Towards sustainable coastal management: a hybrid model for vulnerability and risk assessment
This paper presents the development of a Hybrid Model (HM) integrated with a Bayesian
Network (BN) for comprehensive coastal vulnerability and risk assessment, with a focus on …
Network (BN) for comprehensive coastal vulnerability and risk assessment, with a focus on …
Machine learning techniques to evaluate the impact of calcium oxide (CaO) and silicon dioxide (SiO2) in supplementary cement materials on the compressive strength …
N Sathiparan, P Jeyananthan… - … Chemistry and Pharmacy, 2024 - Elsevier
This study investigates the application of machine learning models to predict the
compressive strength of pervious concrete that incorporates supplementary cementitious …
compressive strength of pervious concrete that incorporates supplementary cementitious …
Response surface regression and machine learning models to predict the porosity and compressive strength of pervious concrete based on mix design parameters
N Sathiparan, SH Wijekoon, R Ravi… - Road Materials and …, 2024 - Taylor & Francis
This study investigates the influence of aggregate size, aggregate-to-cement ratio, and
compaction effort on pervious concrete's porosity and compressive strength. It proposes …
compaction effort on pervious concrete's porosity and compressive strength. It proposes …
A Multi-Approach Analysis for Monitoring Wave Energy Driven by Coastal Extremes
This research investigates the behavior and frequency evolution of extreme waves in coastal
areas through a combination of physical modeling, spectral analysis, and artificial …
areas through a combination of physical modeling, spectral analysis, and artificial …
Mapping coastal resilience: a Gis-based Bayesian network approach to coastal hazard identification for Queensland's dynamic shorelines
A Durap - Anthropocene Coasts, 2024 - Springer
Coastal regions worldwide face increasing threats from climate change-induced hazards,
necessitating more accurate and comprehensive vulnerability assessment tools. This study …
necessitating more accurate and comprehensive vulnerability assessment tools. This study …
Forecasting Demand and Optimizing Product Ordering in the Supply Chain Using Artificial Intelligence
M Pakbin, Y Rahmati Ghofrani… - International Journal of …, 2024 - kps.artahub.ir
The research aims to predict demand and optimize product ordering within the supply chain
using artificial intelligence. Employing a purposeful sampling method, 12 managers from …
using artificial intelligence. Employing a purposeful sampling method, 12 managers from …
Predicting Color Development in Tomatoes Treated with Hot Water and Exposed to High-Temperature Ethylene Using Support Vector Regression
P Pathmanaban - Available at SSRN 4871557 - papers.ssrn.com
This study investigated the impacts of hot water treatment (HWT) at 50 C or 25 C for 5 min
and high-temperature ethylene (HTE) exposure at varying temperatures (20 C, 30 C, or 35 …
and high-temperature ethylene (HTE) exposure at varying temperatures (20 C, 30 C, or 35 …