Grey Systems: Theory and Applications
Grey Systems: Theory and Applications
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DOI：
10.1108/gs.2011.1.3.274.1
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发表时间：
2011-10
期刊：
影响因子：
--
通讯作者：
K. Hipel
中科院分区：
文献类型：
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作者：
K. Hipel
刘思丰教授和林毅教授就灰色系统这一重要课题撰写了另一本开创性的著作。2006年，同一作者写了一本广受欢迎的书，名为《灰色信息：理论与实际应用》，也由施普林格出版社出版。我很高兴地说，他们的第二本书对灰色系统构成了显着的扩展和改进，他们以前的好书。因此，如果你已经拥有一本2006年的书，你可以通过获得一本他们最近的书来做一个有价值的学术投资，以了解灰色系统关键领域的最新思想和进展。自然出现的问题是为什么灰色系统在历史上的这个时候如此重要。答案很简单：社会面临的许多挑战性问题都是由相互关联的复杂系统组成的，这些系统表现出高度的不确定性，而且测量很少。例如，为了有效地应对气候变化，必须尽可能多地了解自然系统（如大气、海洋、地质和水文系统）与社会系统（包括能源生产、工业、农业和城市系统）之间的复杂相互作用。这些相互关联的系统及其潜在的紧急行为所涉及的深度不确定性，加上缺乏观测，意味着对处理这种不确定性的正式工具的需求很高。幸运的是，多年来已经开发出了一系列基于数学的方法和技术：丰富多样的基于概率的工具，Lotfi Zadeh创立的模糊集，Z. Pawlak，Yakov Ben‐Haim完善的信息差距模型，Baoding Liu开发的不确定性理论，以及Julong Deng在1982年建立的灰色系统。描述不确定性的上述和其他方法基于不同的公理，因此对于处理各种各样的不确定情况是高度互补的。
Professors Sifeng Liu and Yi Lin have written another pioneering book on the important topic of grey systems. In 2006, the same authors wrote the well‐received book entitled Grey Information: Theory and Practical Applications which was also published by Springer‐Verlag. I am pleased to say that their second book on Grey Systems constitutes a significant expansion and improvement of their previous fine book. Accordingly, if you already possess a copy of the 2006 book, you can make a worthwhile academic investment by obtaining a copy of their recent book in order to be cognizant of the latest ideas and advancements in the crucial field of grey systems.The question that naturally arises is why grey systems are of such great import at this point in history. The answer is quite straightforward: many challenging problems facing society consist of interconnected complex systems of systems exhibiting high uncertainty and having few measurements. For example, in order to effectively combat climate change, one must understand as much as possible the complex interactions among natural systems such as atmospheric, oceanic, geological, and hydrological systems, with societal systems including energy production, industrial, agricultural, and city systems. The deep uncertainty involved with these interconnected systems of systems and their potential emergent behavior, coupled with a dearth of observations, mean that formal tools for handling this uncertainty are in high demand. Fortunately, an arsenal of mathematically based methodologies and techniques have been developed over the years: a rich variety of probabilistic‐based tools, fuzzy sets founded by Lotfi Zadeh, rough sets started by Z. Pawlak, information‐gap modeling perfected by Yakov Ben‐Haim, uncertainty theory developed by Baoding Liu, and grey systems established by Julong Deng in 1982. The foregoing and other approaches to describing uncertainty are based upon different axioms and are thereby highly complementary for tackling a wide variety of uncertain situations.