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View article: Development of a machine-learning-based performance prediction model for indirect regenerative evaporative cooling applications supported by experimental and numerical techniques
Development of a machine-learning-based performance prediction model for indirect regenerative evaporative cooling applications supported by experimental and numerical techniques Open
Advanced prediction tools are essential for assessing suitability of regenerative evaporative cooling systems, significantly reducing the time and effort required for extensive testing. Smart algorithms enable optimizing operating conditio…
View article: Exothermic thermosolutal convection in a nanofluid-filled square cavity with a rotating Z-Fin: ISPH and AI integration
Exothermic thermosolutal convection in a nanofluid-filled square cavity with a rotating Z-Fin: ISPH and AI integration Open
This study explores the combined effects of exothermic chemical reactions and Cattaneo–Christov heat flux on thermosolutal convection within a nanofluid-filled square cavity containing a rotating Z-shaped fin. The incompressible smoothed p…
View article: Machine learning-based identification of elite genotypes in the endangered Nilgirianthus ciliatus through qualitative and quantitative trait analysis
Machine learning-based identification of elite genotypes in the endangered Nilgirianthus ciliatus through qualitative and quantitative trait analysis Open
Nilgirianthus ciliatus is an economically valuable endangered medicinal plant with a significant influence on traditional medicine and Ayurveda formulation. Its rarity in natural habitats precludes scientific investigation into its potenti…
View article: Enhanced and predictive modelling of direct shoot regeneration of Evolvulus alsinoides (L.) using ANN machine learning model and genetic stability studies
Enhanced and predictive modelling of direct shoot regeneration of Evolvulus alsinoides (L.) using ANN machine learning model and genetic stability studies Open
Several factors interact to regulate direct in vitro shoot regeneration. Optimization of de novo direct regeneration is a primary prerequisite for the success of genetic transformation experiments. However, achieving an optimized protocol …
View article: A Hybrid Approach of Buongiorno's Law and Darcy–Forchheimer Theory Using Artificial Neural Networks: Modeling Convective Transport in <scp>Al<sub>2</sub>O<sub>3</sub></scp>‐<scp>EO</scp> Mono‐Nanofluid Around a Riga Wedge in Porous Medium
A Hybrid Approach of Buongiorno's Law and Darcy–Forchheimer Theory Using Artificial Neural Networks: Modeling Convective Transport in <span>Al<sub>2</sub>O<sub>3</sub></span>‐<span>EO</span> Mono‐Nanofluid Around a Riga Wedge in Porous Medium Open
The inspiration for this study originates from a recognized research gap within the broader collection of studies on nanofluids, with a specific focus on their interactions with different surfaces and boundary conditions (BCs). The primary…
View article: Dairy factory milk product processing and sustainable of the shelf-life extension with artificial intelligence: a model study
Dairy factory milk product processing and sustainable of the shelf-life extension with artificial intelligence: a model study Open
This study models milk product processing and sustainable of the shelf-life extension in a dairy factory using artificial intelligence. The Cappadocia dairy factory was used to study chemical processes and computational system modeling and…
View article: Improving pressure drop predictions for R134a evaporation in corrugated vertical tubes using a machine learning technique trained with the Levenberg–Marquardt method
Improving pressure drop predictions for R134a evaporation in corrugated vertical tubes using a machine learning technique trained with the Levenberg–Marquardt method Open
The present investigation utilized a machine learning structure to ascertain the pressure drop in vertically positioned, corrugated copper tubes during the evaporation process of R134a. The evaporator was a counter-flow heat exchanger, in …
View article: Integrating artificial intelligence in investigating magneto-bioconvection flow of oxytactic microorganisms and nano-enhanced phase change material in H-type cavity
Integrating artificial intelligence in investigating magneto-bioconvection flow of oxytactic microorganisms and nano-enhanced phase change material in H-type cavity Open
Nano-enhanced phase change materials is an effective way to improve the thermal characteristics and to minimize energy consumption. The bioconvection flow of nano-enhanced phase change materials is gaining more attention in recent investig…
View article: Neural networking-based analysis of heat transfer in MHD thermally slip Carreau fluid flow with heat generation
Neural networking-based analysis of heat transfer in MHD thermally slip Carreau fluid flow with heat generation Open
