Quality Prediction and Abnormal Processing Parameter Identification in Polypropylene Fiber Melt Spinning Using Artificial Intelligence Machine Learning and Deep Learning Algorithms

Application of Soft Computing Techniques to Predict the Strength of Geopolymer Composites

(2022) Qichen Wang et al.   Polymers

Integration of multivariate control charts and decision tree classifier to determine the faults of the quality characteristic(s) of a melt spinning machine used in polypropylene as-spun fiber manufacturing Part I: The application of the Taguchi method and principal component analysis in the processing parameter optimization of the melt spinning process

(2021) Chung-Feng Jeffrey Kuo et al.   TEXTILE RESEARCH JOURNAL

Predictive Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Artificial Intelligence Approaches: MLPNN, ANFIS, and GEP

(2021) Afnan Nafees et al.   Materials

Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Machine Learning Techniques

(2021) Afnan Nafees et al.   Polymers

Optimization of an eco-friendly dyeing process in both laboratory scale and pilot scale supercritical carbon dioxide unit for polypropylene fabrics with special new disperse dyes

(2019) Tarek Abou Elmaaty et al.   Journal of CO2 Utilization

Water free dyeing of polypropylene fabric under supercritical carbon dioxide and comparison with its aqueous analogue

(2018) Tarek Abou Elmaaty et al.   JOURNAL OF SUPERCRITICAL FLUIDS

Classification and Regression Tree (CART) analysis to predict influenza in primary care patients

(2016) Richard K. Zimmerman et al.   BMC INFECTIOUS DISEASES

Influence of the machine tool compliance on the dynamic performance of the servo drives

(2016) Igor Ansoategui et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Fault diagnosis in spur gears based on genetic algorithm and random forest

(2016) Mariela Cerrada et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals

(2016) Chuan Li et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals

(2015) Jaouher Ben Ali et al.   APPLIED ACOUSTICS

Neural network based models for software effort estimation: a review

(2012) Vachik S. Dave et al.   ARTIFICIAL INTELLIGENCE REVIEW

The application of principal component analysis and gray relational method in the optimization of the melt spinning process using the cooling air system

(2012) Chung-Feng Jeffrey Kuo et al.   TEXTILE RESEARCH JOURNAL