Data-driven models for predicting solar radiation in semi-arid regions

M Jamei, N Bailek, K Bouchouicha… - Computers, Materials …, 2023 - diva-portal.org
Solar energy represents one of the most important renewable energy sources contributing to
the energy transition process. Considering that the observation of daily global solar radiation …

Ensemble classifiers and their applications: a review

A Rahman, S Tasnim - arXiv preprint arXiv:1404.4088, 2014 - arxiv.org
Ensemble classifier refers to a group of individual classifiers that are cooperatively trained
on data set in a supervised classification problem. In this paper we present a review of …

Soft computing ensemble models based on logistic regression for groundwater potential mapping

PT Nguyen, DH Ha, M Avand, A Jaafari, HD Nguyen… - Applied Sciences, 2020 - mdpi.com
Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …

Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping

BT Pham, T Nguyen-Thoi, C Qi, T Van Phong, J Dou… - Catena, 2020 - Elsevier
Using multiple ensemble learning techniques for improving the predictive accuracy of
landslide models is an active research area. In this study, we combined a radial basis …

Spatial prediction of landslides using a hybrid machine learning approach based on random subspace and classification and regression trees

BT Pham, I Prakash, DT Bui - Geomorphology, 2018 - Elsevier
A hybrid machine learning approach of Random Subspace (RSS) and Classification And
Regression Trees (CART) is proposed to develop a model named RSSCART for spatial …

Blockchain and random subspace learning-based IDS for SDN-enabled industrial IoT security

A Derhab, M Guerroumi, A Gumaei, L Maglaras… - Sensors, 2019 - mdpi.com
The industrial control systems are facing an increasing number of sophisticated cyber
attacks that can have very dangerous consequences on humans and their environments. In …

Quantifying hourly suspended sediment load using data mining models: case study of a glacierized Andean catchment in Chile

K Khosravi, L Mao, O Kisi, ZM Yaseen, S Shahid - Journal of Hydrology, 2018 - Elsevier
Suspended sediment has significant effects on reservoir storage capacity, the operation of
hydraulic structures and river morphology. Hence, modeling suspended sediment loads …

Computer-aided classification of gastrointestinal lesions in regular colonoscopy

P Mesejo, D Pizarro, A Abergel… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
We have developed a technique to study how good computers can be at diagnosing
gastrointestinal lesions from regular (white light and narrow banded) colonoscopic videos …

Two decades on the artificial intelligence models advancement for modeling river sediment concentration: State-of-the-art

T Rajaee, H Jafari - Journal of Hydrology, 2020 - Elsevier
Simulation approaches employed in sediment processes are important for watershed
management and environmental impact assessment. Use of Stochastic models that based …

Gene selection for microarray data classification using a novel ant colony optimization

S Tabakhi, A Najafi, R Ranjbar, P Moradi - Neurocomputing, 2015 - Elsevier
The high-dimensionality of microarray data with small number of samples has presented a
difficult challenge for the microarray data classification task. The aim of gene selection is to …