This book is devoted to fuzzy quantitative studies in managerial science, discussing the philosophical background and decision-making essentials. For reference, a series of practical examples illustrate broad areas of application that are important in project risk management problems, and in complicated mega projects. Using computers to simulate human intelligence with fuzzy approaches is the basis of "Fuzzy-AI model," which offers an efficient tool capable of simulating human intelligence in order to perform digitized decision inference and quantitative information management.

Professor Lin Shaopei

FICE(U.K.), CEng, (U.K)., BE, ME, MS.

China regional Chairman, PMI-GAC (U.S.A.)

Executive Director, ICE China Training and Education Centre (U.K.)

Former Board Director, PMI (Project Management Institution) GAC (Global Accreditation Center for Degree Programs), U.S.A.

Former Director General, ICE (Institution of Civil Engineers, U.K.) Shanghai Branch

The Author serves as a professor in S;hanghai Jiao Tong University, China since 1986, Former Director, PM Teaching and Research Center, School of Mechanical Engineering; and Technical Director, Institute of Engineering Management, School of Naval Architecture, Ocean and Construction Engineering, devoted to teaching and research in engineering, management as well as social consulting work for more than 50 years.

Professor Lin has been the author of seven books (Economic Analyses for Bidding &Tendering Decision; System Analyses and Computer Solutions; Conceptual Design of Structures; Comparative Design of Structures, Computer Methods of project Management; Planning and Design of Smart Residential Zone, etc.). Published more than hundreds of papers, edited around dozen of Proceedings and special volumes in Engineering and Management.

Philosophical Consideration of Quantitative management.- The role of "Fuzz-AI Model" in Quantitative Management.- The Conceptual Investigation of "Deep Data" and "Deep Knowledge".- Fuzzy Quantitative Risk Management.- Quantitative Studies in Risk Management by Knowledge Engineering.- Fuzzy Quantitative Management in Economics.- Fuzzy Programming Modeling for Decision Making.- The Advances in Quantitative Management in Decision.