Sustainability in wood products: a new perspective for handling natural diversity

M Schubert, G Panzarasa, I Burgert - Chemical Reviews, 2022 - ACS Publications
Wood is a renewable resource with excellent qualities and the potential to become a key
element of a future bioeconomy. The increasing environmental awareness and drive to …

The role of artificial neural networks in prediction of mechanical and tribological properties of composites—a comprehensive review

UMR Paturi, S Cheruku, NS Reddy - Archives of Computational Methods …, 2022 - Springer
The artificial neural network (ANN) approach motivated by the biological nervous system is
an inspiring mathematical tool that simulates many complicated engineering applications …

An artificial neural network model for predicting compression strength of heat treated woods and comparison with a multiple linear regression model

S Tiryaki, A Aydın - Construction and Building Materials, 2014 - Elsevier
This paper aims to design an artificial neural network model to predict compression strength
parallel to grain of heat treated woods, without doing comprehensive experiments. In this …

Pre- and/or Postharvest Silicon Application Prolongs the Vase Life and Enhances the Quality of Cut Peony (Paeonia lactiflora Pall.) Flowers

J Song, Y Li, J Hu, J Lee, BR Jeong - Plants, 2021 - mdpi.com
Peony is an important ornamental plant and has become increasingly popular for cut flower
cultivation. However, a short vase life and frequent poor vase quality severely restrict its …

Artificial neural network and regression models for performance prediction of abrasive waterjet in rock cutting

G Aydin, I Karakurt, C Hamzacebi - The International Journal of Advanced …, 2014 - Springer
An experimental study is carried out for modeling the rock cutting performance of abrasive
waterjet. Kerf angle (KA) is considered as a performance criteria and modeled using artificial …

Artificial neural network and partial least square regressions for rapid estimation of cellulose pulp dryness based on near infrared spectroscopic data

LR Costa, GHD Tonoli, FR Milagres, PRG Hein - Carbohydrate polymers, 2019 - Elsevier
The content of water in fiber suspension and affects pulp refining, bleaching and draining
operations. Cellulose pulp dryness estimate through near infrared (NIR) spectroscopy …

Regression and ANN models for predicting MOR and MOE of heat-treated fir wood

AR Haftkhani, F Abdoli, A Sepehr… - Journal of Building …, 2021 - Elsevier
Modulus of rupture (MOR) and modulus of elasticity (MOE) of heat-treated fir wood (abies
sp) were predicted by simple and multiple regression and artificial neural network (ANN) …

Comparison of artificial neural network and multiple linear regression models to predict optimum bonding strength of heat treated woods

S Tiryaki, Ş Özşahin, İ Yıldırım - International Journal of Adhesion and …, 2014 - Elsevier
In this study, an artificial neural network (ANN) model was developed for predicting an
optimum bonding strength of heat treated woods. The MATLAB Neural Network Toolbox was …

Performance prediction of diamond sawblades using artificial neural network and regression analysis

G Aydin, I Karakurt, C Hamzacebi - Arabian Journal for Science and …, 2015 - Springer
This paper is concerned with the application of artificial neural networks (ANNs) and
regression analysis for the performance prediction of diamond sawblades in rock sawing. A …

Failure load prediction of adhesively bonded GFRP composite joints using artificial neural networks

B Birecikli, ÖA Karaman, SB Çelebi… - Journal of Mechanical …, 2020 - Springer
There are different process parameters of bonding joints in the literature. The main objective
of the paper was to investigate the effects of bonding angle, composite lay-up sequences …