Modelling flood susceptibility based on deep learning coupling with ensemble learning models

Y Li, H Hong - Journal of Environmental Management, 2023 - Elsevier
Modelling flood susceptibility is an indirect way to reduce the loss from flood disaster. Now,
flood susceptibility modelling based on data driven model is state-of-the-art method such as …

Multi ceramic particles inclusion in the aluminium matrix and wear characterization through experimental and response surface-artificial neural networks

BN Sharath, CV Venkatesh, A Afzal, N Aslfattahi… - Materials, 2021 - mdpi.com
Lightweight composite materials have recently been recognized as appropriate materials
have been adopted in many industrial applications because of their versatility. The present …

Poultry fat biodiesel as a fuel substitute in diesel-ethanol blends for DI-CI engine: Experimental, modeling and optimization

N Santhosh, A Afzal, Ü Ağbulut, AA Alahmadi… - Energy, 2023 - Elsevier
The purpose of the present study is to evolve an alternate non-edible source for the
synthesis of biodiesel and use it as a fuel substitute in diesel-ethanol blends for DI-CI …

A critical review of supersonic flow control for high-speed applications

A Aabid, SA Khan, M Baig - Applied Sciences, 2021 - mdpi.com
In high-speed fluid dynamics, base pressure controls find many engineering applications,
such as in the automobile and defense industries. Several studies have been reported on …

Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms

A Afzal, S Alshahrani, A Alrobaian, A Buradi, SA Khan - Energies, 2021 - mdpi.com
This work aims to model the combined cycle power plant (CCPP) using different algorithms.
The algorithms used are Ridge, Linear regressor (LR), and upport vector regressor (SVR) …

Experimental investigation of the mechanical properties of carbon/basalt/SiC nanoparticle/polyester hybrid composite materials

K Karthik, D Rajamani, EP Venkatesan, MI Shajahan… - Crystals, 2023 - mdpi.com
In recent years, many researchers have focused on the preparation of carbon and basalt
fiber-reinforced composites. As a result, the composites have gained popularity as an …

Machine learning approach for predicting concrete compressive, splitting tensile, and flexural strength with waste foundry sand

V Mehta - Journal of Building Engineering, 2023 - Elsevier
The scarcity of landfilling and the growing expense of disposal, recycling, and reusing
industrial byproducts have become attractive alternatives to removal. There are several sorts …

ANFIS modeling of biodiesels' physical and engine characteristics: A review

K Janardhana, S Sridhar, CK Dixit, M Deivakani… - Heat …, 2021 - Wiley Online Library
Population increase has resulted in an increase in the worldwide demand for alternative
fuels due to depleting resources. There is a periodic increase in concern about the engine …

Influence of heat treatment and reinforcements on tensile characteristics of aluminium AA 5083/silicon carbide/fly ash composites

S Nagaraja, R Kodandappa, K Ansari, MS Kuruniyan… - Materials, 2021 - mdpi.com
The effect of reinforcements and thermal exposure on the tensile properties of aluminium AA
5083–silicon carbide (SiC)–fly ash composites were studied in the present work. The …

Assessing waste marble powder impact on concrete flexural strength using Gaussian process, SVM, and ANFIS

N Sharma, MS Thakur, R Kumar, MA Malik… - Processes, 2022 - mdpi.com
The study's goal is to assess the flexural strength of concrete that includes waste marble
powder using machine learning methods, ie, ANFIS, Support vector machines, and …