By Rachkovskii D.A., Slipchenko S.V.
Difficulties (inherent in compound hierarchical representations) of retaining info at the constitution of coded info and strategies of fixing them by means of "binding" of knowledge substructures are mentioned. one of those dispensed representations is taken into account within which facts are coded through multidimensional binary sparse vectors. the limitations imposed on a binding method are formulated and its implementation is supplied. a few examples of illustration of established information are thought of.
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Extra resources for A binding Procedure for Distributed Binary Data Representations
1. In the AISI ASD approach, no load factors are applied to the nominal loads to obtain the design loads in the evaluation of the design strengths. In the AISI LRFD approach, on the other hand, various linear combinations of the nominal loads are used for the design loads which are then compared with the design strengths. The design strength is the nominal strength divided by a factor of safety ( ) in the AISI ASD approach, and the nominal strength multiplied by a resistance factor ( ) in the AISI LRFD approach.
11 show the global optimum design curves for thickness, web depth-to-thickness ratio, and flange width-to-thickness ratio for hat-shapes for yield stress of 345 N/mm2. 14 show similar results for yield stress of 250 N/mm2. The hat-shape is laterally stable when the wide flange is in compression. Therefore, only the unbraced condition is considered. The bending, combined bending and shear, and web crippling strength constraints control the global optimum design for most cases. 5 kN/m). Deflection constraint is less important for the lower strength steel where the strength constraints dominate the global optimum design.
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A binding Procedure for Distributed Binary Data Representations by Rachkovskii D.A., Slipchenko S.V.