Modeling renewable energy usage with hesitant Fuzzy cognitive map
Abstract Renewable energy sources (solar, wind, tidal, etc.), which are unlimited and have a fair distribution in the world, are an alternative to the depleting fossil fuels (coil, petroleum, natural gas, etc.). It is necessary to identify the right technologies and methods to make more effective us...
Ausführliche Beschreibung
Autor*in: |
Çoban, Veysel [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2017 |
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Anmerkung: |
© The Author(s) 2017 |
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Übergeordnetes Werk: |
Enthalten in: Complex & intelligent systems - Berlin : SpringerOpen, 2015, 3(2017), 3 vom: 03. Mai, Seite 155-166 |
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Übergeordnetes Werk: |
volume:3 ; year:2017 ; number:3 ; day:03 ; month:05 ; pages:155-166 |
Links: |
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DOI / URN: |
10.1007/s40747-017-0043-y |
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Katalog-ID: |
SPR037218565 |
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10.1007/s40747-017-0043-y doi (DE-627)SPR037218565 (SPR)s40747-017-0043-y-e DE-627 ger DE-627 rakwb eng Çoban, Veysel verfasserin aut Modeling renewable energy usage with hesitant Fuzzy cognitive map 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2017 Abstract Renewable energy sources (solar, wind, tidal, etc.), which are unlimited and have a fair distribution in the world, are an alternative to the depleting fossil fuels (coil, petroleum, natural gas, etc.). It is necessary to identify the right technologies and methods to make more effective use of renewable energy sources including uncertainty and irregularity in resource creation. In this study, dynamic environmental factors affecting the production of solar and wind energy are defined and the relations among them are linguistically expressed by the experts. These linguistic relationships among factors and their initial states are assessed by new developed hesitant linguistic cognitive map method that is an extension of hesitant fuzzy sets and fuzzy cognitive map. Relational development between factors was observed by simulating the model according to the initial condition of the factors. Thus, the model helps investors and governments to direct their solar and wind energy investment decisions. Hesitant fuzzy cognitive map (dpeaa)DE-He213 Renewable energy (dpeaa)DE-He213 Solar energy (dpeaa)DE-He213 Fuzzy sets (dpeaa)DE-He213 Onar, Sezi Çevik aut Enthalten in Complex & intelligent systems Berlin : SpringerOpen, 2015 3(2017), 3 vom: 03. Mai, Seite 155-166 (DE-627)835589269 (DE-600)2834740-7 2198-6053 nnns volume:3 year:2017 number:3 day:03 month:05 pages:155-166 https://dx.doi.org/10.1007/s40747-017-0043-y kostenfrei 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_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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2017 3 03 05 155-166 |
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10.1007/s40747-017-0043-y doi (DE-627)SPR037218565 (SPR)s40747-017-0043-y-e DE-627 ger DE-627 rakwb eng Çoban, Veysel verfasserin aut Modeling renewable energy usage with hesitant Fuzzy cognitive map 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2017 Abstract Renewable energy sources (solar, wind, tidal, etc.), which are unlimited and have a fair distribution in the world, are an alternative to the depleting fossil fuels (coil, petroleum, natural gas, etc.). It is necessary to identify the right technologies and methods to make more effective use of renewable energy sources including uncertainty and irregularity in resource creation. In this study, dynamic environmental factors affecting the production of solar and wind energy are defined and the relations among them are linguistically expressed by the experts. These linguistic relationships among factors and their initial states are assessed by new developed hesitant linguistic cognitive map method that is an extension of hesitant fuzzy sets and fuzzy cognitive map. Relational development between factors was observed by simulating the model according to the initial condition of the factors. Thus, the model helps investors and governments to direct their solar and wind energy investment decisions. Hesitant fuzzy cognitive map (dpeaa)DE-He213 Renewable energy (dpeaa)DE-He213 Solar energy (dpeaa)DE-He213 Fuzzy sets (dpeaa)DE-He213 Onar, Sezi Çevik aut Enthalten in Complex & intelligent systems Berlin : SpringerOpen, 2015 3(2017), 3 vom: 03. Mai, Seite 155-166 (DE-627)835589269 (DE-600)2834740-7 2198-6053 nnns volume:3 year:2017 number:3 day:03 month:05 pages:155-166 https://dx.doi.org/10.1007/s40747-017-0043-y kostenfrei 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_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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2017 3 03 05 155-166 |
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10.1007/s40747-017-0043-y doi (DE-627)SPR037218565 (SPR)s40747-017-0043-y-e DE-627 ger DE-627 rakwb eng Çoban, Veysel verfasserin aut Modeling renewable energy usage with hesitant Fuzzy cognitive map 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2017 Abstract Renewable energy sources (solar, wind, tidal, etc.), which are unlimited and have a fair distribution in the world, are an alternative to the depleting fossil fuels (coil, petroleum, natural gas, etc.). It is necessary to identify the right technologies and methods to make more effective use of renewable energy sources including uncertainty and irregularity in resource creation. In this study, dynamic environmental factors affecting the production of solar and wind energy are defined and the relations among them are linguistically expressed by the experts. These linguistic relationships among factors and their initial states are assessed by new developed hesitant linguistic cognitive map method that is an extension of hesitant fuzzy sets and fuzzy cognitive map. Relational development between factors was observed by simulating the model according to the initial condition of the factors. Thus, the model helps investors and governments to direct their solar and wind energy investment decisions. Hesitant fuzzy cognitive map (dpeaa)DE-He213 Renewable energy (dpeaa)DE-He213 Solar energy (dpeaa)DE-He213 Fuzzy sets (dpeaa)DE-He213 Onar, Sezi Çevik aut Enthalten in Complex & intelligent systems Berlin : SpringerOpen, 2015 3(2017), 3 vom: 03. Mai, Seite 155-166 (DE-627)835589269 (DE-600)2834740-7 2198-6053 nnns volume:3 year:2017 number:3 day:03 month:05 pages:155-166 https://dx.doi.org/10.1007/s40747-017-0043-y kostenfrei 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_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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2017 3 03 05 155-166 |
