[HTML][HTML] Fifty years of data envelopment analysis
Abstract Data Envelopment Analysis (DEA) has emerged as a powerful analytical tool,
revolutionising the field of Operational Research (OR) and contributing to advancements in …
revolutionising the field of Operational Research (OR) and contributing to advancements in …
Statistical and Artificial Intelligence-based Tools for Building Energy Prediction: A Systematic Literature Review
The application of statistical and artificial intelligence (AI) tools in building energy prediction
(BEP) is considered one of the most effective advances toward improving energy efficiency …
(BEP) is considered one of the most effective advances toward improving energy efficiency …
Predicting compressive strength of cement-stabilized earth blocks using machine learning models incorporating cement content, ultrasonic pulse velocity, and …
N Sathiparan, P Jeyananthan - Nondestructive Testing and …, 2024 - Taylor & Francis
The quality monitoring technique for Cement stabilised earth blocks (CSEBs) is so
challenging that it is often neglected. This study has investigated the possibility of using …
challenging that it is often neglected. This study has investigated the possibility of using …
Daily scale streamflow forecasting in multiple stream orders of Cauvery River, India: Application of advanced ensemble and deep learning models
Accurate forecasts of streamflow (Q flow) are crucial for optimal management of water
reservoir systems and preparing for catastrophic events such as floods. Although several …
reservoir systems and preparing for catastrophic events such as floods. Although several …
Effect of aggregate size, aggregate to cement ratio and compaction energy on ultrasonic pulse velocity of pervious concrete: prediction by an analytical model and …
N Sathiparan, P Jeyananthan… - Asian Journal of Civil …, 2024 - Springer
The purpose of present study is to examine how the UPV of pervious concrete changes with
three parameters: compaction energy, aggregate size and aggregate-to-cement ratio. The …
three parameters: compaction energy, aggregate size and aggregate-to-cement ratio. The …
Data-driven predictive modeling of steel slag concrete strength for sustainable construction
AS Albostami, RKS Al-Hamd, AA Al-Matwari - Buildings, 2024 - rke.abertay.ac.uk
Conventional concrete causes significant environmental problems, including resource
depletion, high CO 2 emissions, and high energy consumption. Steel slag aggregate (SSA) …
depletion, high CO 2 emissions, and high energy consumption. Steel slag aggregate (SSA) …
[HTML][HTML] Prediction of Dielectric Constant in Series of Polymers by Quantitative Structure-Property Relationship (QSPR)
This work is devoted to the investigation of dielectric permittivity which is influenced by
electronic, ionic, and dipolar polarization mechanisms, contributing to the material's capacity …
electronic, ionic, and dipolar polarization mechanisms, contributing to the material's capacity …
[HTML][HTML] Improving the accuracy of honey bee forage class mapping using ensemble learning and multi-source satellite data in Google Earth Engine
In semi-arid agro-pastoral environments of Africa, beekeeping is widely recognized as an
important activity to improve and diversify livelihoods. Although the scientific identification of …
important activity to improve and diversify livelihoods. Although the scientific identification of …
[HTML][HTML] An unsupervised learning-based generalization of Data Envelopment Analysis
In this paper, we introduce an unsupervised machine learning method for production frontier
estimation. This new approach satisfies fundamental properties of microeconomics, such as …
estimation. This new approach satisfies fundamental properties of microeconomics, such as …
[HTML][HTML] Support Vector Frontiers with kernel splines
Among recent methodological proposals for efficiency measurement, machine learning
methods are playing an important role, particularly in the reduction of overfitting in classical …
methods are playing an important role, particularly in the reduction of overfitting in classical …