Automation for the Maritime Industries by Edited by: J Aranda, M A Armada, J M de la Cruz

By Edited by: J Aranda, M A Armada, J M de la Cruz

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At least, four scenarios should be considered for the analysis. Two scenarios, namely night (case 1) and day (case 2), as specified in chapter 13 of the FSS Code; and, two further scenarios (case 3 and case 4) based on reduced escape route availability are considered for the day and night case, as specified in the appendix. The Guide permits a big freedom in the model choice with the following limits: − Each person is represented in the model individually. − The abilities of each person are determined by a set of parameters, some of which are probabilistic.

Some advantages of the ANN-ES combination are: ƒ It can accumulate the knowledge by learning the previous fault information. ƒ Every ANN can be trained independently when using the multi-layer structure. ƒ The rules of diagnosis reasoning will be automatically obtained during the training process of the network. ƒ Knowledge and the rules will be stored in the net topology and the connecting weight values, thus avoiding the problem of “match impact” and “combination explosion”. It is suitable for on-line operation.

Et all. 1997. Development of operation-aided system for chemical processes. Expert Systems with Applications. 12: pp 455-464 [24] Kramer M. A. and Finch F. E. 1988. Development and classification of expert systems for chemical process fault diagnosis. Robotics and Computer integrated Manufacturing. 4: pp 437-446 [25] Li. T. 1989. Expert Systems for Engineering Diagnosis: Styles, requirements for tools, and adaptability. Ed Tzafestas S. G. Knowledge-based Systems Diagnosis, Supervision, and Control, pp.

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