{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T11:40:18Z","timestamp":1789040418442,"version":"build-2803163510"},"reference-count":50,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T00:00:00Z","timestamp":1700438400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004054","name":"Institutional Fund Projects","doi-asserted-by":"publisher","award":["IFPIP-1555-137-1443"],"award-info":[{"award-number":["IFPIP-1555-137-1443"]}],"id":[{"id":"10.13039\/501100004054","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Education and King Abdulaziz University, DSR, Jeddah, Saudi Arabia","award":["IFPIP-1555-137-1443"],"award-info":[{"award-number":["IFPIP-1555-137-1443"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biomimetics"],"abstract":"<jats:p>Direct methanol fuel cells (DMFCs) are promising form of energy conversion technology that have the potential to take the role of lithium-ion batteries in portable electronics and electric cars. To increase the efficiency of DMFCs, many operating conditions ought to be optimized. Developing a reliable fuzzy model to simulate DMFCs is a major objective. To increase the power output of a DMFC, three process variables are considered: temperature, methanol concentration, and oxygen flow rate. First, a fuzzy model of the DMFC was developed using experimental data. The best operational circumstances to increase power density were then determined using the beetle antennae search (BAS) method. The RMSE values for the fuzzy DMFC model are 0.1982 and 1.5460 for the training and testing data. For training and testing, the coefficient of determination (R2) values were 0.9977 and 0.89, respectively. Thanks to fuzzy logic, the RMSE was reduced by 88% compared to ANOVA. It decreased from 7.29 (using ANOVA) to 0.8628 (using fuzzy). The fuzzy model\u2019s low RMSE and high R2 values show that the modeling phase was successful. In comparison with the measured data and RSM, the combination of fuzzy modeling and the BAS algorithm increased the power density of the DMFC by 8.88% and 7.5%, respectively, and 75 \u00b0C, 1.2 M, and 400 mL\/min were the ideal values for temperature, methanol concentration, and oxygen flow rate, respectively.<\/jats:p>","DOI":"10.3390\/biomimetics8070557","type":"journal-article","created":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T11:31:36Z","timestamp":1700479896000},"page":"557","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0427-4079","authenticated-orcid":false,"given":"Ahmed","family":"Al Shouny","sequence":"first","affiliation":[{"name":"Department of Geomatics, Faculty of Architecture and Planning, King Abdulaziz University, Jeddah 21589, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9254-2744","authenticated-orcid":false,"given":"Hegazy","family":"Rezk","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering in Wadi Alddawasir, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enas Taha","family":"Sayed","sequence":"additional","affiliation":[{"name":"Department of Chemical Engineering, Faculty of Engineering, Minia University, Minya 61111, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3248-9843","authenticated-orcid":false,"given":"Mohammad Ali","family":"Abdelkareem","sequence":"additional","affiliation":[{"name":"Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates"},{"name":"Fuel Cell Institute, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2972-5649","authenticated-orcid":false,"given":"Usama Hamed","family":"Issa","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Faculty of Engineering, Minia University, Minya 61519, Egypt"},{"name":"Department of Civil Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3544-0228","authenticated-orcid":false,"given":"Yehia","family":"Miky","sequence":"additional","affiliation":[{"name":"Department of Geomatics, Faculty of Architecture and Planning, King Abdulaziz University, Jeddah 21589, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdul Ghani","family":"Olabi","sequence":"additional","affiliation":[{"name":"Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"073005","DOI":"10.1088\/1748-9326\/abee4e","article-title":"A review of trends and drivers of greenhouse gas emissions by sector from 1990 to 2018","volume":"16","author":"Lamb","year":"2021","journal-title":"Environ. Res. Lett."},{"key":"ref_2","unstructured":"Rahimpour, M.R., Farsi, M., and Makarem, M.A. (2020). 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