Investigating the efficacy of machine learning tools in modeling the continuous stabilization and carbonization process and predicting carbon fiber properties

Prediction of mechanical properties of carbon fiber based on cross-scale FEM and machine learning

(2019) Zhenchao Qi et al.   COMPOSITE STRUCTURES

Machine learning assisted design of high entropy alloys with desired property

(2019) Cheng Wen et al.   ACTA MATERIALIA

Prediction and optimization of epoxy adhesive strength from a small dataset through active learning

(2019) Sirawit Pruksawan et al.   SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS

Support vector regression modelling and optimization of energy consumption in carbon fiber production line

(2018) Gelayol Golkarnarenji et al.   COMPUTERS & CHEMICAL ENGINEERING

Production of Low Cost Carbon-Fiber through Energy Optimization of Stabilization Process

(2018) Gelayol Golkarnarenji et al.   Materials

A machine learning case study with limited data for prediction of carbon fiber mechanical properties

(2018) Gelayol Golkarnarenji et al.   COMPUTERS IN INDUSTRY

Classifying Four Carbon Fiber Fabrics via Machine Learning: A Comparative Study Using ANNs and SVM

(2016) Min Zhao et al.   Applied Sciences-Basel

High strength and high modulus carbon fibers

(2015) Han Gi Chae et al.   CARBON

Dynamic Prediction Models and Optimization of Polyacrylonitrile (PAN) Stabilization Processes for Production of Carbon Fiber

(2015) Hamid Khayyam et al.   IEEE Transactions on Industrial Informatics

Processing, structure, and properties of gel spun PAN and PAN/CNT fibers and gel spun PAN based carbon fibers

(2015) Bradley A. Newcomb et al.   POLYMER ENGINEERING AND SCIENCE

The Bi-Directional Prediction of Carbon Fiber Production Using a Combination of Improved Particle Swarm Optimization and Support Vector Machine

(2014) Chuncai Xiao et al.   Materials

Accelerated Materials Design of Lithium Superionic Conductors Based on First-Principles Calculations and Machine Learning Algorithms

(2013) Koji Fujimura et al.   Advanced Energy Materials