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Since large-scale multi-objective problems (LSMOPs) have huge decision variables, the traditional evolutionary algorithms are facing difficulties of low exploitation efficiency and high exploration costs in solving LSMOPs. Therefore, this paper ...

Wave propagation in elastodynamic problems in solids often requires fine computational meshes. In this work we propose to combine stabilized finite element methods (FEM) with an artificial neural network (ANN) correction term to solve such ...

• Finite elements for mixed velocity–stress problems in elastodynamics are presented.
• An artificial neural network correction term for the discrete problem is introduced.
• The correction term allows for accurate problem solving on ...

Intelligent reflecting surface (IRS), in which a large number of tunable reflective elements are employed, can enhance the wireless propagation environment in an acceptable manner. Although this issue is operated via intelligently reflecting the ...

Artificial intelligence algorithms play a key role in solving multimodal urban mobility problems, this study outlines a scheme covering bus, boat, and pedestrian transport modes. This involves designing an Artificial Neural Network (ANN) model to ...

The incidence of facial fractures is on the rise globally, yet limited studies are addressing the diverse forms of facial fractures present in 3D images. In particular, due to the nature of the facial fracture, the ...

• 3D facial fractures rising, challenging 2D imaging; 3D needed for accurate localization.
• Proposed VFHA-CAM detects fractures using weakly-supervised learning without pixel labels.
• VFHA-CAM improves detection accuracy by 20% and ...

The estimation of the maximum displacement of steel beams with hexagonal web openings under impact loads is crucial for the anti-impact design of structures. The dynamic characteristics are complex, and the maximum displacement can be obtained ...

Determining ultra-low cycle fatigue (ULCF) life of stainless steel typically involves laborious and time-consuming tests. While machine learning offers an efficient solution for fatigue life prediction, the inherent demand for sufficient training ...

• TLNN to predict ULCF life using small datasets was proposed by combining ANN and TL.
• The TL strategy in TLNN model enhanced the predictive capacity of ANN model.
• The TLNN-Syn with TL and synthetic data on regression problem was ...

The enhancement of photovoltaic (PV) arrays through reconfiguration presents a promising avenue for increasing the global maximum power (GMP) and improving overall array performance. This enhancement is achieved by minimizing differences between ...

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The performance of substitute osteoconductive scaffolds in guiding new bone formation and creating vital biological conditions in living organisms is of crucial importance. In this study, bioresorbable scaffolds were synthesized by incorporating ...

This study presents a novel hybrid ensemble strategy based on an inputs-outputs amalgamation technique for estimating the rate of penetration (ROP) of tunnel boring machines (TBMs). Notably, accurate estimation of TBM performance reduces risks ...

• Accurate estimation of TBM performance reduces risks that can arise during tunnelling work.
• A hybrid ensemble strategy for estimating the rate of penetration (ROP) of TBMs is presented.
• A portion of the main database was used to ...

Nonlinear equation systems (NESs) are common in practical applications, and solving them is an important task in numerical computation. Evolutionary algorithms (EAs) for handling NESs have received considerable attention. EAs generate a large ...

Participants in the supply chain may have different information, leading to incomplete or inaccurate information when making decisions. To this end, a process and machine learning based collaborative scheduling algorithm for all materials is proposed. ...

In the current study, authors have studied the heat transfer through ternary hybrid nanofluid (THNF) between the gap of a disk and cone, where both are co-rotating with regard to the other. The authors have developed a mathematical model of THNF ...

• Fuel consumption can be predicted using soil and tractor-implement parameters.
• Tractive force has the highest influence on the predicted fuel consumption rate.
• Increased hidden layer neurons do not necessarily improve algorithm-...

Artificial intelligence (AI) requires complex neurocomputing algorithms (NCAs) for robustness in predictive modeling. Since 1990, a plethora of NCAs have evolved, challenging selection of the most intelligent and error-tolerant model for ...

In this paper, we investigate the method of solving partial differential equations (PDEs) using artificial neural network (ANN) structures, which have been actively applied in artificial intelligence models. The ANN model for solving PDEs offers ...

The introduction of hybrid alternating current (AC)/direct current (DC) distribution networks led to several developments in smart grid and decentralized power system technology. The paper concentrates on several topics related to the operation of ...

Tensile properties of multifilament polyester woven fabrics are of great importance for their end uses such as parachutes, sails, tents, sleeping bags, filters and surgical textiles. The filament fineness, weave type and weave density have a great ...${}^{\mathrm{}}$

A theoretical framework is constructed for the Casson–Carreau nanofluid flow over a curved surface that is stretched exponentially. Artificial intelligence and machine learning are in vogue as the technologies that involve them, have expanded ...

This paper proposes a solution to enhance and compare different neural network (NN)-based side-slip angle estimators. The feed-forward neural networks (FFNNs), recurrent neural networks, long short-term memory units (LSTMs), and gated recurrent ...

The paper describes three lossy data compression techniques based on the principal component analysis (PCA), which are compared using the image compression task. The presented approach uses both classical PCA method based on the eigen-...

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• Classical PCA compression outweighs neural nets in image quality and operation time.
• Appropriate learning algorithm is essential for the neural PCA compression.
• Neural PCA compression can have an advantage in online data ...