厦门大学平台管理系统 Fan Lin--Home-- Comparative Study on Theoretical and Machine Learning Methods for Acquiring Compressed Liquid Densities of 1,1,1,2,3,3,3-Heptafluoropropane (R227ea) via Song and Mason Equation, Support Vector Machine, and Artificial Neural Networks

Fan Lin Associate Professor

林凡，理学博士，现担任厦门大学平潭研究院执行院长、硕/博士生导师、软件工程系副教授、IEEE高级会员；指导的已毕业硕士研究生22人、博士5人。主要研究方向包括：强化学习、推荐算法、生成模型近年来致力于研究生成式模型方法的深层次应用。包括基于生成模型的时间序列预测分析、数字虚拟人、RLHF应用教育、金融交叉领域的研究。主持教育交叉学科国家自然科学基金面上项目、主持国家科技支撑计划、主持科技部中小企业创新基金...Detials

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Comparative Study on Theoretical and Machine Learning Methods for Acquiring Compressed Liquid Densities of 1,1,1,2,3,3,3-Heptafluoropropane (R227ea) via Song and Mason Equation, Support Vector Machine, and Artificial Neural Networks

Release time:2022-03-11 Hits:

Journal:APPLIED SCIENCES-BASEL
Correspondence Author:Fan Lin
Indexed by:Article
Volume:6
Issue:1
Translation or Not:no
Date of Publication:2015-12-01

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