船舶碰撞事故发生率居高不下与人为失误有关，而人为失误的发生又受到包括个人因素、环境因素、船舶因素以及组织因素的影响。根据一般的事故统计数据能够初步识别出引发碰撞的人为失误行为，但要进一步建立影响因素与人为失误之间的对应关系却一直是令研究人员困惑的事情。一方面是因为缺少数据，另一方面是缺少方法。我们在收集100个碰撞事故调查报告的基础上，利用数据挖掘技术中的关联规则对人为失误与其影响因素之间的关系进行了挖掘，初步确定了船舶避碰过程中人为失误与引发因素之间的对应关系。

人类社会的需求激发了现代科学技术在海事领域特别是在船舶上的应用。经济、安全、环境保护是人类发展的三大主题，为此，从这三个角度探讨了未来航海技术的发展及其在发展过程中可能会面临的困难与挑战。重点讨论了船型、导航技术以及环境保护措施的未来发展。

大连海事大学的交通信息工程与控制和轮机工程两个学科被国家确定为国家级重点学科，这标志着由海洋船舶驾驶和轮机管理发展而来的航海类学科进入了新的发展阶段。文章从学科的含义、学科与专业的关系等基本概念出发，讨论了航海类专业及其学科的设置和发展历史，以及航海学科应建设的内容，认为航海教育也是建立在学科基础上的，期望能对澄清航海学科与专业的关系起到积极的作用。

探讨了人的可靠性分析技术在船舶避碰中的应用，提出了利用船舶碰撞事故报告以及事故统计数据并结合专家意见评估避碰过程中的人的可靠性的实用技术；给出了人为失误引发碰撞的概率以及失误迫使条件的量值. 所提方法和评价结果为避碰系统中人的可靠性的进一步研究打下了基础，对船舶安全系统的风险分析也有参考价值。

在整理分析有关船模试验资料之后，提出了估算船舶横流阻力系数的近似公式，与实船试验结果比较，能较好的吻合，在此基础上，试算了超大型船靠离码头所需拖轮力的大小，并分析了风、浅水等对靠离力的影响，对操船人员安全、经济靠离码头有一定的参考意义。

Collision of ships is a typical maritime accident that usually happened at a low rate but with disastrous consequence. Human elements play a very important role in collision avoidance. It is reported that human elements were involved in more than 90% of collision accidents. The most important thing for collision avoidance is to make sure that the human being in collision avoidance system is reliable. In this paper, a method called technique for human reliability analysis in ship collision avoidance or THRASCA is presented, which is purposely designed for assessing the human reliability in collision avoidance of ships quantitatively. The analyzing procedure is consisted of seven steps: determining the scope of analysis, initial task analysis, identifying the human elements, expressing the human errors, identifying the performance shaping factors, quantifying the human reliability and expressing the human reliability. Since the method is simple in expression, it could also act as an active aid for those who are in charge of maritime safety affairs. The main difficulties met in designing the method are lack of human element data, lack of proper human error model, the vagueness of the relationship between human error and its shaping factors. To overcome all these difficulties, accident statistics, written accident reports, expert judgment and simulator experiment are taken as the data sources of human element; the techniques such as gray relational assessment, fuzzy logic and rule discovery are used as tools in identifying human elements and their relationships; the human error model are established on the recognition process of collision avoidance as sensing, decision making and action.

It's well known that human elements are deeply involved in collision of ships. Most of human errors or unsafe acts and their causational factors or performance shaping factors (PSFs) have been identified by varies methods such as accident statistics, expert judgment and accident investigation, but the relationship between them has not been depicted clearly yet, not to mention to describe it quantitatively. It is quite necessary to identify the relationship between them for reducing the negative influence of human elements on collision avoidance. In this paper, an attempt to establish the link between unsafe acts in collision of ships and performance shaping factors with the help of data mining technique is presented. For the purpose of this paper, 100 written collision accident reports are collected and analyzed. With the human elemet classification modeled by the authors, all data relating to human elements are sought out from these accident reports and put together forming a small database. With the help of data mining technique, the association rules between each kind of unsafe acts and performance shaping factors are discovered. There are mainly 6 kinds of unsafe acts and 9 kinds of performance shaping factors; each of the unsafe acts is influenced by several PSFs out of 9 PSFs respectively. For example, improper lookout is influenced by knowledge/experience/training, organization and administration, attention, constrained waters, visibility, manning, traffic density, equipment layout and capability of information management, while late action has a close relationship with organization and administration, knowledge/experience/training, constrained waters, and attention. The degree of support and credibility of the relationship between the unsafe acts and PSFs has also been calculated which provide a platform for further analysis of human elements in collision of ships.

For the purpose of evaluating the maritime safety situation in Chinese navigable waters, statistics and analysis work on maritime accidents occurred in Chinese navigable waters in last ten years has been done in this paper. It presents that number of maritime accidents steadily decreased while direct economic loss and number of life loss seems fluctuating during the period 1993-2002. In accordance with the analysis results, except the human factors, which have been involved in most of major maritime accidents, some other factors such as management of shipping companies, ship conditions, conditions of navigable waters, marine traffic volume and maritime traffic safety assuring and supporting system were also play an important role in all those maritime accidents. Based on the results of analysis, some recommendations on measures and policies against the maritime accidents are presented.

It is well known that human errors is involved in most of maritime accidents. For the purpose of reducing the influence of human elements on maritime activities, it is necessary to identify the human unsafe acts in those activities The commonly used methods in identification of human unsafe acts are maritime accident statistics or case analysis. With the statistics data, people could roughly identify what kinds of unsafe acts or human errors have played active role in the accident, however, they often neglected some active unsafe acts while overestimated some mini-unsafe acts because of the inherent shortcoming of the methods. There should be some more accurate approaches for human error identification in maritime accidents. In this paper, the application of technique called grey relational analysis (GRA) into the identification of human unsafe acts is presented. GRA is used to examine the extent of connections between two digits by applying the methodology of departing and scattering measurement to actual distance measurement. Based on the statistics data of maritime accidents occurred in Chinese waters in last 10years, the relationship between the happening times of maritime accidents and that of unsafe acts are established with GRA. In accordance with the value of grey relational grade, the identified main human unsafe acts involved in maritime accidents are ranked in following orders: improper lookout, improper use of radar and equivalent equipment, error of judgment, act not in time, improper communication, improper shiphandling, use of unsafe speed, violating the rule and ignorance of good seamanship. The result shows that GRA is an effective and practical technique in improving the accuracy of human unsafe acts identification.

The ship collision is one of the most significant casualties occurring at sea. Some research on maritime casualty reveals that over 90% of all collisions were attributable to human element. Although frequently occurring unsafe acts in collisions have been roughly identified, very little is known about the human element and the reasons why mistakes occur repeatedly. The main objective of this paper intends to identify the human elements especially the underlying human elements and influencing factors behind the unsafe acts involved in collisions at sea. For this purpose, 100 existing written accident reports are selected and used as the data sources for human element analysis. As compensation, an investigation on the viewpoints of maritime safety related persons has been carried out by questionnaires. A classification for collecting and storing the data of human elements involved in collisions is specially constructed. It seems that Expert's perspectives on human elements involved in collision accident are roughly identical with the actuality data derived from the written reports. It is found that the most frequently involved unsafe act in collision is poor lookout, the underlying human elements are lack of experience and knowledge, and the external factors are fairway