Advances in machine learning-and artificial intelligence-assisted material design of steels
G Pan, F Wang, C Shang, H Wu, G Wu, J Gao… - International Journal of …, 2023 - Springer
With the rapid development of artificial intelligence technology and increasing material data,
machine learning-and artificial intelligence-assisted design of high-performance steel …
machine learning-and artificial intelligence-assisted design of high-performance steel …
Practical aspects of the design and use of the artificial neural networks in materials engineering
Artificial neural networks are an effective and frequently used modelling method in
regression and classification tasks in the area of steels and metal alloys. New publications …
regression and classification tasks in the area of steels and metal alloys. New publications …
[HTML][HTML] Shape-constrained multi-objective genetic programming for symbolic regression
We describe and analyze algorithms for shape-constrained symbolic regression, which
allow the inclusion of prior knowledge about the shape of the regression function. This is …
allow the inclusion of prior knowledge about the shape of the regression function. This is …
Deep belief network based hybrid model for building energy consumption prediction
To enhance the prediction performance for building energy consumption, this paper
presents a modified deep belief network (DBN) based hybrid model. The proposed hybrid …
presents a modified deep belief network (DBN) based hybrid model. The proposed hybrid …
Deep-learning-assisted inverse design of dual-spin/frequency metasurface for quad-channel off-axis vortices multiplexing
Recently, the metasurfaces for independently controlling the wavefront and amplitude of two
orthogonal circularly polarized electromagnetic (EM) waves have been demonstrated to …
orthogonal circularly polarized electromagnetic (EM) waves have been demonstrated to …
Modeling of CCT diagrams for tool steels using different machine learning techniques
X Geng, H Wang, W Xue, S Xiang, H Huang… - Computational Materials …, 2020 - Elsevier
Continuous cooling transformation (CCT) diagram is an important basis to make an optimal
heat treatment process of steels with a desired microstructure and properties. Therefore, it is …
heat treatment process of steels with a desired microstructure and properties. Therefore, it is …
Robust metamodels for accurate quantitative estimation of turbulent flow in pipe bends
Pipe bends are inevitable in industrial piping systems, turbomachinery, heat exchangers,
etc. Computational fluid dynamics (CFD), which is commonly employed to understand the …
etc. Computational fluid dynamics (CFD), which is commonly employed to understand the …
A Hybrid Method for Calculating the Chemical Composition of Steel with the Required Hardness after Cooling from the Austenitizing Temperature
The article presents a hybrid method for calculating the chemical composition of steel with
the required hardness after cooling from the austenitizing temperature. Artificial neural …
the required hardness after cooling from the austenitizing temperature. Artificial neural …
Determination of process parameters for selective laser melting of inconel 718 alloy through evolutionary multi-objective optimization
J Tiwari, E Cozzolino, S Devadula… - Materials and …, 2024 - Taylor & Francis
Selective laser melting (SLM) is a sustainable process that offers various environmental
benefits. However, the parts produced from SLM process require post-processing treatments …
benefits. However, the parts produced from SLM process require post-processing treatments …
PSO-tuned support vector machine metamodels for assessment of turbulent flows in pipe bends
Purpose Computational fluid dynamics (CFD) technique is the most commonly used
numerical approach to simulate fluid flow behaviour. Owing to its computationally, cost …
numerical approach to simulate fluid flow behaviour. Owing to its computationally, cost …