Frequent itemset mining (FIM) is an essential task within data analysis since it is responsible
for extracting frequently occurring events, patterns, or items in data. Insights from such …

Association rule mining (ARM) is a commonly encountred data mining method. There are
many approaches to mining frequent rules and patterns from a database and one among …

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 …

This book is intended to provide a general and comprehensible overview of the field of
pattern mining with evolutionary algorithms. To do so, the book provides formal definitions …

Traditional association rule mining based on the support–confidence framework provides
the objective measure of the rules that are of interest to users. However, it does not reflect …

Global path planning is a fundamental problem of mobile robotics. The majority of global
path planning methods are designed to find a collision-free path from a start location to a …

In the past three decades nature-inspired and meta-heuristic algorithms have dominated the
literature in the broad areas of search and optimization. Harmony search algorithm (HSA) is …

Costly and time-consuming destructive methods of sampling, curing, and testing under
hydraulic jacks are often used to determine concrete properties. Computational intelligence …

Damage identi cation in Structural Health Monitoring (SHM) involves three main steps:
signal acquisition, signal processing, and feature extraction and interpretation. Recently, the …

Business process analysis is a key activity that aims at increasing the efficiency of business
operations. In recent years, several data mining based methods have been designed for …