From view of situation elements , the limitations of obtaining situation elements for students majoring? in? marine engineering were analyzed .The methods were put forward to improve students'ability of obtaining situation elements , such as de-composing the teaching content and mixing other training courses .In practice, situation awareness of the most students were pro-moted, and their safety management abilities were improved .

Based on the NAM model, which is a lumped hydrological model, the discharge at the Wudaogou Hydrological Station was simulated. Nine flood events with the largest peak flows from the period of 1985 to 2010 were chosen to calibrate the model parameters. Simulation results show that peak flow appeared in advance systematically, and the flood peak phase difference could not be decreased by adjusting model parameters. In order to obtain reasonable results, two improved models are proposed: one is a lumped NAM hydrological model that does not change model parameters but deals with area precipitation by shifting time weighted, and the other is a NAM hydrological model, which is based on sub-catchments and deals with simultaneously weighted area precipitation. Calculation results of the two improved models show that the flood peak phase difference decreases, and the coefficient of determination and the qualified rate increase.

由于滚动轴承不同状态的振动信号具有不同复杂度的特点,提出利用模糊熵和最小二乘支持向量机(LS-SVM)实现轴承故障的准确诊断.模糊熵将模糊理论引入到数据序列的复杂度测度中,能够测量出不同复杂度的数据序列.根据模糊熵计算方法,选择最优参数计算轴承振动信号的模糊熵,作为区分轴承不同故障状态的特征参数.以轴承振动信号的模糊熵为输入,以最小二乘支持向量机为分类器,准确识别轴承故障状态.轴承实测振动信号分析表明,方法能够有效诊断轴承故障,提高故障诊断的准确率.

This paper discusses a fuzzy AHP method being used to calculate weights of indictors in the assessing process of system simulation. The method used triangle fuzzy numbers to establish judgment matrix. Based on the principle of the comparison of fuzzy numbers the vectors of weight are represented by , where, is the value of fuzzy synthetic extent with respect to the i-th object foe m goals. Since fuzzy AHP has considered fuzzy characteristic existing in the people's judgment, the method increase subjective effects and is more reasonable. The application result shows that the method is reasonable, easy and feasible.

In this paper, control problems of an industrial Azeotropic distillation column were discussed and improved. At first, the soft-sensor of water content in the bottom of the column was built based on on-the-spot data, through applying soft-sensor technology of regression. At the same time, an inferential control scheme with constrained control based on soft-sensor was designed. As a result of increasing constrained control in the arithmetic, the reliability and practicability of the system is strengthened. Application of the control system to the column showed that the control system can resolve effectively the problems that the product quality cannot be measured on-line and be close-loop controlled directly, and has realized the bounder control of water content in the bottom of the column.

The action and meaning of the system programming in intelligent buildings is analyzed. Using the fuzzy multi attribute group decision method to rank the system programming projects is brought forward. A method for obtaining the fuzzy judgement matrix and subordinate degree is proposed. The calculating processes and methods about the fuzzy multi attribute group decision method how to rank the system programming projects in intelligent buildings are introduced in detail.

This paper investigates the applicability and feasibility of real-coded GAs for the complete development of fuzzy systems with imbedded constraints; i.e., automatic design of both fuzzy membership functions and rules subject to certain constraints. In this paper, a real-coded GA called RGA is developed, in which chromosomes are represented as real vectors. The constraints associated with the fuzzy systems are explicitly considered and satisfied during the training process of the fuzzy systems by the RGA. The satisfaction of the constraints is done primarily by using tailor-made genetic operators, which are designed based on the coding structure and the required characteristics of the fuzzy systems. We apply the RGA to the design of three fuzzy systems, called fuzzy decision models (FDMs), to model and forecast economic activities in the crude oil tanker sector of maritime transportation. The effects of the RGA's control parameters on the performance of the RGA, including the crossover and mutation rates, multiple mutation, and selection pressure, are investigated in this paper. Our results indicate that the RGA is robust in developing appropriate FDMs with strong modeling and forecasting capability.

This paper presents an improved Smith-NN pre-estimated control method which is designed to overcome the effect caused by controlled object's time-varying, nonlinear and uncertainties when large time-delay is compensated. The studying of the closed loop neural controller and the Smith pre-estimated controller designing and testing prove the method is feasible. From control system simulation, especially experiments on the pH process and dynamic ration weighing process, confirm the effectiveness of the method to overcome large time-delay. This method can easily be realized by intelligent tools based on the assembly language

On the basis of the analysis on the policy-making process of enterprise marketing management, this paper suggests the design methods of marketing DDS model base and the pattern of system function structure. The system design has taken into account the theoretical and technical levels of the system and the developmental feasibility so that it is easy for enterprises to develop and implement.

The application of fuzzy control theory in the ship marine speed control is studied, and the design of a parameter selftuning fuzzy controller is also introduced. The simulation of the fuzzy control system is performed on a PC for a big ship.The results show that the fuzzy controller has good control performance and has reference value for further applications.

Improvement in forecasting accuracy is a difficult task but critical for business success. This paper investigates the potential of neural networks for short- to long-term prediction of monthly tanker freight rates. Procedures are outlined for the development of the neural networks. The problem of under-training and over-training is addressed by controlling the number of iterations during the training process of neural networks. A comparative study of predictive performance between neural networks and ARMA time series models is conducted. Our evience shows that neural networks can significantly outperform time series models, especially for longer-term forecasting. Tel: (313) 763-3081; Fax: (313) 936-8820. Tel: (313) 763-3081; Fax: (313) 936-8820. Tel: (313) 763-3081; Fax: (313) 936-8820. Tel: (313) 763-3081; Fax: (313) 936-8820. Notes Tel: (313) 763-3081; Fax: (313) 936-8820. Tel: (313) 763-3081; Fax: (313) 936-8820.

Fuzzy logic is a technique that attempts to systematically and mathematically emulate human reasoning. This paper investigates the feasibility of applying fuzzy logic to transportation and shipbuilding market modeling, analysis and forecasting. Fuzzy systems called fuzzy decision modelers (FDMs) are developed based on fuzzy logic techniques to model the crude oil tanker freight rate market, the tanker new order market and the tanker scrapping market. Our results show that the FDMs are able to model and forecast these economic systems very well. In addition, the FDMs also provide valuable insights into market mechanisms and market participants' decision-making patterns. The FDMs are mathematical model-free, nonlinear systems capable of capturing complicated relationships among economic variables. The FDMs are easy to develop and easy to interpret. These advantages of fuzzy systems suggest that fuzzy logic techniques are a promising alternative in shipping and shipbuilding market modeling, analysis and forecasting.