Metaheuristic algorithms on feature selection: A survey of one decade of research (2009-2019)
Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …
dimension of the feature set while maintaining the accuracy of the performance is the main …
Dragonfly algorithm: a comprehensive review and applications
Dragonfly algorithm (DA) is a novel swarm intelligence meta-heuristic optimization algorithm
inspired by the dynamic and static swarming behaviors of artificial dragonflies in nature. It …
inspired by the dynamic and static swarming behaviors of artificial dragonflies in nature. It …
Dragonfly algorithm: a comprehensive survey of its results, variants, and applications
This paper thoroughly introduces a comprehensive review of the so-called Dragonfly
algorithm (DA) and highlights its main characteristics. DA is considered one of the promising …
algorithm (DA) and highlights its main characteristics. DA is considered one of the promising …
Comparison of dragonfly algorithm and Harris hawks optimization evolutionary data mining techniques for the assessment of bearing capacity of footings over two …
H Moayedi, MM Abdullahi, H Nguyen… - Engineering with …, 2021 - Springer
By assist of novel evolutionary science, the classification accuracy of neural computing is
improved in analyzing the bearing capacity of footings over two-layer foundation soils. To …
improved in analyzing the bearing capacity of footings over two-layer foundation soils. To …
[HTML][HTML] Recent advancements using machine learning & deep learning approaches for diabetes detection: a systematic review
Abstract Nowadays, Diabetes Mellitus is one of the significant health challenges that affects
many people across the world. Early detection of Diabetes Mellitus will help in preventing …
many people across the world. Early detection of Diabetes Mellitus will help in preventing …
Novel nature-inspired hybrids of neural computing for estimating soil shear strength
H Moayedi, D Tien Bui, A Dounis, L Kok Foong… - Applied Sciences, 2019 - mdpi.com
This paper focuses on the prediction of soil shear strength (SSS), which is one of the most
fundamental parameters in geotechnical engineering. Consisting of 12 influential factors …
fundamental parameters in geotechnical engineering. Consisting of 12 influential factors …
COOT optimization algorithm on training artificial neural networks
A Özden, İ İşeri - Knowledge and Information Systems, 2023 - Springer
In recent years, significant advancements have been made in artificial neural network
models and they have been applied to a variety of real-world problems. However, one of the …
models and they have been applied to a variety of real-world problems. However, one of the …
Prediction of diabetes risk based on machine learning techniques
M Rout, A Kaur - 2020 International Conference on Intelligent …, 2020 - ieeexplore.ieee.org
The explosive population growth and health maintenance is an extremely crucial matter
worldwide. Many lethal diseases are causing threats at a high peak in recent years …
worldwide. Many lethal diseases are causing threats at a high peak in recent years …
A new hybrid quantitative structure property relationships‐support vector regression (QSPR‐SVR) approach for predicting the solubility of drug compounds in …
The purpose of this work was to compare the performance of 7 meta‐heuristics algorithms
namely: Dragonfly (DA), Ant Lion (ALO), Grey Wolf (GWO), Artificial Bee Colony (ABC) …
namely: Dragonfly (DA), Ant Lion (ALO), Grey Wolf (GWO), Artificial Bee Colony (ABC) …
Two novel neural-evolutionary predictive techniques of dragonfly algorithm (DA) and biogeography-based optimization (BBO) for landslide susceptibility analysis
H Moayedi, A Osouli, DT Bui, L Kok Foong… - … , Natural Hazards and …, 2019 - Taylor & Francis
Due to the wide application of evolutionary science in different engineering problems, the
main aim of this paper is to present two novel optimizations of multi-layer perceptron (MLP) …
main aim of this paper is to present two novel optimizations of multi-layer perceptron (MLP) …