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10.1007/s40747-017-0043-y doi (DE-627)SPR037218565 (SPR)s40747-017-0043-y-e DE-627 ger DE-627 rakwb eng Çoban, Veysel verfasserin aut Modeling renewable energy usage with hesitant Fuzzy cognitive map 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2017 Abstract Renewable energy sources (solar, wind, tidal, etc.), which are unlimited and have a fair distribution in the world, are an alternative to the depleting fossil fuels (coil, petroleum, natural gas, etc.). It is necessary to identify the right technologies and methods to make more effective use of renewable energy sources including uncertainty and irregularity in resource creation. In this study, dynamic environmental factors affecting the production of solar and wind energy are defined and the relations among them are linguistically expressed by the experts. These linguistic relationships among factors and their initial states are assessed by new developed hesitant linguistic cognitive map method that is an extension of hesitant fuzzy sets and fuzzy cognitive map. Relational development between factors was observed by simulating the model according to the initial condition of the factors. Thus, the model helps investors and governments to direct their solar and wind energy investment decisions. Hesitant fuzzy cognitive map (dpeaa)DE-He213 Renewable energy (dpeaa)DE-He213 Solar energy (dpeaa)DE-He213 Fuzzy sets (dpeaa)DE-He213 Onar, Sezi Çevik aut Enthalten in Complex & intelligent systems Berlin : SpringerOpen, 2015 3(2017), 3 vom: 03. Mai, Seite 155-166 (DE-627)835589269 (DE-600)2834740-7 2198-6053 nnns volume:3 year:2017 number:3 day:03 month:05 pages:155-166 https://dx.doi.org/10.1007/s40747-017-0043-y kostenfrei 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_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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2017 3 03 05 155-166 |
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Çoban, Veysel misc Hesitant fuzzy cognitive map misc Renewable energy misc Solar energy misc Fuzzy sets Modeling renewable energy usage with hesitant Fuzzy cognitive map |
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Modeling renewable energy usage with hesitant Fuzzy cognitive map Hesitant fuzzy cognitive map (dpeaa)DE-He213 Renewable energy (dpeaa)DE-He213 Solar energy (dpeaa)DE-He213 Fuzzy sets (dpeaa)DE-He213 |
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modeling renewable energy usage with hesitant fuzzy cognitive map |
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Modeling renewable energy usage with hesitant Fuzzy cognitive map |
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Abstract Renewable energy sources (solar, wind, tidal, etc.), which are unlimited and have a fair distribution in the world, are an alternative to the depleting fossil fuels (coil, petroleum, natural gas, etc.). It is necessary to identify the right technologies and methods to make more effective use of renewable energy sources including uncertainty and irregularity in resource creation. In this study, dynamic environmental factors affecting the production of solar and wind energy are defined and the relations among them are linguistically expressed by the experts. These linguistic relationships among factors and their initial states are assessed by new developed hesitant linguistic cognitive map method that is an extension of hesitant fuzzy sets and fuzzy cognitive map. Relational development between factors was observed by simulating the model according to the initial condition of the factors. Thus, the model helps investors and governments to direct their solar and wind energy investment decisions. © The Author(s) 2017 |
abstractGer |
Abstract Renewable energy sources (solar, wind, tidal, etc.), which are unlimited and have a fair distribution in the world, are an alternative to the depleting fossil fuels (coil, petroleum, natural gas, etc.). It is necessary to identify the right technologies and methods to make more effective use of renewable energy sources including uncertainty and irregularity in resource creation. In this study, dynamic environmental factors affecting the production of solar and wind energy are defined and the relations among them are linguistically expressed by the experts. These linguistic relationships among factors and their initial states are assessed by new developed hesitant linguistic cognitive map method that is an extension of hesitant fuzzy sets and fuzzy cognitive map. Relational development between factors was observed by simulating the model according to the initial condition of the factors. Thus, the model helps investors and governments to direct their solar and wind energy investment decisions. © The Author(s) 2017 |
abstract_unstemmed |
Abstract Renewable energy sources (solar, wind, tidal, etc.), which are unlimited and have a fair distribution in the world, are an alternative to the depleting fossil fuels (coil, petroleum, natural gas, etc.). It is necessary to identify the right technologies and methods to make more effective use of renewable energy sources including uncertainty and irregularity in resource creation. In this study, dynamic environmental factors affecting the production of solar and wind energy are defined and the relations among them are linguistically expressed by the experts. These linguistic relationships among factors and their initial states are assessed by new developed hesitant linguistic cognitive map method that is an extension of hesitant fuzzy sets and fuzzy cognitive map. Relational development between factors was observed by simulating the model according to the initial condition of the factors. Thus, the model helps investors and governments to direct their solar and wind energy investment decisions. © The Author(s) 2017 |
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