Böcker av Qi Zhou

作者写作的内容全部是出自于自己真实的经历和身边发生的事。写作陆续在网络上发表时，得到了众多网友的喜爱。其中不乏有网友留言鼓励我出书，于是萌发了出版的想法。在此作者想借用奥地利著名作家史蒂芬-茨威格写在他发表在的"昨日世界"的那段序言来诠释自己的写作： "我从未把我个人看得如此重要，以致于非要把我自己的生平历史向傍人讲述不可。是因为，在我鼓足勇气开始写这本以自己为主角--或更确切地说，以我为中心的书之前所发生的事件，灾难和考验远远超过任何一代人所经历过的。我见证了理性遭遇到最可怕到失败，野蛮取得来最惊人到胜利。历史上从未有过象我们这一代人，道德会从如此高尚到文明堕落到如此低下的程度。从我开始长胡须，到胡须开始灰白，这样短短的时间跨度，亦即半个世纪之内，所发生的激剧变迁大大超过了以往十代人所经历的。以致我时常感到我一生所过的不是一种生活而是完全不同的好几种。当我无意中说到我生活时会情不自禁地问自己：我的哪一种生活？是第二次世界大战前，还是二次世界大战之间的，还是今天的？"本书没有任何虚拟的文学构思，全部都是接地气的真实事实。作品从作者1949年出生写到1994年移民美国前经历的四十五年。

This book investigates two types of static multi-fidelity surrogates modeling approaches, sequential multi-fidelity surrogates modeling approaches, the multi-fidelity surrogates-assisted efficient global optimization, reliability analysis, robust design optimization, and evolutionary optimization. Multi-fidelity surrogates have attracted a significant amount of attention in simulation-based design and optimization in recent years. Some real-life engineering design problems, such as prediction of angular distortion in the laser welding, optimization design of micro-aerial vehicle fuselage, and optimization design of metamaterial vibration isolator, are also provided to illustrate the ability and merits of multi-fidelity surrogates in support of engineering design. Specifically, lots of illustrative examples are adopted throughout the book to help explain the approaches in a more "e;hands-on"e; manner. This book is a useful reference for postgraduates and researchers of mechanical engineering, as well as engineers of enterprises in related fields.

Recent advancements in computer technology have allowed for designers to have direct control over the production process through the help of computer-based tools, creating the possibility of a completely integrated design and manufacturing process. Over the last few decades, "artificial intelligence" (AI) techniques, such as machine learing and deep learning, have been topics of interest in computer-based design and manufacturing research fields. However, efforts to develop computer-based AI to handle big data in design and manufacturing have not yet been successful. This Special Issue aims to collect novel articles covering artificial intelligence-based design, manufacturing, and data-driven design. It will comprise academics, researchers, mechanical, manufacturing, production and industrial engineers and professionals related to engineering design and manufacturing.