Titlebook: Applications of Artificial Intelligence in Engineering Problems; Proceedings of the 1 D. Sriram,R. Adey Conference proceedings 1986 Springe

Auditory-Nerve

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书目名称Applications of Artificial Intelligence in Engineering Problems网络公开度学科排名




书目名称Applications of Artificial Intelligence in Engineering Problems被引频次




书目名称Applications of Artificial Intelligence in Engineering Problems被引频次学科排名




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书目名称Applications of Artificial Intelligence in Engineering Problems年度引用学科排名




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书目名称Applications of Artificial Intelligence in Engineering Problems读者反馈学科排名

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overhaul

Hierarchical Conceptual Clusteringal techniques for this purpose, developed in numerical data analysis, are often inadequate because they cluster objects solely on the basis of a numerical measure of similarity. Thus the clusters obtained have no simple descriptions. This limitation is overcome by the conceptual hierarchical methods

CERE

Lessons Learned Developing a Planning Systemtop-down structured programming, but we also discuss our own policies (the good, the bad and the unimplemented) from which others might choose or avoid to their benefit. Another category of lessons learned is knowledge of what we do not know how to do. An example of this is pattern matching across p

航海太平洋

Counter Examples and Explanationsneralization, AGAPE, based on the principle of structural matching has been implemented. Examples are progressively transformed to get the same form i.e. to be instantiations of a common formula, with different links between variables. That formula, and the common links between variables give the ge

inhibit

共同时代

成份

Interpretation of Pipe Networks by Magnetic Sensingto enforce the correct placement of steel in new concrete, and is even more important in assessing as-built structures. Rebar mapping is essential in post-construction operations such as coring and anchor emplacement in nuclear power plants. Pipe mapping is invaluable to the excavation and repair of

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