, fuzzy modelling of oil spill penetration, evaluating the hypothesis of whether the spilled oil will penetrate the ground layer and groundwater and finally evaluating the effectiveness of the proposition. The accuracy and reliability of the proposed model were assessed using synthetic data of oil spill penetrations into the ground and predictions of nine experts. The obtained experimental results show that the proposed fuzzy model is valid and does not contradict reality. Furthermore, statistical parameter (MAE and RMSE) shows that the proposed fuzzy model can predict the geological oil spill consequences with sufficient accuracy. It is practical and contributes to the body of knowledge in predicting geological oil spills. In addition, it will assist the practitioner in making decisions about how to respond to an oil spill. Fuzzy (dpeaa)DE-He213 Oil spill (dpeaa)DE-He213 Geological environment model (dpeaa)DE-He213 Prediction model (dpeaa)DE-He213 Burmakova, Anastasiya aut Enthalten in International journal of fuzzy systems Taibei : Association, 2006 24(2021), 1 vom: 22. Aug., Seite 425-439 (DE-627)612134636 (DE-600)2523322-1 2199-3211 nnns volume:24 year:2021 number:1 day:22 month:08 pages:425-439 https://dx.doi.org/10.1007/s40815-021-01145-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2021 1 22 08 425-439 |
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10.1007/s40815-021-01145-3 doi (DE-627)SPR046177957 (SPR)s40815-021-01145-3-e DE-627 ger DE-627 rakwb eng Kalibatiene, Diana verfasserin (orcid)0000-0002-1317-6561 aut Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Taiwan Fuzzy Systems Association 2021 Abstract Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However, there is a lack of approaches for predicting oil spills in the geological environment. This paper proposes a new fuzzy model for predicting oil spills on the ground. It uses fuzzy set theory to express the uncertainty of the spilled oil volume and the specific oil capacity to make predictions more efficient and effective. It consists of the following parts: formulating a hypothesis based on initial oil spill data, fuzzy modelling of oil spill penetration, evaluating the hypothesis of whether the spilled oil will penetrate the ground layer and groundwater and finally evaluating the effectiveness of the proposition. The accuracy and reliability of the proposed model were assessed using synthetic data of oil spill penetrations into the ground and predictions of nine experts. The obtained experimental results show that the proposed fuzzy model is valid and does not contradict reality. Furthermore, statistical parameter (MAE and RMSE) shows that the proposed fuzzy model can predict the geological oil spill consequences with sufficient accuracy. It is practical and contributes to the body of knowledge in predicting geological oil spills. In addition, it will assist the practitioner in making decisions about how to respond to an oil spill. Fuzzy (dpeaa)DE-He213 Oil spill (dpeaa)DE-He213 Geological environment model (dpeaa)DE-He213 Prediction model (dpeaa)DE-He213 Burmakova, Anastasiya aut Enthalten in International journal of fuzzy systems Taibei : Association, 2006 24(2021), 1 vom: 22. Aug., Seite 425-439 (DE-627)612134636 (DE-600)2523322-1 2199-3211 nnns volume:24 year:2021 number:1 day:22 month:08 pages:425-439 https://dx.doi.org/10.1007/s40815-021-01145-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2021 1 22 08 425-439 |
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10.1007/s40815-021-01145-3 doi (DE-627)SPR046177957 (SPR)s40815-021-01145-3-e DE-627 ger DE-627 rakwb eng Kalibatiene, Diana verfasserin (orcid)0000-0002-1317-6561 aut Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Taiwan Fuzzy Systems Association 2021 Abstract Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However, there is a lack of approaches for predicting oil spills in the geological environment. This paper proposes a new fuzzy model for predicting oil spills on the ground. It uses fuzzy set theory to express the uncertainty of the spilled oil volume and the specific oil capacity to make predictions more efficient and effective. It consists of the following parts: formulating a hypothesis based on initial oil spill data, fuzzy modelling of oil spill penetration, evaluating the hypothesis of whether the spilled oil will penetrate the ground layer and groundwater and finally evaluating the effectiveness of the proposition. The accuracy and reliability of the proposed model were assessed using synthetic data of oil spill penetrations into the ground and predictions of nine experts. The obtained experimental results show that the proposed fuzzy model is valid and does not contradict reality. Furthermore, statistical parameter (MAE and RMSE) shows that the proposed fuzzy model can predict the geological oil spill consequences with sufficient accuracy. It is practical and contributes to the body of knowledge in predicting geological oil spills. In addition, it will assist the practitioner in making decisions about how to respond to an oil spill. Fuzzy (dpeaa)DE-He213 Oil spill (dpeaa)DE-He213 Geological environment model (dpeaa)DE-He213 Prediction model (dpeaa)DE-He213 Burmakova, Anastasiya aut Enthalten in International journal of fuzzy systems Taibei : Association, 2006 24(2021), 1 vom: 22. Aug., Seite 425-439 (DE-627)612134636 (DE-600)2523322-1 2199-3211 nnns volume:24 year:2021 number:1 day:22 month:08 pages:425-439 https://dx.doi.org/10.1007/s40815-021-01145-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2021 1 22 08 425-439 |
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Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However, there is a lack of approaches for predicting oil spills in the geological environment. This paper proposes a new fuzzy model for predicting oil spills on the ground. It uses fuzzy set theory to express the uncertainty of the spilled oil volume and the specific oil capacity to make predictions more efficient and effective. It consists of the following parts: formulating a hypothesis based on initial oil spill data, fuzzy modelling of oil spill penetration, evaluating the hypothesis of whether the spilled oil will penetrate the ground layer and groundwater and finally evaluating the effectiveness of the proposition. The accuracy and reliability of the proposed model were assessed using synthetic data of oil spill penetrations into the ground and predictions of nine experts. The obtained experimental results show that the proposed fuzzy model is valid and does not contradict reality. Furthermore, statistical parameter (MAE and RMSE) shows that the proposed fuzzy model can predict the geological oil spill consequences with sufficient accuracy. It is practical and contributes to the body of knowledge in predicting geological oil spills. 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Kalibatiene, Diana |
