Towards augmented kernel extreme learning models for bankruptcy prediction: algorithmic behavior and comprehensive analysis
Y Zhang, R Liu, AA Heidari, X Wang, Y Chen, M Wang… - Neurocomputing, 2021 - Elsevier
Bankruptcy prediction is a crucial application in financial fields to aid in accurate decision
making for business enterprises. Many models may stagnate to low-accuracy results due to …
making for business enterprises. Many models may stagnate to low-accuracy results due to …
Gaussian mutational chaotic fruit fly-built optimization and feature selection
To cope with the potential shortcomings of classical fruit fly optimization algorithm (FOA), a
new version of FOA with Gaussian mutation operator and the chaotic local search strategy …
new version of FOA with Gaussian mutation operator and the chaotic local search strategy …
Optimizing deep transfer networks with fruit fly optimization for accurate diagnosis of diabetic retinopathy
It is crucial to develop a smart analytics system capable of accurately diagnosing diabetic
retinopathy. This research uses a new deep transfer network framework to diagnose …
retinopathy. This research uses a new deep transfer network framework to diagnose …
Efficient multi-population outpost fruit fly-driven optimizers: Framework and advances in support vector machines
The original fruit fly algorithm (FOA) in simple structure is easy to understand, but it has a
slow convergence rate and tends to be trapped in the local optimal solutions. In order to …
slow convergence rate and tends to be trapped in the local optimal solutions. In order to …
Multi-population following behavior-driven fruit fly optimization: A Markov chain convergence proof and comprehensive analysis
X Wang, H Chen, AA Heidari, X Zhang, J Xu… - Knowledge-Based …, 2020 - Elsevier
Fruit fly optimization algorithm (FOA) is a well-known optimization algorithm with a well-
designed structure and superiority of fewer parameters, more effortless adjustment, and …
designed structure and superiority of fewer parameters, more effortless adjustment, and …
A new effective machine learning framework for sepsis diagnosis
There is a lack of early specific diagnosis and effective evaluation of sepsis, and the clinical
treatment is not timely. As a result, the mortality is high, which seriously threatens the health …
treatment is not timely. As a result, the mortality is high, which seriously threatens the health …
Robust predictive control of wheel slip in antilock braking systems based on radial basis function neural network
H Mirzaeinejad - Applied soft computing, 2018 - Elsevier
Abstract Anti-Lock Braking System (ABS) is a well-known technology for vehicle safety
enhancement during hard braking. The wheel slip control has been a challenging problem …
enhancement during hard braking. The wheel slip control has been a challenging problem …
Instantaneous vehicle fuel consumption estimation using smartphones and recurrent neural networks
The high level of air pollution in urban areas, caused in no small extent by road transport,
requires the implementation of continuous and accurate monitoring techniques if emissions …
requires the implementation of continuous and accurate monitoring techniques if emissions …
Multiobjective Optimization of an Off‐Road Vehicle Suspension Parameter through a Genetic Algorithm Based on the Particle Swarm Optimization
D Peng, G Tan, K Fang, L Chen… - Mathematical …, 2021 - Wiley Online Library
Ride comfort and handling performances are known conflicts for off‐road vehicles. Recent
publications focus on passenger vehicles on class B and class C roads, while, for off‐road …
publications focus on passenger vehicles on class B and class C roads, while, for off‐road …
Actuator and sensor fault estimation based on a proportional multiple‐integral sliding mode observer for linear parameter varying systems with inexact scheduling …
S Gómez‐Peñate, FR López‐Estrada… - … Journal of Robust …, 2021 - Wiley Online Library
This article proposes an approach for the estimation of states, actuator, and sensor faults in
nonlinear systems represented by a polytopic linear parameter varying (LPV) system with …
nonlinear systems represented by a polytopic linear parameter varying (LPV) system with …