A comparison of machine learning methods for cutting parameters prediction in high speed turning process

Fault and sensor error diagnostic strategies for a vapor compression refrigeration system by using fuzzy inference systems and artificial neural network

(2015) Necati Kocyigit   INTERNATIONAL JOURNAL OF REFRIGERATION-REVUE INTERNATIONALE DU FROID

Modeling and optimization of parameters for minimizing surface roughness and tool wear in turning Al/SiCp MMC, using conventional and soft computing techniques

(2015) S.K. Tamang et al.   Advances in Production Engineering & Management

Prediction of surface roughness of end milling operation using genetic algorithm

(2014) G. Mahesh et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A Methodology for Cutting Force Prediction in Side Milling

(2014) Mehmet Aydın et al.   MATERIALS AND MANUFACTURING PROCESSES

Integrated approach for optimising machining parameters, tool wear and surface quality in multi-pass turning operations

(2014) M.I. Mgwatu   Advances in Production Engineering & Management

An ANN approach for predicting the cutting inserts performances of different geometries in hard turning

(2014) N. Senthilkumar et al.   Advances in Production Engineering & Management

Particle swarm optimization approach for modelling a turning process

(2014) M. Hrelja et al.   Advances in Production Engineering & Management

Use of Neural Networks in Prediction and Simulation of Steel Surface Roughness

(2013) T. Saric et al.   International Journal of Simulation Modelling

Modelling of laser processing cut quality by an adaptive network-based fuzzy inference system

(2009) Sivarao Subramonian et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE

Regression analysis, support vector machines, and Bayesian neural network approaches to modeling surface roughness in face milling

(2008) B. Lela et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY