خط مشی دسترسیدرباره ما
ثبت نامثبت نام
راهنماراهنما
فارسی
ورودورود
صفحه اصلیصفحه اصلی
جستجوی مدارک
تمام متن
منابع دیجیتالی
رکورد قبلیرکورد بعدی
Document Type : Latin Dissertation
Language of Document : English
Record Number : 151293
Doc. No : ET23085
Main Entry : Andrew Joel Meador
Title Proper : APPLICATIONS IN GROWTH AND YIELD OF LONGLEAF PINE (PliVUS PAL USTRIS MILL.): A COMPARISON OF ARTIFICIAL NEURAL NETWORKS AND OTHER TRADITIONAL MODELING METHODOLOGES
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Longleaf pine (Pinw pohutris Mill.) is a valuable species that has highlydesirable wood characteristics and pest resistances unlike many other southern pines.Modeling multiple thinnings in longleaf pine introduces sparse data sets that traditionalmodels do not handle well, thus, presenting an ideal situation to test the versatility ofartificial neural networks. Separate neural networks were developed and compared toparametric techniques for a thinning decision model and a hture diameter predictionmodel based on time of thinning. The parametric techniques included logistic regressionand the least square parameter recovery method. Results showed.-....,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL46319.pdf
Title and statement of responsibility and : APPLICATIONS IN GROWTH AND YIELD OF LONGLEAF PINE (PliVUS PAL USTRIS MILL.): A COMPARISON OF ARTIFICIAL NEURAL NETWORKS AND OTHER TRADITIONAL MODELING METHODOLOGES [Thesis]
 
 
 
(در صورت عدم وضوح تصویر اینجا را کلیک نمایید)