The formulation of heat transfer in non-Newtonian fluid models remains a topic of great interest for researchers. The ultimate flow differential equations in this direction are non-linear and hence difficult to solve analytically. Therefor…
View article: Determination of optimum insulation thickness in submarines
Determination of optimum insulation thickness in submarines Open
One of the most effective ways to save energy for cooling and heating applications is thermal insulation. Because of this, determining the ideal insulation thickness is a popular topic for publications. The purpose of this study is to dete…
View article: An Intelligent Approach for Predicting Mechanical Properties of High-Volume Fly Ash (HVFA) Concrete
An Intelligent Approach for Predicting Mechanical Properties of High-Volume Fly Ash (HVFA) Concrete Open
Plastic waste (PW) is a major soild waste, which its generation continues to increase globally year in and year out. Proper management of the PW is still a challenge due to its non-biodegradable nature. One of the most convenient ways of m…
View article: The Intraday High-Frequency Trading with Different Data Ranges: A Comparative Study with Artificial Neural Network and Vector Autoregressive Models
The Intraday High-Frequency Trading with Different Data Ranges: A Comparative Study with Artificial Neural Network and Vector Autoregressive Models Open
With the High-Frequency Trading process, which is a subclass of algorithmic trading transactions, intraday information has increasing importance. Traditional statistical methods often fall short in capturing the intricate patterns and vola…
View article: Predicting Stock Market Index and Credit Default Swap Spreads Using Artificial Intelligence and Determining Nonlinear Relations
Predicting Stock Market Index and Credit Default Swap Spreads Using Artificial Intelligence and Determining Nonlinear Relations Open
In this study, a simulation model has been established to forecast the stock price index of Borsa Istanbul (BIST100) and 5-year maturity credit default swap (CDSs) spreads with an artificial intelligence approach. In the study where short-…
View article: Modeling and survival exploration of breast carcinoma: A statistical, maximum likelihood estimation, and artificial neural network perspective
Modeling and survival exploration of breast carcinoma: A statistical, maximum likelihood estimation, and artificial neural network perspective Open
The core objective of this research is to describe the behavior of the distribution using the MLE method to estimate its parameters, as well as to determine the optimal Artificial Neural Network method by comparing it to the maximum likeli…
View article: The Role of Technical Indicators in the Intraday Prediction of Stock Markets: Artificial Neural Network Models for Borsa Istanbul
The Role of Technical Indicators in the Intraday Prediction of Stock Markets: Artificial Neural Network Models for Borsa Istanbul Open
In this study, two simulation models have been developed to predict the main stock price index of Borsa Istanbul (BIST100) with an artificial intelligence approach. In order to analyze the role of technical indicators in intraday predictin…
View article: Levenberg–Marquardt Training Technique Analysis of Thermally Radiative and Chemically Reactive Stagnation Point Flow of Non-Newtonian Fluid with Temperature Dependent Thermal Conductivity
Levenberg–Marquardt Training Technique Analysis of Thermally Radiative and Chemically Reactive Stagnation Point Flow of Non-Newtonian Fluid with Temperature Dependent Thermal Conductivity Open
We have examined the magnetized stagnation point flow of non-Newtonian fluid towards an inclined cylindrical surface. The mixed convection, thermal radiation, viscous dissipation, heat generation, first-order chemical reaction, and tempera…
View article: Prediction of Mechanical Properties of Rubberized Concrete Incorporating Fly Ash and Nano Silica by Artificial Neural Network Technique
Prediction of Mechanical Properties of Rubberized Concrete Incorporating Fly Ash and Nano Silica by Artificial Neural Network Technique Open
The use of enormous amounts of material is required for production. Due to the current emphasis on the environment and sustainability of materials, waste products and by-products, including silica fume and fly ash (FA), are incorporated in…
View article: Artificial Neural Networking Magnification for Heat Transfer Coefficient in Convective Non-Newtonian Fluid with Thermal Radiations and Heat Generation Effects
Artificial Neural Networking Magnification for Heat Transfer Coefficient in Convective Non-Newtonian Fluid with Thermal Radiations and Heat Generation Effects Open
In this study, the Casson fluid flow through an inclined, stretching cylindrical surface is considered. The flow field is manifested with pertinent physical effects, namely heat generation, viscous dissipation, thermal radiations, stagnati…
