Artificial intelligence neural network and fuzzy modelling of unsteady Sisko trihybrid nanofluids for cancer therapy with entropy insights DOI Creative Commons

A. Divya,

Thandra Jithendra, Muhammad Jawad

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Ноя. 14, 2024

The main objective of the current endeavor is to monitor hypothetical processes utilizing a Sisko tri-hybrid fluid over rotating disk with entropy generation suspended in Darcy-Forchheimer porous medium. Electro Magneto Hydro Dynamics (EMHD), non-linear thermal radiation and exponential thermal- space dependent heat source/sink coefficients are considered intent conceiving an Runge-Kutta-Fehlberg method shooting procedures integrated combination Adaptive Neuro-Fuzzy Inference System (ANFIS) Reptile Search Algorithm (RSA). Then, ANFIS-RSA, used predict Nusselt number, skin friction co-efficient radial tangential velocities. Reliable self-similarity variables have reduced partial differential set equations into ordinary equation. According empirical evidence, parameter rises velocity whereas for magnetic field azimuthal axial velocities visualizations decreasing trend, respectively. Bejan number electric effects. Also, ANFIS-RSA indicates that model attained high level precision terms (98.13%), (98.18%) (98.91%). Thus, longer rendering nanoparticles here might, makes them potentially helpful regulating therapeutic impact management treatment cancer.

Язык: Английский

Artificial Intelligence Based Analysis for Magnetized Casson Fluid in Partially Heated Cavity Rooted with Heated Fin DOI Creative Commons
Khalil Ur Rehman, Wasfı Shatanawi, Yian Yian Lok

и другие.

International Journal of Thermofluids, Год журнала: 2025, Номер unknown, С. 101095 - 101095

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

3

Intelligent neuron based interpretation of carreau trihybrid nanofluid model with streamline analysis: Configuration of distinct geometries DOI Creative Commons

Basma Souayeh,

Ali Haider, Assad Ayub

и другие.

Journal of Radiation Research and Applied Sciences, Год журнала: 2024, Номер 17(4), С. 101154 - 101154

Опубликована: Окт. 17, 2024

Язык: Английский

Процитировано

6

Mathematical modeling of radiative nanofluid flow over nonlinear stretching sheet using artificial neural networks and Levenberg-Marquardt scheme: Applications in solar thermal energy DOI
Umar Farooq,

Sana Ullah Saqib,

Shan Ali Khan

и другие.

Solar Energy Materials and Solar Cells, Год журнала: 2024, Номер 281, С. 113265 - 113265

Опубликована: Ноя. 22, 2024

Язык: Английский

Процитировано

3

Highest electro-viscous energy and lowest irreversibility analysis for Maxwell fluid in transient microchannel flow DOI
Sujit Saha, Balaram Kundu

Applied Thermal Engineering, Год журнала: 2025, Номер unknown, С. 125764 - 125764

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

AI-driven modeling of bioconvective nanofluid flow: An ANN approach to anisotropic slip and heat transfer in 3D systems DOI

Mehdi Mahboobtosi,

H. Ehsani,

Ali Mirzagoli Ganji

и другие.

International Communications in Heat and Mass Transfer, Год журнала: 2025, Номер 165, С. 109035 - 109035

Опубликована: Май 14, 2025

Язык: Английский

Процитировано

0

Artificial intelligence neural network and fuzzy modelling of unsteady Sisko trihybrid nanofluids for cancer therapy with entropy insights DOI Creative Commons

A. Divya,

Thandra Jithendra, Muhammad Jawad

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Ноя. 14, 2024

The main objective of the current endeavor is to monitor hypothetical processes utilizing a Sisko tri-hybrid fluid over rotating disk with entropy generation suspended in Darcy-Forchheimer porous medium. Electro Magneto Hydro Dynamics (EMHD), non-linear thermal radiation and exponential thermal- space dependent heat source/sink coefficients are considered intent conceiving an Runge-Kutta-Fehlberg method shooting procedures integrated combination Adaptive Neuro-Fuzzy Inference System (ANFIS) Reptile Search Algorithm (RSA). Then, ANFIS-RSA, used predict Nusselt number, skin friction co-efficient radial tangential velocities. Reliable self-similarity variables have reduced partial differential set equations into ordinary equation. According empirical evidence, parameter rises velocity whereas for magnetic field azimuthal axial velocities visualizations decreasing trend, respectively. Bejan number electric effects. Also, ANFIS-RSA indicates that model attained high level precision terms (98.13%), (98.18%) (98.91%). Thus, longer rendering nanoparticles here might, makes them potentially helpful regulating therapeutic impact management treatment cancer.

Язык: Английский

Процитировано

2