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Kalibatiene, Diana misc Fuzzy misc Oil spill misc Geological environment model misc Prediction model Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill |
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Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill Fuzzy (dpeaa)DE-He213 Oil spill (dpeaa)DE-He213 Geological environment model (dpeaa)DE-He213 Prediction model (dpeaa)DE-He213 |
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Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill |
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fuzzy model for predicting contamination of the geological environment during an accidental oil spill |
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Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill |
| abstract |
Abstract Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However, there is a lack of approaches for predicting oil spills in the geological environment. This paper proposes a new fuzzy model for predicting oil spills on the ground. It uses fuzzy set theory to express the uncertainty of the spilled oil volume and the specific oil capacity to make predictions more efficient and effective. It consists of the following parts: formulating a hypothesis based on initial oil spill data, fuzzy modelling of oil spill penetration, evaluating the hypothesis of whether the spilled oil will penetrate the ground layer and groundwater and finally evaluating the effectiveness of the proposition. The accuracy and reliability of the proposed model were assessed using synthetic data of oil spill penetrations into the ground and predictions of nine experts. The obtained experimental results show that the proposed fuzzy model is valid and does not contradict reality. Furthermore, statistical parameter (MAE and RMSE) shows that the proposed fuzzy model can predict the geological oil spill consequences with sufficient accuracy. It is practical and contributes to the body of knowledge in predicting geological oil spills. In addition, it will assist the practitioner in making decisions about how to respond to an oil spill. © Taiwan Fuzzy Systems Association 2021 |
| abstractGer |
Abstract Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However, there is a lack of approaches for predicting oil spills in the geological environment. This paper proposes a new fuzzy model for predicting oil spills on the ground. It uses fuzzy set theory to express the uncertainty of the spilled oil volume and the specific oil capacity to make predictions more efficient and effective. It consists of the following parts: formulating a hypothesis based on initial oil spill data, fuzzy modelling of oil spill penetration, evaluating the hypothesis of whether the spilled oil will penetrate the ground layer and groundwater and finally evaluating the effectiveness of the proposition. The accuracy and reliability of the proposed model were assessed using synthetic data of oil spill penetrations into the ground and predictions of nine experts. The obtained experimental results show that the proposed fuzzy model is valid and does not contradict reality. Furthermore, statistical parameter (MAE and RMSE) shows that the proposed fuzzy model can predict the geological oil spill consequences with sufficient accuracy. It is practical and contributes to the body of knowledge in predicting geological oil spills. In addition, it will assist the practitioner in making decisions about how to respond to an oil spill. © Taiwan Fuzzy Systems Association 2021 |
| abstract_unstemmed |
Abstract Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However, there is a lack of approaches for predicting oil spills in the geological environment. This paper proposes a new fuzzy model for predicting oil spills on the ground. It uses fuzzy set theory to express the uncertainty of the spilled oil volume and the specific oil capacity to make predictions more efficient and effective. It consists of the following parts: formulating a hypothesis based on initial oil spill data, fuzzy modelling of oil spill penetration, evaluating the hypothesis of whether the spilled oil will penetrate the ground layer and groundwater and finally evaluating the effectiveness of the proposition. The accuracy and reliability of the proposed model were assessed using synthetic data of oil spill penetrations into the ground and predictions of nine experts. The obtained experimental results show that the proposed fuzzy model is valid and does not contradict reality. Furthermore, statistical parameter (MAE and RMSE) shows that the proposed fuzzy model can predict the geological oil spill consequences with sufficient accuracy. It is practical and contributes to the body of knowledge in predicting geological oil spills. In addition, it will assist the practitioner in making decisions about how to respond to an oil spill. © Taiwan Fuzzy Systems Association 2021 |
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Fuzzy Model for Predicting Contamination of the Geological Environment During an Accidental Oil Spill |
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https://dx.doi.org/10.1007/s40815-021-01145-3 |
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Burmakova, Anastasiya |
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Burmakova, Anastasiya |
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| doi_str |
10.1007/s40815-021-01145-3 |
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2024-07-03T20:52:33.826Z |
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