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A metamodeling of complex calculation procedures (static systems) is investigated with the aim to create low-complexity surrogate models that are applicable in low-computing-power real-time (RT) measurement systems. Unlike the single-parameter error criteria and minimum description length measure, the proposed compound-squared-relative-error measure forces the group method of data handling (GMDH) algorithm to prefer the models having the smallest compound deviation of accuracy and execution time from the given thresholds and thus generally leads to more favorable models with respect to both conditions. Approximation errors, execution speed, and the applicability of the derived GMDH models in RT flow-rate measurements of natural gas are discussed and compared with the corresponding models derived by artificial neural network and support vector regression. [ABSTRACT FROM AUTHOR]

Describes an indirect tracking of the measurement system characteristic by using a periodic multiple-point autocalibration. Unsteady, nonlinear function that depends upon time and ambient conditions; Application of a tangent method to the ideal characteristic; Verification of the efficiency of the algorithm for direct current generation; Measurement of internal references.

The topic of neighborhood redevelopment is central to residential appraisal and the lending process. We examine both the effect of neighborhood upgrading and decline, captured by subsidized new residential construction and sustained property tax delinquency respectively, on the sales price of one-to-two family homes. The research uses a two stage hedonic price model of 12,100 individual residential sales in Cleveland, Ohio during 1992-94. Results show a significant positive effect of $670 on the sales price of existing housing for each new unit built in a one-to-two block area. A decrease in sales price of $778 is associated with a 1% Increase in the tax delinquency rate. The spatial variability of these effects is also explored. [ABSTRACT FROM AUTHOR]