View article: Computational Analysis on Magnetized and Non-Magnetized Boundary Layer Flow of Casson Fluid Past a Cylindrical Surface by Using Artificial Neural Networking
Computational Analysis on Magnetized and Non-Magnetized Boundary Layer Flow of Casson Fluid Past a Cylindrical Surface by Using Artificial Neural Networking Open
In this article, we constructed an artificial neural networking model for the stagnation point flow of Casson fluid towards an inclined stretching cylindrical surface. The Levenberg–Marquardt training technique is used in multilayer percep…
View article: Estimation of heat transfer parameters of shell and helically coiled tube heat exchangers by machine learning
Estimation of heat transfer parameters of shell and helically coiled tube heat exchangers by machine learning Open
Shell and helically coiled tube heat exchangers (SHCTHEXs) are heat exchangers that only take up a small space and enable greater heat transfer area compared to traditional models. Information on 21 different SHCTHEXs obtained from catalog…
View article: Prediction of heat transfer coefficient, pressure drop, and overall cost of double-pipe heat exchangers using the artificial neural network
Prediction of heat transfer coefficient, pressure drop, and overall cost of double-pipe heat exchangers using the artificial neural network Open
Typically, success in the estimation of machine learning is expected to rise with increasing input parameters, whereas the noise issue may rarely arise owing to redundant input factors undesirably influencing the learning algorithm. The pa…
View article: Optimization of Bioconvective Magnetized Walter’s B Nanofluid Flow towards a Cylindrical Disk with Artificial Neural Networks
Optimization of Bioconvective Magnetized Walter’s B Nanofluid Flow towards a Cylindrical Disk with Artificial Neural Networks Open
Nanotechnology is a fundamental component of modern technology. Researchers have concentrated their efforts in recent years on inventing various algorithms to increase heat transmission rates. Using nanoparticles in host fluids to dramatic…
View article: Analysis of Flow Characteristics of Carreau Fluid in a Vertical Stretching Cylinder with Artificial Intelligence Approach
Analysis of Flow Characteristics of Carreau Fluid in a Vertical Stretching Cylinder with Artificial Intelligence Approach Open
In this study, the flow characteristics of Carreau fluid flow on a vertical stretching cylinder immersed in a porous medium were analyzed in detail with an artificial intelligence approach. Local skin friction, local Nusselt number and loc…
View article: Do Artificial Neural Networks Always Provide High Prediction Performance? An Experimental Study on the Insufficiency of Artificial Neural Networks in Capacitance Prediction of the 6H-SiC/MEH-PPV/Al Diode
Do Artificial Neural Networks Always Provide High Prediction Performance? An Experimental Study on the Insufficiency of Artificial Neural Networks in Capacitance Prediction of the 6H-SiC/MEH-PPV/Al Diode Open
In this paper, we study a new model that represents the symmetric connection between capacitance–voltage and Schottky diode. This model has a symmetrical shape towards the horizontal direction. In recent times, works conducted on artificia…
View article: Artificial Neural Networking (ANN) Model for Drag Coefficient Optimization for Various Obstacles
Artificial Neural Networking (ANN) Model for Drag Coefficient Optimization for Various Obstacles Open
For various obstacles in the path of a flowing liquid stream, an artificial neural networking (ANN) model is constructed to study the hydrodynamic force depending on the object. The multilayer perceptron (MLP), back propagation (BP), and f…
View article: Artificial Neural Networking (ANN) Model for Convective Heat Transfer in Thermally Magnetized Multiple Flow Regimes with Temperature Stratification Effects
Artificial Neural Networking (ANN) Model for Convective Heat Transfer in Thermally Magnetized Multiple Flow Regimes with Temperature Stratification Effects Open
The convective heat transfer in non-Newtonian fluid flow in the presence of temperature stratification, heat generation, and heat absorption effects is debated by using artificial neural networking. The heat transfer rate is examined for t…
View article: An Experimental Investigation on Workability and Bleeding Behaviors of Cement Pastes Doped with Nano Titanium Oxide (n-TiO2) Nanoparticles and Fly Ash
An Experimental Investigation on Workability and Bleeding Behaviors of Cement Pastes Doped with Nano Titanium Oxide (n-TiO2) Nanoparticles and Fly Ash Open
In this study, the workability of cement-based grouts containing n-TiO2 nanoparticles and fly ash has been investigated experimentally. Several characteristic quantities (including, but not limited to, the marsh cone flow time, the mini sl…