Evolutionary machine learning: A survey
Evolutionary Computation (EC) approaches are inspired by nature and solve optimization
problems in a stochastic manner. They can offer a reliable and effective approach to address …
problems in a stochastic manner. They can offer a reliable and effective approach to address …
[HTML][HTML] A systematic literature review for the tourist trip design problem: Extensions, solution techniques and future research lines
The tourism sector represents an opportunity for economic growth in countries with tourism
potential. However, new trends in global tourism require efficiency in tourism supply chain …
potential. However, new trends in global tourism require efficiency in tourism supply chain …
Interactions among safety risks in metro deep foundation pit projects: An association rule mining-based modeling framework
L Fu, X Wang, H Zhao, M Li - Reliability Engineering & System Safety, 2022 - Elsevier
The deep foundation pit project (DFPP) in subway construction is characterized by a high
accident rate. Insufficient examination of the interactions among relevant safety risks often …
accident rate. Insufficient examination of the interactions among relevant safety risks often …
Minimum threshold determination method based on dataset characteristics in association rule mining
Association rule mining is a technique that is widely used in data mining. This technique is
used to identify interesting relationships between sets of items in a dataset and predict …
used to identify interesting relationships between sets of items in a dataset and predict …
[PDF][PDF] Machine learning based recommender system for e-commerce
Nowadays, e-commerce is becoming an essential part of business for many reasons,
including the simplicity, availability, richness and diversity of products and services, flexibility …
including the simplicity, availability, richness and diversity of products and services, flexibility …
A systematic assessment of numerical association rule mining methods
In data mining, the classical association rule mining techniques deal with binary attributes;
however, real-world data have a variety of attributes (numerical, categorical, Boolean). To …
however, real-world data have a variety of attributes (numerical, categorical, Boolean). To …
A data-knowledge-driven interval type-2 fuzzy neural network with interpretability and self-adaptive structure
Interval type-2 fuzzy neural networks (IT2FNNs) have gained sustainable attention and wide
applications because of their power of adaptive fuzzy modeling. Although the existing …
applications because of their power of adaptive fuzzy modeling. Although the existing …
Differential evolution and sine cosine algorithm based novel hybrid multi-objective approaches for numerical association rule mining
In association rules mining from data that have numeric-valued attributes, automatically
adjusting the attribute intervals at the time of the mining process without a preprocess is very …
adjusting the attribute intervals at the time of the mining process without a preprocess is very …
Anomaly detection based on CNN and regularization techniques against zero-day attacks in IoT networks
The fast expansion of the Internet of Things (IoT) in the technology and communication
industries necessitates a continuously updated cyber-security mechanism to keep protecting …
industries necessitates a continuously updated cyber-security mechanism to keep protecting …
Estimation of distribution algorithms in machine learning: a survey
The automatic induction of machine learning models capable of addressing supervised
learning, feature selection, clustering and reinforcement learning problems requires …
learning, feature selection, clustering and reinforcement learning problems requires …