基于多元线性回归和人工神经网络的瓦楞原纸性能预测

IF 0.8 4区农林科学 Q3 MATERIALS SCIENCE, PAPER & WOOD

Drewno Pub Date : 2016-01-01 DOI:10.12841/WOOD.1644-3985.144.13

S. Adamopoulos, A. Karageorgos, Elli Rapti, D. Birbilis

引用次数: 10

摘要

难以预测使用含有高回收纤维百分比的异质原料生产的纸制品的性能和行为，这限制了它们的效率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Drewno MATERIALS SCIENCE, PAPER & WOOD-

CiteScore

1.10

自引率

12.50%

发文量

审稿时长

>12 weeks

期刊介绍： Wood. Research papers. Reports. Announcements" ("Drewno") is an international scientific journal that publishes original results of innovatory basic and applied research concerning technological, technical, economic and ecological issues important for the wood science and forest-based industries, including their environment, and interesting to the international recipients. "Drewno" is an Open Access biannual journal. Aims and scope: wood science: anatomy, biology, chemistry, physics wood mechanical and chemical technology, inter alia, sawmilling, composite wood products, wooden construction, furniture making, wood pulp, paper making material engineering, biocomposites, nanocomposites material management environmental protection, safety of the processes, products and working stations biotechnology bioenergy, biofuels forestry: harvesting and wood quality wood-based industries economics The Editorial Board of the journal especially welcomes articles concerning increase in wood resources (wood mobilisation); innovative composites and lignocellulosic materials; new trends in the protection, modification and finishing of wood; biorefining of raw wood material; "green" building; new technologies of wood waste recycling; sustainable development; innovation management; and business networks.