Matches in SemOpenAlex for { <https://semopenalex.org/work/W1637762634> ?p ?o ?g. }
- W1637762634 abstract "The problem of modeling forest tree growth curves with an artificial neural network (NN) is examined. The NN parametric form is shown to be a suitable model if each forest tree plot is assumed to consist of several differently growing sub-plots. The predictive Bayesian approach is used in estimating the NN output. Data from the correlated curve trend (CCT) experiments are used. The NN predictions are compared with those of one of the best parametric solutions, the Schnute model. Analysis of variance (ANOVA) methods are used to evaluate whether any observed differences are statistically significant. From a Frequentist perspective the differences between the Schnute and NN approach are found not to be significant. However, a Bayesian ANOVA indicates that there is a 93% probability of the NN approach producing better predictions on average." @default.
- W1637762634 created "2016-06-24" @default.
- W1637762634 creator A5018614798 @default.
- W1637762634 date "1999-06-07" @default.
- W1637762634 modified "2023-09-27" @default.
- W1637762634 title "Artificial Neural Network Modeling of Forest Tree Growth" @default.
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