Two-level and hybrid ensembles of decision trees for high performance concrete compressive strength prediction

HI Erdal - Engineering Applications of Artificial Intelligence, 2013 - Elsevier
Accurate prediction of high performance concrete (HPC) compressive strength is very
important issue. In the last decade, a variety of modeling approaches have been developed …

Advancing monthly streamflow prediction accuracy of CART models using ensemble learning paradigms

HI Erdal, O Karakurt - Journal of Hydrology, 2013 - Elsevier
Streamflow forecasting is one of the most important steps in the water resources planning
and management. Ensemble techniques such as bagging, boosting and stacking have …

High performance concrete compressive strength forecasting using ensemble models based on discrete wavelet transform

HI Erdal, O Karakurt, E Namli - Engineering Applications of Artificial …, 2013 - Elsevier
This paper investigates the use of wavelet ensemble models for high performance concrete
(HPC) compressive strength forecasting. More specifically, we incorporate bagging and …

An evaluation of various data pre-processing techniques with machine learning models for water level prediction

ESK Tiu, YF Huang, JL Ng, N AlDahoul, AN Ahmed… - Natural Hazards, 2022 - Springer
Floods are the most frequent type of natural disaster. It destroys wildlife habitat, damages
bridges, railways, roads, properties, and puts millions of people at risk. As such, flood …

Bagging and boosting variants for handling classifications problems: a survey

SB Kotsiantis - The Knowledge Engineering Review, 2014 - cambridge.org
Bagging and boosting are two of the most well-known ensemble learning methods due to
their theoretical performance guarantees and strong experimental results. Since bagging …

Evaluating influences of seasonal variations and anthropogenic activities on alluvial groundwater hydrochemistry using ensemble learning approaches

KP Singh, S Gupta, D Mohan - Journal of Hydrology, 2014 - Elsevier
Chemical composition and hydrochemistry of groundwater is influenced by the seasonal
variations and anthropogenic activities in a region. Understanding of such influences and …

Big Data with deep learning for benchmarking profitability performance in project tendering

M Bilal, LO Oyedele - Expert Systems with Applications, 2020 - Elsevier
A reliable benchmarking system is crucial for the contractors to evaluate the profitability
performance of project tenders. Existing benchmarks are ineffective in the tender evaluation …

[HTML][HTML] A comparative assessment of bagging ensemble models for modeling concrete slump flow

HY Aydogmus, HI Erdal, O Karakurt, E Namli… - Computers and …, 2015 - koreascience.kr
In the last decade, several modeling approaches have been proposed and applied to
estimate the high-performance concrete (HPC) slump flow. While HPC is a highly complex …

Predicting toxicities of diverse chemical pesticides in multiple avian species using tree-based QSAR approaches for regulatory purposes

N Basant, S Gupta, KP Singh - Journal of Chemical Information …, 2015 - ACS Publications
A comprehensive safety evaluation of chemicals should require toxicity assessment in both
the aquatic and terrestrial test species. Due to the application practices and nature of …

Predicting human intestinal absorption of diverse chemicals using ensemble learning based QSAR modeling approaches

N Basant, S Gupta, KP Singh - Computational Biology and Chemistry, 2016 - Elsevier
Human intestinal absorption (HIA) of the drugs administered through the oral route
constitutes an important criterion for the candidate molecules. The computational approach …