Multi-verse optimizer algorithm: a comprehensive survey of its results, variants, and applications
L Abualigah - Neural Computing and Applications, 2020 - Springer
This review paper presents a comprehensive and full review of the so-called optimization
algorithm, multi-verse optimizer algorithm (MOA), and reviews its main characteristics and …
algorithm, multi-verse optimizer algorithm (MOA), and reviews its main characteristics and …
Ant lion optimizer: theory, literature review, and application in multi-layer perceptron neural networks
This chapter proposes an efficient hybrid training technique (ALOMLP) based on the Ant
Lion Optimizer (ALO) to be utilized in dealing with Multi-Layer Perceptrons (MLPs) neural …
Lion Optimizer (ALO) to be utilized in dealing with Multi-Layer Perceptrons (MLPs) neural …
Optimization of random forest through the use of MVO, GWO and MFO in evaluating the stability of underground entry-type excavations
The stability evaluation of underground entry-type excavations is a prerequisite of the entry-
type mining method, which directly affects whether workers can be provided with a safe and …
type mining method, which directly affects whether workers can be provided with a safe and …
Optimizing connection weights in neural networks using the whale optimization algorithm
The learning process of artificial neural networks is considered as one of the most difficult
challenges in machine learning and has attracted many researchers recently. The main …
challenges in machine learning and has attracted many researchers recently. The main …
Evolutionary population dynamics and grasshopper optimization approaches for feature selection problems
Searching for the optimal subset of features is known as a challenging problem in feature
selection process. To deal with the difficulties involved in this problem, a robust and reliable …
selection process. To deal with the difficulties involved in this problem, a robust and reliable …
An efficient hybrid multilayer perceptron neural network with grasshopper optimization
This paper proposes a new hybrid stochastic training algorithm using the recently proposed
grasshopper optimization algorithm (GOA) for multilayer perceptrons (MLPs) neural …
grasshopper optimization algorithm (GOA) for multilayer perceptrons (MLPs) neural …
Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm
Monthly streamflow forecasting is required for short-and long-term water resources
management especially in extreme events such as flood and drought. Therefore, there is …
management especially in extreme events such as flood and drought. Therefore, there is …
Simultaneous feature selection and support vector machine optimization using the grasshopper optimization algorithm
Support vector machine (SVM) is considered to be one of the most powerful learning
algorithms and is used for a wide range of real-world applications. The efficiency of SVM …
algorithms and is used for a wide range of real-world applications. The efficiency of SVM …
Asynchronous accelerating multi-leader salp chains for feature selection
Feature selection is an imperative preprocessing step that can positively affect the
performance of machine learning techniques. Searching for the optimal feature subset …
performance of machine learning techniques. Searching for the optimal feature subset …
Multi-verse optimizer with rosenbrock and diffusion mechanisms for multilevel threshold image segmentation from COVID-19 chest X-ray images
Y Han, W Chen, AA Heidari, H Chen - Journal of Bionic Engineering, 2023 - Springer
Abstract Coronavirus Disease 2019 (COVID-19) is the most severe epidemic that is
prevalent all over the world. How quickly and accurately identifying COVID-19 is of great …
prevalent all over the world. How quickly and accurately identifying COVID-19 is of great …