Optimum configurational and dimensional design of truss structures

Alspaugh, Dale W.; Kunoo, Kazuo

doi:10.1016/0045-7949(74)90043-1

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1989

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“…The resulting truss is seen in Figure 8(c). This configuration is close to optimal if common truss layouts are considered as candidates (Alspaugh and Kunnoo, 1974).…”

Section: Derivational Analogymentioning

confidence: 76%

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The potential of machine learning techniques for expert systems

Reich

Fenves

1989

AIEDAM

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Expert systems employing current methodologies suffer from two major problems: they are brittle and their development is time-consuming and tedious.Learning, the key to intelligent human behavior and expertise, has the potential of alleviating these difficulties. The paper reviews a number of machine learning techniques and provides a framework for their classification. The description of each technique is followed by an example taken from the domain of structural design. The applicability of machine learning techniques to expert systems is discussed, including some prototype applications and their shortcomings. Three promising research directions are outlined as a partial solution for the shortcomings.

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“…The resulting truss is seen in Figure 8(c). This configuration is close to optimal if common truss layouts are considered as candidates (Alspaugh and Kunnoo, 1974).…”

Section: Derivational Analogymentioning

confidence: 76%

“…This experimentation might discover interesting configurations that can be judged according to the payoff provided by their specification relaxations. A sequence of trusses generated by this method is given in Figure 10(c) (Alspaugh and Kunnoo, 1974). These three approaches to solve the problem can interact.…”

Section: Learning By Discoverymentioning

confidence: 99%