Machine Learning Algorithms and Applications in Engineering
暫譯: 工程中的機器學習演算法與應用

機器學習 (Machine Learning, ML) 是人工智慧的一個子領域，利用軟計算和演算法使計算機能夠自主學習，識別觀察數據中的模式，建立解釋世界的模型，並在沒有明確預先編程的規則和模型的情況下進行預測。本書討論了機器學習在工程領域的各種應用，以及機器學習演算法在解決從生物醫學、交通、供應鏈和物流到製造和工業等挑戰性工程問題中的使用。通過眾多案例研究，本書將幫助研究人員和實務工作者選擇正確的選項和策略來管理組織任務。

Prasenjit Chatterjee is an Associate Professor of Mechanical Engineering Department at MCKV Institute of Engineering, India. He has published over 80 research papers in various international journals and has received numerous awards including Outstanding Researcher Award and University Gold Medal. He has been the Guest Editor of several special issues and has edited and authored several books on decision-making approaches and sustainability. He is the Lead Series Editor of International Perspectives on Decision Analysis and Operations Research, Emerald Group Publishing. Dr. Chatterjee is one of the developers of a new data-driven multiple-criteria decision-making method called Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS).
Morteza Yazdani works at Universidad Loyola Andalucia, Spain. Previously he finished his post-doctoral research at the University of Toulouse and was a lecturer the European University of Madrid. He participates in the editorial board of the International Journal of Decision Support System Technology and is a reviewer in different journals. His main research areas are decision-making modelling and fuzzy decision system in application of supply chain and energy systems and has published several journal articles.
Francisco de Asís Fernández Navarro has earned his PhD in Computer Science and Artificial Intelligence from the University of Malaga, Spain. He also obtained a degree in Market Research from the Open University of Catalonia (UOC). He was awarded at the European Space Agency Noordwijk, The Netherlands with a postdoctoral fellowship in computational management and currently works as an Associate Professor at the Loyola University of Andalusia, Department of Quantitative Methods.
Javier Pérez-Rodríguez earned his PhD in ICT from the University of Granada, Spain. In 2018 he joined the Department of Quantitative Methods at the University of Loyola, Andalucía as an Associate Professor. His research is focused on Computer Science and Artificial Intelligence and Bioinformatics. Within the area of machine learning, specifically, his works have been about pattern recognition and classification and has published several papers in reputable journals. His residency at the Institut für Mathematik und Informatik of the University of Greifswald, Germany was with Professor Stanke, who develops and maintains one of the most prestigious automatic gene recognition systems at present at an international level.

Prasenjit Chatterjee 是印度 MCKV 工程學院機械工程系的副教授。他在各種國際期刊上發表了超過 80 篇研究論文，並獲得了包括傑出研究者獎和大學金獎在內的多項獎項。他曾擔任多個特刊的客座編輯，並編輯和撰寫了幾本有關決策方法和可持續性的書籍。他是 Emerald Group Publishing 出版的《國際決策分析與運營研究系列》的首席系列編輯。Chatterjee 博士是新型數據驅動的多準則決策方法「根據妥協解的替代方案測量與排名」（Measurement of Alternatives and Ranking according to COmpromise Solution，簡稱 MARCOS）的開發者之一。

Morteza Yazdani 目前在西班牙洛約拉安達盧西亞大學工作。此前，他在圖盧茲大學完成了博士後研究，並曾擔任馬德里歐洲大學的講師。他參與了《國際決策支持系統技術期刊》的編輯委員會，並擔任多個期刊的審稿人。他的主要研究領域是決策建模和模糊決策系統在供應鏈和能源系統中的應用，並發表了幾篇期刊文章。

Francisco de Asís Fernández Navarro 獲得了西班牙馬拉加大學的計算機科學和人工智慧博士學位。他還在加泰羅尼亞開放大學（UOC）獲得了市場研究學位。他曾在荷蘭北海岸的歐洲太空總署獲得計算管理的博士後獎學金，目前擔任洛約拉安達盧西亞大學定量方法系的副教授。

Javier Pérez-Rodríguez 獲得了西班牙格拉納達大學的資訊與通信技術博士學位。2018 年，他加入洛約拉安達盧西亞大學定量方法系擔任副教授。他的研究專注於計算機科學、人工智慧和生物資訊學。在機器學習領域，他的研究主要涉及模式識別和分類，並在多個知名期刊上發表了幾篇論文。他在德國格賴夫斯瓦爾德大學的數學與計算機科學研究所的居留期間，與 Stanke 教授合作，該教授目前開發和維護著國際上最具聲望的自動基因識別系統之一。