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Inputs included membrane type, pressure, temperature, pressure, and solute concentration, and a multilayer perceptron (fully connected feedforward ANN) was implemented in Jupyter Notebook. The study evaluated permeance and rejection performance, focused mainly on silica-coated membranes, using MAE, MSE, RMSE, and R2, with 361-sample data and pre-processing. Principal component analysis identified key parameter similarities for both targets. AI-based predictions achieved up to 89% for permeance and 90% for rejection, supporting a more efficient and cost-effective approach for sustainable membrane processes.","MACHINE LEARNING-INCORPORATED MEMBRANE PERFORMANCE PREDICTION FOR MEMBRANE PROCESSES  \nSTEPHANIE SU YI CHEIN  \nBACHELOR OF CHEMICAL ENGINEERING UNIVERSITI MALAYSIA PAHANG AL-SULTAN ABDULLAH  \nMACHINE LEARNING-INCORPORATED MEMBRANE PERFORMANCE PREDICTION FOR MEMBRANE PROCESSES  \nSTEPHANIE SU YI CHEIN  \nThesis submitted in partial fulfilment of the requirements for the award of the degree of  \nBachelor of Chemical Engineering  \nFaculty of Chemical & Process Engineering Technology UNIVERSITI MALAYSIA PAHANG AL-SULTAN ABDULLAH  \n18 JANUARY 2024  \nUNIVERSITI MALAYSIA PAHANG AL-SULTAN ABDULLAH  \n\n|  |  |  |  |  |  |\n| --- | --- | --- | --- | --- | --- |\n| DECLARATION OF THESIS AND COPYRIGHT |  |  |  |  |  |\n| Author’s Full Name Date ofBirth\u003Cbr>Title\u003Cbr>Academic Session |  | :\u003Cbr>:\u003Cbr>:\u003Cbr>: | STEPHANIE SU YI CHEIN 06 SEPTEMBER 2000\u003Cbr>MACHINE LEARNING-INCORPORATED MEMBRANE PERFORMANCE PREDICTION FOR MEMBRANE PROCESSES\u003Cbr>SEM I 2023/2024 |  |  |\n| I declare that this thesis is classified as: |  |  |  |  |  |\n| 􀂅 CONFIDENTIAL\u003Cbr>􀂅 RESTRICTED\u003Cbr>􀀻 OPEN ACCESS |  | (Contains confidential information under the Official Secret Act 1997) *\u003Cbr>(Contains restricted information as specified by the organization where research was done)*\u003Cbr>I agree that my thesis to be published as online open Access (Full Text) |  |  |  |\n| I acknowledge that Universiti Malaysia Pahang reserves the following rights:\u003Cbr>1. The Thesis is the Property of Universiti Malaysia Pahang\u003Cbr>2. The Library of Universiti Malaysia Pahang has the right to make copies of the thesis for the purpose of research only.\u003Cbr>3. The Library has the right to make copies of the thesis for academic exchange. |  |  |  |  |  |\n| Certified by: | |  |  | \u003Cbr>___________________ |  |\n| Date: 18 JANUARY 2024 TS. DR. LIANG YONG YEOW\u003Cbr>Date: 18 JANUARY 2024 |  |  |  |  |  |\n|  |  |  |  |  |  |\n\nSUPERVISOR’S DECLARATION  \nI hereby declare that I have checked this thesis and in my opinion, this thesis is adequate in terms of scope and quality for the award of the degree of Bachelor of Chemical Engineering.  \nSignature  \nSupervisor’s name  \nDate  \n:  \n: TS. DR. LIANG YONG YEOW: 18 JANUARY 2024  \nSTUDENT’S DECLARATION  \nI hereby declare that the work in this thesis is my own except for quotations and summaries which have been duly acknowledged. The thesis has not been accepted for any degree and is not concurrently submitted for award of other degree.  \nSignature :   \nName : STEPHANIE SU YI CHEIN  \nID Number : KA20107  \nDate : 18 JANUARY 2024  \nDedication  \nFor the ones who dream of stranger worlds.  \nACKNOWLEDGEMENTS  \nI would like to express my sincere gratitude to the following individuals who have contributed significantly to the completion of my partial thesis for the degree of Bachelor of Chemical Engineering:  \nFirst and foremost, I would like to extend my heartfelt appreciation to my supervisor, Ts. Dr. Liang Yong Yeow. His valuable guidance and insightful ideas throughout the research process have been instrumental in shaping the direction of my thesis. He has consistently been available to provide assistance whenever I encountered challenges, and his expertise has greatly enriched my work.  \nI would also like to express my deepest thanks to my family for their unwavering support from the moment I embarked on this thesis journey. Their encouragement, belief in my abilities, and understanding of the demands of my studies have been invaluable. I am truly grateful for their constant presence in my life.  \nAdditionally, I would like to acknowledge the emotional support provided by my friends. Meeting them during my university years has been a stroke of luck. Their presence, words of encouragement, and shared experiences have been sources of inspiration and motivation during both the highs and lows of my research.  \nTo all those mentioned above, I extend my heartfelt thanks for their indispensable contributions to the completion of my thesis. Your guidance, support, and encouragement have bee","cbCaieK267mgCrpt","https://ap.wps.com/l/cbCaieK267mgCrpt","pdf",1238708,78,"English","en",105,"# Declaration of Thesis and Copyright\n# Supervisor’s Declaration\n# Student’s Declaration\n# Dedication\n# Acknowledgements\n# Abstract","[{\"question\":\"What is the purpose of the research project?\",\"answer\":\"To develop a machine learning model that predicts membrane performance in membrane processes, especially permeance and rejection.\"},{\"question\":\"What machine learning method was used?\",\"answer\":\"A multilayer perceptron (fully connected feedforward artificial neural network) implemented in a Jupyter Notebook environment using Python.\"},{\"question\":\"Which data inputs and evaluation metrics were used?\",\"answer\":\"The model used inputs such as membrane type, pressure, temperature, and solute concentration, and evaluated performance using MAE, MSE, RMSE, and R2.\"}]","MACHINE LEARNING-INCORPORATED MEMBRANE PERFORMANCE PREDICTION FOR MEMBRANE PROCESSES - Thesis submitted for the Bachelor of Chemical Engineering | PDF",1789641853,197,{"code":4,"msg":82,"data":83},"ok",{"site_id":75,"language":74,"slug":84,"title":65,"keywords":85,"description":66,"schema_data":86,"social_meta":140,"head_meta":142,"extra_data":144,"updated_unix":79},"machine-learning-incorporated-membrane-performance-prediction-for-membrane-processes-thesis-submitted-for-the-bachelor-of-chemical-engineering","",{"@graph":87,"@context":139},[88,102,122],{"@type":89,"itemListElement":90},"BreadcrumbList",[91,95,97,100],{"item":92,"name":93,"@type":94,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":96,"name":9,"@type":94,"position":14},"https://docshare.wps.com/document/",{"item":98,"name":40,"@type":94,"position":99},"https://docshare.wps.com/document/research-report/",3,{"item":101,"name":65,"@type":94,"position":19},"https://docshare.wps.com/document/machine-learning-incorporated-membrane-performance-prediction-for-membrane-processes-thesis-submitted-for-the-bachelor-of-chemical-engineering/290503/",{"url":101,"name":65,"@type":103,"image":104,"author":109,"headline":65,"publisher":111,"fileFormat":114,"inLanguage":74,"description":66,"dateModified":115,"datePublished":116,"encodingFormat":114,"isAccessibleForFree":117,"interactionStatistic":118},"DigitalDocument",{"url":105,"@type":106,"width":107,"height":108},"https://docshare.wps.com/thumbnails/machine-learning-incorporated-membrane-performance-prediction-for-membrane-processes-thesis-submitted-for-the-bachelor-of-chemical-engineering/290503.png","ImageObject",300,407,{"name":63,"@type":110},"Person",{"url":92,"name":112,"@type":113},"DocShare","Organization","application/pdf","2026-11-09","2026-09-17",true,{"@type":119,"interactionType":120,"userInteractionCount":44},"InteractionCounter",{"@type":121},"ViewAction",{"@type":123,"mainEntity":124},"FAQPage",[125,131,135],{"name":126,"@type":127,"acceptedAnswer":128},"What is the purpose of the research project?","Question",{"text":129,"@type":130},"To develop a machine learning model that predicts membrane performance in membrane processes, especially permeance and rejection.","Answer",{"name":132,"@type":127,"acceptedAnswer":133},"What machine learning method was used?",{"text":134,"@type":130},"A multilayer perceptron (fully connected feedforward artificial neural network) implemented in a Jupyter Notebook environment using Python.",{"name":136,"@type":127,"acceptedAnswer":137},"Which data inputs and evaluation metrics were used?",{"text":138,"@type":130},"The model used inputs such as membrane type, pressure, temperature, and solute concentration, and evaluated performance using MAE, MSE, RMSE, and R2.","https://schema.org",{"og:url":101,"og:type":141,"og:title":65,"og:site_name":112,"og:description":66},"article",{"robots":143,"canonical":101},"index,follow",{"doc_id":61,"site_id":75}]