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Found 15 papers, 4 papers with code
Towards replicated algorithms
The main deficiency of the algorithms running on digital computers nowadays is their inability to change themselves during the execution.
A comprehensive review of visualization methods for association rule mining: Taxonomy, Challenges, Open problems and Future ideas
Association rule mining is intended for searching for the relationships between attributes in transaction databases.
Time series numerical association rule mining variants in smart agriculture
However, little attention has been paid to the time series numerical association rule mining, which offers a new technique for extracting association rules from time series data.
A brief overview of swarm intelligence-based algorithms for numerical association rule mining
In line with this, the main mission of this chapter is to make a historical overview of swarm intelligence-based algorithms for Numerical Association Rule Mining, as well as to present the main features of these algorithms for the observed problem.
uARMSolver: A framework for Association Rule Mining
The paper presents a novel software framework for Association Rule Mining named uARMSolver.
Association rules over time
One of the more important issues faced by developers is exposed as how to create more explainable Machine Learning models.
Discovering associations in COVID-19 related research papers
A COVID-19 pandemic has already proven itself to be a global challenge.
Information cartography in association rule mining
The aim of this study is to develop a method for automatic creation of metro maps of information obtained by Association Rule Mining and, thus, spread its applicability to the other machine learning methods.
Population-based metaheuristics for Association Rule Text Mining
To solve the problem, the PSO-ARTM method was proposed, that consists of three steps: Text preprocessing, Association Rule Text Mining using population-based metaheuristics, and text postprocessing.
Modeling preference time in middle distance triathlons
Modeling preference time in triathlons means predicting the intermediate times of particular sports disciplines by a given overall finish time in a specific triathlon course for the athlete with the known personal best result.
Making up for the deficit in a marathon run
This paper proposes an automatic making up for the deficit by using a Differential Evolution algorithm.
A comprehensive review of firefly algorithms
This paper carries out a comprehensive review of this living and evolving discipline of Swarm Intelligence, in order to show that the firefly algorithm could be applied to every problem arising in practice.
A Brief Review of Nature-Inspired Algorithms for Optimization
Swarm intelligence and bio-inspired algorithms form a hot topic in the developments of new algorithms inspired by nature.
Comparing various regression methods on ensemble strategies in differential evolution
Differential evolution possesses a multitude of various strategies for generating new trial solutions.
Using the quaternion's representation of individuals in swarm intelligence and evolutionary computation
We believe that this representation could also be successfully applied to other swarm intelligence and evolutionary algorithms.
