Results 261 to 270 of about 786,876 (299)

Recurrent Algorithms for Selecting the Maximum Input

Neural Processing Letters, 2004
In this paper, two novel recurrent algorithms for selecting the maxima of a set S containing M positive real numbers are introduced. In the first one the aim is to determine a threshold T such that only the maxima of S lie above it, while in the second one, each element of S is reduced independently of the rest until either it becomes zero (if it is ...
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Use of index selection in recurrent selection programs in maize

Euphytica, 1981
Phenotypic and genotypic correlations were examined for four traits in seven populations of maize (Zea mays L.) undergoing recurrent selection. Correlations among grain yield and percentage of grain moisture, root lodging, and stalk lodging were low (|r| 0.5).
O. S. Smith, A. R. Hallauer, W. A. Russell   +2 more
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Recurrence rate after highly selective vagotomy

World Journal of Surgery, 1988
AbstractSeveral ways of analyzing recurrence figures are presented in order to demonstrate the difficult interpretation of recurrence rate with highly selective vagotomy (HSV) in 262 patients operated on for duodenal ulcer with an almost complete follow‐up.
D C, Busman, A, Volovics, J D, Munting
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Two-locus inbreeding measures for recurrent selection

Theoretical and Applied Genetics, 1977
For a population undergoing recurrent selection, a method is presented for determining the average inbreeding coefficients at the end of each breeding cycle. The coefficients are derived in terms of probability measures that genes are identical by descent.
S C, Choy, B S, Weir
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Basic Concepts in Recurrent Selection

1988
In Chapter 1, we briefly discussed the difference between agricultural crop breeding and forest tree breeding. We presented the need to broaden the concept of tree breeding to include the ability to handle a multiplicity of objectives and environments. We also discussed mechanisms of natural selection, and concepts of gene expression and environmental ...
Gene Namkoong, Hyun Chung Kang, Jean Sébastien Brouard   +2 more
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General Recurrent Selection Systems

1988
In Chapter 3, we defined a complete cycle of selection (Fig. 3.2) and developed simple recurrent selection (SRS) starting with a basic breeding system of simple mass selection in which seed is collected from the individuals judged best by their field performance In this chapter, we consider more elaborate breeding systems with primary focus on the ...
Gene Namkoong, Hyun Chung Kang, Jean Sébastien Brouard   +2 more
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Recurrent neural network for dynamic portfolio selection

Applied Mathematics and Computation, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chi-Ming Lin, Jih-Jeng Huang, Mitsuo Gen, Gwo-Hshiung Tzeng   +3 more
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Computing Digit Selection Regions for Digit Recurrences

2007 IEEE International Conf. on Application-specific Systems, Architectures and Processors (ASAP), 2007
Digit selection is often the most difficult part of evaluating digit recurrence equations. Knowing the correct bounds on the digit selection regions is important for a number of reasons: to ensure that the recurrences converge, to know how to initialize the computation, to know the maximal convergence range of input values, and to compute the ...
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Sex selection and recurrence of anencephaly.

International journal of biological research in pregnancy, 1982
The case presented here involves recurrent anencephalies and so-called sex selection, a method applied to dispel anxiety about a third pregnancy in a couple free from hereditary predisposition to births with congenital malformation of the central nervous system.
K, Kasai, S, Nakayama, S S, Shik, Y, Yoshida   +3 more
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Using recurrent selection to improve GA performance

1997
Genetic algorithms (GA's) are based on the idea that solutions to otherwise intractable problems can be derived by mimicking natural evolution. With a few exceptions, however, GA's are limited to haploid implementations with random breeding among a single population, failing to exploit a number of strategies that are found in nature.
Ben S. Hadad, Christoph F. Eick
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