Multi-layer artificial neural network modeling of entropy generation on MHD stagnation point flow of Cross-nanofluid

Reddy, P. Bala Anki; Jakeer, Shaik; Basha, H. Thameem; Reddy, Seethi Reddy Reddisekhar; Kumar, T. Mahesh

doi:10.1080/17455030.2022.2067375

Cited by 17 publications

(5 citation statements)

References 46 publications

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“…This phenomenon has been identified as a replication of the evolutionary process of neural networks observed in the human brain. This model exhibits comparable performance to the human brain with respect to optimization, clustering, learning, classification, prediction, and generalization [12].…”

Section: Ann Modelingmentioning

confidence: 99%

“…Artificial intelligence (AI) finds application in diverse fields such as robotics, computer vision, pattern recognition, information retrieval, natural language processing, medical image computing, machine learning, image processing, data mining, knowledge representation, and other related domains. The artificial neural network (ANN) is a widely used methodology that emulates neural processes to mimic the cognitive functions of the human brain [12,13]. The significance of this factor is found to be crucial in addressing numerous intricate challenges in the field of physical engineering.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Influence of Induced Magnetic Fields and Double-Diffusive Convection on Carreau Nanofluid Flow through Diverse Geometries: A Comparative Study Using Numerical and ANN Approaches

Jakeer,

Reddy,

Easwaramoorthy

et al. 2023

Mathematics

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This current investigation aims to explore the significance of induced magnetic fields and double-diffusive convection in the radiative flow of Carreau nanofluid through three distinct geometries. To simplify the fluid transport equations, appropriate self-similarity variables were employed, converting them into ordinary differential equations. These equations were subsequently solved using the Runge–Kutta–Fehlberg (RKF) method. Through graphical representations like graphs and tables, the study demonstrates how various dynamic factors influence the fluid’s transport characteristics. Additionally, the artificial neural network (ANN) approach is considered an alternative method to handle fluid flow issues, significantly reducing processing time. In this study, a novel intelligent numerical computing approach was adopted, implementing a Levenberg–Marquardt algorithm-based MLP feed-forward back-propagation ANN. Data collection was conducted to evaluate, validate, and guide the artificial neural network model. Throughout all the investigated geometries, both velocity and induced magnetic profiles exhibit a declining trend for higher values of the magnetic parameter. An increase in the Dufour number corresponds to a rise in the nanofluid temperature. The concentration of nanofluid increases with higher values of the Soret number. Similarly, the nanofluid velocity increases with higher velocity slip parameter values, while the fluid temperature exhibits opposite behavior, decreasing with increasing velocity slip parameter values.

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Section: Ann Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exploring the Influence of Induced Magnetic Fields and Double-Diffusive Convection on Carreau Nanofluid Flow through Diverse Geometries: A Comparative Study Using Numerical and ANN Approaches

Jakeer,

Reddy,

Easwaramoorthy

et al. 2023

Mathematics

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“…Between these neural nets, the long short-term memory units are noteworthy [27,36,21,24,29]. Recently deep learning technologies with multi-layer neural networks are widely used to improve the performance of prediction and classification [10,5].…”

Section: Objectives Of the Studymentioning

confidence: 99%

Aspect-based Text Classification for Sentimental Analysis using Attention mechanism with RU-BiLSTM

Yelisetti,

Nellore Geethanjali

2023

SCPE

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Sentiment analysis has gained increasing attention from an educational and social perspective with the huge expansion of user interactions due to the Web’s significant improvement. The connection between an opinion target’s polarity scores and other aspects of the content is defined by aspect-based sentiment analysis. Identifying aspects and determining their different polarities is quite complicated because they are frequently implicit. To overcome these difficulties, efficient hybrid methods are used in aspect-based text classification in sentiment analysis. The existing process evaluates the aspects of polarity by using a Convolutional neural network, and it does not work with Big data. In this work, aspect-based text classification and attention mechanisms are used to assist in filtering out irrelevant information and quickly locating the essential features in big data. Initially, the data is collected, and then the data is preprocessed by using Tokenization, Stop word removal, Stemming, and Lemmatization. After preprocessing, the features are vectorized and extracted using Bag-of-Words and TF-IDF. Then, the extracted features are given into word embeddings by GloVe and Word2vec. It uses Deep Recurrent based Bidirectional Long Short Term Memory (RUBiLSTM) for aspect-based sentiment analysis. The RU-Bi-LSTM method integrates aspect-based embeddings and an attention mechanism for text classification. The attention mechanism focuses on more crucial aspects and the bidirectional LSTM to maintain context in both ways. Finally, the binary and ternary classification outcomes are obtained using the final dense softmax output layer. The proposed RU-BiLSTM uses four reviews and two Twitter datasets. The results of the studies demonstrate the efficacy of the RU-BiLSTM model, which outperformed aspect-based classifications on lengthy reviews and short tweets in terms of evaluation.

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“…Entropy generation in a hybrid nanofluid with the effects of electric field, magnetic field and thermal radiative heat flow is characterized as follows [37][38][39]:…”

Section: Entropy Analysis or Analysis Of Energy Lossmentioning

confidence: 99%

Entropy Analysis of EMHD Hybrid Nanofluid Stagnation Point Flow over a Porous Stretching Sheet with Melting Heat Transfer in the Presence of Thermal Radiation

Kayalvizhi

Vijayakumar

2022

Energies

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In this study, the entropy formation of an electromagnetohydrodynamic hybrid nanofluid at a stagnation point flow towards a stretched surface in the presence of melting heat transfer, second-order slip, porous medium, viscous dissipation and thermal radiation are investigated. Hybrid nanoparticles alumina (Al2O3) and copper (Cu) are considered, with the base fluid water (H2O). Similarity transformations are used to address the governing partial differential equations (PDEs) that lead to the corresponding ordinary differential equations. The resulting ODEs are solved by employing bvp4c solver numerically in the MATLAB package. The effects of temperature, transport, production of entropy and Bejan number Be are graphically exhibited. Higher radiation parameters R and an electric field E lead to an increase in fluid temperature. The velocity boundary layer is lowered by the magnetic field and porous media parameters. The opposite behaviour is observed in the electric field E. As a result, hybrid nanofluid has numerous uses in engineering cosmetics, automotive industry, home industry, for cancer treatment, food packaging, pharmaceuticals, fabrics, paper plastics, paints, ceramics, food colorants, electronics, heat exchangers, water purification, lubricants and soaps as well.

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Multi-layer artificial neural network modeling of entropy generation on MHD stagnation point flow of Cross-nanofluid

Cited by 17 publications

References 46 publications

Exploring the Influence of Induced Magnetic Fields and Double-Diffusive Convection on Carreau Nanofluid Flow through Diverse Geometries: A Comparative Study Using Numerical and ANN Approaches

Exploring the Influence of Induced Magnetic Fields and Double-Diffusive Convection on Carreau Nanofluid Flow through Diverse Geometries: A Comparative Study Using Numerical and ANN Approaches

Aspect-based Text Classification for Sentimental Analysis using Attention mechanism with RU-BiLSTM

Entropy Analysis of EMHD Hybrid Nanofluid Stagnation Point Flow over a Porous Stretching Sheet with Melting Heat Transfer in the Presence of Thermal Radiation

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