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 …

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …

Abstract Association Rule Mining (ARM) is a significant task for discovering frequent patterns
in data mining. It has achieved great success in a plethora of applications such as market …

A demand for predictive models for on-line estimation of variables is increasing in industry.
As industrial processes are time-varying, on-line learning algorithms should be adaptive to …

In some situations, finding the rare association rule is of higher importance than the frequent
itemset. Unique rules represent rare cases, activities, or events in real-world applications. It …

Association rule mining (ARM) is one of the core techniques of data mining to discover
potentially valuable association relationships from mixed datasets. In the current research …

Predicting postoperative survival of lung cancer patients (LCPs) is an important problem of
medical decision‐making. However, the imbalanced distribution of patient survival in the …

关联规则挖掘是数据挖掘中的重要领域, 考虑到当前数据的大规模, 高维度,
模态多样及类型复杂等特性, 传统关联规则挖掘算法已无法适应大数据的需求 …

Fuzzy associative classification has not been widely analyzed in the literature, although
associative classifiers (ACs) have proved to be very effective in different real domain …

Finding the optimal path for a mobile robot in complex environments is a crucial part of
automation. In this application, we seek a path that avoids obstacles inside the scene. This …