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description Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2021Publisher:Wiley Zhimin Li; Deyin Zhao; Linbo Han; Li Yu; Mohammad Mahdi Molla Jafari;This paper incorporates the adaptive neurofuzzy inference system (ANFIS) technique to model the yield of bio‐oil. The estimation of this parameter was performed according to pyrolysis conditions and biomass compositions of feedstock. For this purpose, this paper innovates two optimization methods including a genetic algorithm (GA) and particle swarm optimization (PSO). Primary data were gathered from previous studies and included 244 data of biodiesel oils. The findings showed a coefficient determination (R2) of 0.937 and RMSE of 2.1053 for the GA‐ANFIS model, and a coefficient determination (R2) of 0.968 and RMSE of 1.4443 for PSO‐ANFIS. This study indicates the capability of the PSO‐ANFIS algorithm in the estimation of the bio‐oil yield. According to the performed analysis, this model shows a higher ability than the previously presented models in predicting the target values and can be a suitable alternative to time‐consuming and difficult experimental tests.
BioMed Research Inte... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1155/2021/2204021&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!
more_vert BioMed Research Inte... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1155/2021/2204021&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
description Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2021Publisher:Wiley Zhimin Li; Deyin Zhao; Linbo Han; Li Yu; Mohammad Mahdi Molla Jafari;This paper incorporates the adaptive neurofuzzy inference system (ANFIS) technique to model the yield of bio‐oil. The estimation of this parameter was performed according to pyrolysis conditions and biomass compositions of feedstock. For this purpose, this paper innovates two optimization methods including a genetic algorithm (GA) and particle swarm optimization (PSO). Primary data were gathered from previous studies and included 244 data of biodiesel oils. The findings showed a coefficient determination (R2) of 0.937 and RMSE of 2.1053 for the GA‐ANFIS model, and a coefficient determination (R2) of 0.968 and RMSE of 1.4443 for PSO‐ANFIS. This study indicates the capability of the PSO‐ANFIS algorithm in the estimation of the bio‐oil yield. According to the performed analysis, this model shows a higher ability than the previously presented models in predicting the target values and can be a suitable alternative to time‐consuming and difficult experimental tests.
BioMed Research Inte... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1155/2021/2204021&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!
more_vert BioMed Research Inte... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1155/2021/2204021&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu