Novel volatility forecasting using deep learning–long short term memory recurrent neural networks
Y Liu - Expert Systems with Applications, 2019 - Elsevier
Abstracts The volatility is related to financial risk and its prediction accuracy is very important
in portfolio optimisation. A large body of literature to-date suggests Support Vector Machines …
in portfolio optimisation. A large body of literature to-date suggests Support Vector Machines …
Surrogate models based on machine learning methods for parameter estimation of left ventricular myocardium
L Cai, L Ren, Y Wang, W Xie… - Royal Society open …, 2021 - royalsocietypublishing.org
A long-standing problem at the frontier of biomechanical studies is to develop fast methods
capable of estimating material properties from clinical data. In this paper, we have studied …
capable of estimating material properties from clinical data. In this paper, we have studied …
An improved differential evolution algorithm with triangular mutation for global numerical optimization
AW Mohamed - Computers & Industrial Engineering, 2015 - Elsevier
This paper presents an Improved Differential Evolution (IDE) algorithm for solving global
numerical optimization problems over continuous space. The proposed algorithm introduces …
numerical optimization problems over continuous space. The proposed algorithm introduces …
A new approach to very short term wind speed prediction using k-nearest neighbor classification
Wind energy is an inexhaustible energy source and wind power production has been
growing rapidly in recent years. However, wind power has a non-schedulable nature due to …
growing rapidly in recent years. However, wind power has a non-schedulable nature due to …
A modified differential evolution algorithm for unconstrained optimization problems
D Zou, J Wu, L Gao, S Li - Neurocomputing, 2013 - Elsevier
A modified differential evolution algorithm (MDE) is proposed to solve unconstrained
optimization problems in this paper. Gauss distribution and uniform distribution have one …
optimization problems in this paper. Gauss distribution and uniform distribution have one …
ACCUGRAM: A novel approach based on classification to frequency band selection for rotating machinery fault diagnosis
Frequency band selection (FBS) in rotating machinery fault diagnosis aims to recognize
frequency band location including a fault transient out of a full band spectrum, and thus fault …
frequency band location including a fault transient out of a full band spectrum, and thus fault …
Hierarchical differential evolution algorithm combined with multi-cross operation
ZG Liu, XH Ji, Y Yang - Expert Systems with Applications, 2019 - Elsevier
In expert systems, complex optimization problems are always characterized by nonlinearity,
nonconvexity, multi-modality, discontinuity, and high dimensionality. Although classical …
nonconvexity, multi-modality, discontinuity, and high dimensionality. Although classical …
Optimization of mooring systems in the context of an integrated design methodology
B da Fonseca Monteiro, JS Baioco, CH Albrecht… - Marine Structures, 2021 - Elsevier
This work describes an enhanced mooring optimization procedure, oriented towards recent
floating production systems (FPS) for oil & gas exploitation in ultra-deep-water scenarios …
floating production systems (FPS) for oil & gas exploitation in ultra-deep-water scenarios …
An enhanced differential evolution algorithm based on multiple mutation strategies
W Xiang, X Meng, M An, Y Li… - Computational …, 2015 - Wiley Online Library
Differential evolution algorithm is a simple yet efficient metaheuristic for global optimization
over continuous spaces. However, there is a shortcoming of premature convergence in …
over continuous spaces. However, there is a shortcoming of premature convergence in …
A novel differential evolution algorithm using local abstract convex underestimate strategy for global optimization
Two main challenges in differential evolution (DE) are reducing the number of function
evaluations required to obtain optimal solutions and balancing the exploration and …
evaluations required to obtain optimal solutions and balancing the exploration and …