The discovery of new materials is one of the driving forces to promote the development of
modern society and technology innovation, the traditional materials research mainly …

Screening new materials and decoding their structure-property relationships is a time-
consuming and costly task in the laboratory. This research proposes the use of machine …

The present study compares the optimization using Artificial Neural Networks (ANN) and
Adaptive Network-based Fuzzy Inference System (ANFIS) in the sugarcane bagasse …

Reinforced refractories have been demonstrated to be economically and technically useful
in industrial furnaces to improve energy efficiency. Nevertheless, there is a lack of …

In this paper, an adaptive network-based fuzzy inference system (ANFIS) model has been
established to predict the flow stress of Ti600 alloy during hot deformation process. This …

In this paper, the relative texture coefficient (RTC) of nanocrystalline (NC) nickel as a
function of electroplating parameters has been modeled using artificial neural network …

In this paper, a fuzzy neural network (FNN) prediction model has been employed to
establish the relationship between processing parameters and mechanical properties of Ti …

The characterization of the material surface of the machine tool result should be known to
assess quality of the product. Currently, the evaluation of product quality of machine tools is …

This paper attempts to demonstrate the applicability of artificial neural networks to the
estimation of steel properties, cyclic strain‐hardening exponent and cyclic strength …

Nitriding is usually used to improve the surface properties of steel materials. In this way, the
wear resistance of steels is improved. We conducted a series of studies in order to …