Prediction of concrete and FRC properties at high temperature using machine and deep learning: a review of recent advances and future perspectives
Concrete structures when exposed to elevated temperature significantly decline their
original properties. High temperatures substantially affect the concrete physical and …
original properties. High temperatures substantially affect the concrete physical and …
Machine learning into metaheuristics: A survey and taxonomy
EG Talbi - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
During the past few years, research in applying machine learning (ML) to design efficient,
effective, and robust metaheuristics has become increasingly popular. Many of those …
effective, and robust metaheuristics has become increasingly popular. Many of those …
Survey on genetic programming and machine learning techniques for heuristic design in job shop scheduling
Job shop scheduling (JSS) is a process of optimizing the use of limited resources to improve
the production efficiency. JSS has a wide range of applications, such as order picking in the …
the production efficiency. JSS has a wide range of applications, such as order picking in the …
Multiobjective evolution of the explainable fuzzy rough neural network with gene expression programming
B Cao, J Zhao, X Liu, J Arabas… - … on Fuzzy Systems, 2022 - ieeexplore.ieee.org
The fuzzy logic-based neural network usually forms fuzzy rules via multiplying the input
membership degrees, which lacks expressiveness and flexibility. In this article, a novel …
membership degrees, which lacks expressiveness and flexibility. In this article, a novel …
Multifactorial genetic programming for symbolic regression problems
Genetic programming (GP) is a powerful evolutionary algorithm that has been widely used
for solving many real-world optimization problems. However, traditional GP can only solve a …
for solving many real-world optimization problems. However, traditional GP can only solve a …
Prediction of UCS of fine-grained soil based on machine learning part 1: multivariable regression analysis, gaussian process regression, and gene expression …
The present research introduces the best architecture approach and model for predicting the
unconfined compressive strength (UCS) of cohesive virgin soil by comparing the …
unconfined compressive strength (UCS) of cohesive virgin soil by comparing the …
Applicability of genetic algorithms for stock market prediction: A systematic survey of the last decade
Stock market is one of the attractive domains for researchers as well as academicians. It
represents highly complex non-linear fluctuating market behaviours where traders …
represents highly complex non-linear fluctuating market behaviours where traders …
[HTML][HTML] Prediction of specific cutting energy consumption in eco-benign lubricating environment for biomedical industry applications: Exploring efficacy of GEP, ANN …
This study emphasizes the criticality of measuring specific cutting energy in machining
Hastelloy C276 for biomedical industry applications, offering valuable insights into …
Hastelloy C276 for biomedical industry applications, offering valuable insights into …
Prediction of soaked CBR of fine-grained soils using soft computing techniques
The present research determines the effect of training data sets, correlation, and
multicollinearity on the performance and overfitting of gene expression programming (GEP) …
multicollinearity on the performance and overfitting of gene expression programming (GEP) …
Intrusion detection model using gene expression programming to optimize parameters of convolutional neural network for energy internet
D Song, X Yuan, Q Li, J Zhang, M Sun, X Fu… - Applied Soft …, 2023 - Elsevier
The open, interconnected, and shared operational characteristics of the energy Internet
introduce more sophisticated cybersecurity attacks. How to accurately detect these cyber …
introduce more sophisticated cybersecurity attacks. How to accurately detect these cyber …