Application of meta-heuristic algorithms for training neural networks and deep learning architectures: A comprehensive review
The learning process and hyper-parameter optimization of artificial neural networks (ANNs)
and deep learning (DL) architectures is considered one of the most challenging machine …
and deep learning (DL) architectures is considered one of the most challenging machine …
Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications
Abstract Machine learning is one of the key pillars of industry 4.0 that has enabled rapid
technological advancement through establishing complex connections among …
technological advancement through establishing complex connections among …
Influence of data splitting on performance of machine learning models in prediction of shear strength of soil
The main objective of this study is to evaluate and compare the performance of different
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
Shallow landslide susceptibility map**: A comparison between logistic model tree, logistic regression, naïve bayes tree, artificial neural network, and support vector …
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices,
and can cause social upheaval and loss of life. As a result, many scientists study the …
and can cause social upheaval and loss of life. As a result, many scientists study the …
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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 …
groundwater storage resources. In this study, we proposed four ensemble soft computing …
GIS based hybrid computational approaches for flash flood susceptibility assessment
Flash floods are one of the most devastating natural hazards; they occur within a catchment
(region) where the response time of the drainage basin is short. Identification of probable …
(region) where the response time of the drainage basin is short. Identification of probable …
Fuzzy-metaheuristic ensembles for spatial assessment of forest fire susceptibility
Forests are important dynamic systems which are widely affected by fire worldwide. Due to
the complexity and non-linearity of the forest fire problem, employing hybrid evolutionary …
the complexity and non-linearity of the forest fire problem, employing hybrid evolutionary …