[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122617-en":3,"doc-seo-122617-105":29,"detail-sidebar-cat-0-en-105":81},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":20,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},122617,1099513958762,"Logic","https://ap-avatar.wpscdn.com/avatar/1000023916a998db790?x-image-process=image/resize,m_fixed,w_180,h_180&k=1784791008015729253",8,"Research & Report","Biohydrogen production from microalgae - A review unveiling various machine learning algorithms","Biohydrogen production from microalgae is a promising alternative energy pathway intensively studied for its potential to replace conventional fuels. The biological processes behind it involve complex dynamics that reduce the reliability of traditional modeling and optimization while increasing cost. Machine learning algorithms are used to address these limitations because they can capture nonlinear interactions and manage multivariate inputs. The review surveys recent microalgal biohydrogen applications of random forests, artificial neural networks, support vector machines, and regression, comparing their effectiveness for relationship analysis, classification, and prediction.","A review unveiling various machine learning algorithms adopted for biohydrogen  \nproductions from microalgae  \nABSTRACT  \nBiohydrogen production from microalgae is a potential alternative energy source that is now intensively being researched. The complex natures of the biological processes involved have afflicted the accuracy of traditional modelling and optimization, besides being costly. Accordingly, machine learning algorithms have been employed to overcome setbacks, as these approaches have the capability to predict nonlinear interactions and handle multivariate data from microalgal biohydrogen studies. Thus, the review focuses on revealing the recent applications of machine learning techniques in microalgal biohydrogen production. The working principles of random forests, artificial neural networks, support vector machines, and regression algorithms are covered. The applications of these techniques are analyzed and compared for their effectiveness, advantages and disadvantages in the relationship studies, classification of results, and prediction of microalgal hydrogen production. These techniques have shown great performance despite limited data sets that are complex and nonlinear. However, the current techniques are still susceptible to overfitting, which could potentially reduce prediction performance. These could be potentially resolved or mitigated by comparing the methods, should the input data be limited.","cbCaij1bqatoWM97","https://ap.wps.com/l/cbCaij1bqatoWM97","pdf",37212,1,"English","en",105,"# Abstract\n# Scope and Motivation\n# Machine Learning Techniques Covered\n## Random Forests\n## Artificial Neural Networks\n## Support Vector Machines\n## Regression Algorithms\n# Application Analysis and Comparison\n## Relationship Studies\n## Classification of Results\n## Prediction of Hydrogen Production\n# Performance Considerations and Limitations","[{\"question\":\"What main limitation remains with current machine learning techniques?\",\"answer\":\"Even with strong performance on complex nonlinear data, current techniques can be susceptible to overfitting, which may reduce prediction performance when data are limited.\"}]","Biohydrogen production from microalgae - A review unveiling various machine learning algorithms | PDF",1785811744,3,{"code":4,"msg":30,"data":31},"ok",{"site_id":23,"language":22,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":76,"head_meta":78,"extra_data":80,"updated_unix":27},"biohydrogen-production-from-microalgae-a-review-unveiling-various-machine-learning-algorithms","",{"@graph":35,"@context":75},[36,52,66],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,49],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":28},"https://docshare.wps.com/document/research-report/",{"item":50,"name":13,"@type":42,"position":51},"https://docshare.wps.com/document/biohydrogen-production-from-microalgae-a-review-unveiling-various-machine-learning-algorithms/122617/",4,{"url":50,"name":13,"@type":53,"author":54,"headline":13,"publisher":56,"fileFormat":59,"inLanguage":22,"description":14,"dateModified":60,"datePublished":60,"encodingFormat":59,"isAccessibleForFree":61,"interactionStatistic":62},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":40,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":63,"interactionType":64,"userInteractionCount":4},"InteractionCounter",{"@type":65},"ViewAction",{"@type":67,"mainEntity":68},"FAQPage",[69],{"name":70,"@type":71,"acceptedAnswer":72},"What main limitation remains with current machine learning techniques?","Question",{"text":73,"@type":74},"Even with strong performance on complex nonlinear data, current techniques can be susceptible to overfitting, which may reduce prediction performance when data are limited.","Answer","https://schema.org",{"og:url":50,"og:type":77,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":79,"canonical":50},"index,follow",{"doc_id":7,"site_id":23},{"code":4,"msg":5,"data":82},[83,87,91,95,100,105,110,113,118,121,125],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":84,"show_sort_weight":85,"slug":86},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":88,"show_sort_weight":89,"slug":90},"Literature",80,"literature",{"id":51,"doc_module":4,"doc_module_name":45,"category_name":92,"show_sort_weight":93,"slug":94},"Exam",70,"exam",{"id":96,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},5,"Comic",60,"comic",{"id":101,"doc_module":4,"doc_module_name":45,"category_name":102,"show_sort_weight":103,"slug":104},6,"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":45,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":111,"slug":112},30,"research-report",{"id":114,"doc_module":4,"doc_module_name":45,"category_name":115,"show_sort_weight":116,"slug":117},9,"Religion & Spirituality",20,"religion-spirituality",{"id":116,"doc_module":4,"doc_module_name":45,"category_name":119,"show_sort_weight":116,"slug":120},"World Cup","world-cup",{"id":122,"doc_module":4,"doc_module_name":45,"category_name":123,"show_sort_weight":122,"slug":124},10,"Lifestyle","lifestyle",{"id":126,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":96,"slug":128},19,"General","general"]