[HTML][HTML] Wire and arc additive manufacturing: Opportunities and challenges to control the quality and accuracy of manufactured parts

D Jafari, THJ Vaneker, I Gibson - Materials & Design, 2021 - Elsevier
Wire and arc additive manufacturing (WAAM) has proven that it can produce medium to
large components because of its high-rate deposition and potentially unlimited build size …

Fuzzy neural networks and neuro-fuzzy networks: A review the main techniques and applications used in the literature

PV de Campos Souza - Applied soft computing, 2020 - Elsevier
This paper presents a review of the central theories involved in hybrid models based on
fuzzy systems and artificial neural networks, mainly focused on supervised methods for …

Mid-term prediction of electrical energy consumption for crude oil pipelines using a hybrid algorithm of support vector machine and genetic algorithm

L Xu, L Hou, Z Zhu, Y Li, J Liu, T Lei, X Wu - Energy, 2021 - Elsevier
The mid-term electrical energy consumption forecasting for crude oil pipelines is helpful for
making important decisions, such as energy consumption target setting, unit commitment …

Residual stresses in wire-arc additive manufacturing–Hierarchy of influential variables

Q Wu, T Mukherjee, A De, T DebRoy - Additive Manufacturing, 2020 - Elsevier
Residual stresses and distortion are common serious defects in wire-arc additive
manufacturing. Commercial thermomechanical models are often used to understand how …

A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks

A Singh, J Amutha, J Nagar, S Sharma - Expert Systems with Applications, 2023 - Elsevier
Abstract Wireless Sensor Networks (WSNs) is a promising technology with enormous
applications in almost every walk of life. One of the crucial applications of WSNs is intrusion …

Comparative evaluation of supervised machine learning algorithms in the prediction of the relative density of 316L stainless steel fabricated by selective laser melting

GO Barrionuevo, JA Ramos-Grez, M Walczak… - … International Journal of …, 2021 - Springer
To find a robust combination of selective laser melting (SLM) process parameters to achieve
the highest relative density of 3D printed parts, predicting the relative density of 316L …

Prediction of surface residual stress in end milling with Gaussian process regression

M Cheng, L Jiao, P Yan, L Feng, T Qiu, X Wang… - Measurement, 2021 - Elsevier
The residual stress has an important influence on the performance of parts such as fatigue
life, and many researches have been carried out for the quantitative evaluation or prediction …

Management of landslides in a rural–urban transition zone using machine learning algorithms—A case study of a National Highway (NH-44), India, in the Rugged …

M Fayaz, G Meraj, SA Khader, M Farooq, S Kanga… - Land, 2022 - mdpi.com
Landslides are critical natural disasters characterized by a downward movement of land
masses. As one of the deadliest types of disasters worldwide, they have a high death toll …

A parallel strategy for predicting the quality of welded joints in automotive bodies based on machine learning

G Chen, B Sheng, R Luo, P Jia - Journal of Manufacturing Systems, 2022 - Elsevier
Due to the complexity of the resistance spot welding process, it is still a challenge to
accurately know the operating status of the welding robot under the current parameter …

Generative modelling of laser beam welded Inconel 718 thin weldments using ANFIS based hybrid algorithm

P Thejasree, KL Narasimhamu, M Natarajan… - International Journal on …, 2022 - Springer
Abstract Laser Beam Welding (LBW) is one of the sophisticated welding processes that find
applications in multiple technical disciplines such as vehicle manufacturing, aviation, and …