[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122554-en":3,"doc-seo-122554-105":30,"detail-sidebar-cat-0-en-105":91},{"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":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122554,13056703020460,"Valentina","https://ap-avatar.wpscdn.com/avatar/be000253dac470eee5d?_k=1778207105932848923",8,"Research & Report","Development of an Interpretable Maritime Accident Prediction System Using Machine Learning Techniques - Master of Science Thesis","This master’s thesis develops an interpretable maritime accident prediction system using machine learning techniques to support risk modeling with explainable outputs. The study defines research objectives and requirements, then evaluates feasibility across economic, technical, social, regulatory, and environmental dimensions. A literature review compares traditional and statistical maritime accident analysis with modern machine learning, focusing on the interpretability gap and explainable AI (XAI). The work proceeds through system analysis, proposed design artifacts, and implementation using selected algorithms.","Master’s Thesis  \nOn  \nDevelopment of an Interpretable Maritime Accident Prediction System Using Machine Learning  \nTechniques  \nIn Partial Fulfillment ofthe requirements for the academic  \ndegree \"Master of Science (M.Sc.)\"  \nSubmitted by: Ali Kashif Syed  \nMatriculation Number: 7024270  \nExaminer 1: Prof. Dr Marcus Bentin  \nExaminer 2: Prof. Dipl.-Ing. Freerk  \nMeyer  \nHochschule Emden-Leer  \nTable Of Contents:  \nList of Tables: ............................................................................................................................................... iv  \nList of Figures: .............................................................................................................................................. iv  \n[Acknowledgement ....................................................................................................................................... vi](Acknowledgement ....................................................................................................................................... vi)  \n[Statement of Authorship ...............................](Statement of Authorship ...............................)............................................................................................. vii  \nAbstract ...................................................................................................................................................... viii  \n1. Introduction .............................................................................................................................................. 9  \n1.1 Research Objectives: ......................................................................................................................... 10  \n1.2 Software Requirements: ................................................................................................................... 10  \n1.3 Hardware Requirements:.................................................................................................................. 11  \n1.4 Maritime Context and Global Impact: .............................................................................................. 12  \n2. Feasibility Study ...................................................................................................................................... 13  \n2.1 Economic Feasibility.......................................................................................................................... 14  \n2.2 Technical Feasibility .......................................................................................................................... 14  \n2.3 Social Feasibility ................................................................................................................................ 14  \n2.4 Regulatory Feasibility ........................................................................................................................ 15  \n2.5 Environmental Feasibility.................................................................................................................. 15  \n3. Literature Review .................................................................................................................................... 16  \n3.1. Introduction ..................................................................................................................................... 16  \n3.2. Traditional and Statistical Approaches to Maritime Accident Analysis ........................................... 16  \n3.3. The Centrality of Human Factors ..................................................................................................... 17  \n3.4. The Rise of Machine Learning for Predictive Risk Modelling........................................................... 18  \n3.5. The Interpretability Gap: From Black Box to Explainable AI (XAI) ................................................... 19  \n3.6. Identification of the Research Gap an","cbCain8VnynXoi92","https://ap.wps.com/l/cbCain8VnynXoi92","pdf",1972875,1,93,"English","en",105,"# Introduction\n## Research Objectives\n## Software Requirements\n## Hardware Requirements\n## Maritime Context and Global Impact\n# Feasibility Study\n## Economic Feasibility\n## Technical Feasibility\n## Social Feasibility\n## Regulatory Feasibility\n## Environmental Feasibility\n# Literature Review\n## Traditional and Statistical Approaches to Maritime Accident Analysis\n## The Centrality of Human Factors\n## The Rise of Machine Learning for Predictive Risk Modelling\n## The Interpretability Gap: From Black Box to Explainable AI (XAI)\n# System Analysis\n## Existing System\n## Disadvantages of Existing System\n## Proposed System\n# System Design\n## System Architecture\n## Data Flow Diagram\n## UML Diagrams\n# Implementation\n## Applying Algorithms","[{\"question\":\"What is the primary goal of the thesis?\",\"answer\":\"To develop an interpretable maritime accident prediction system using machine learning so that predictive risk modeling includes explainable outputs.\"},{\"question\":\"How does the thesis address interpretability?\",\"answer\":\"It frames the work around the interpretability gap from black-box models to explainable AI (XAI) and motivates why interpretability is needed for maritime risk modelling.\"},{\"question\":\"What feasibility aspects are evaluated before system development?\",\"answer\":\"The thesis evaluates feasibility across economic, technical, social, regulatory, and environmental dimensions.\"}]","Development of an Interpretable Maritime Accident Prediction System Using Machine Learning Techniques - 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