The accuracies rates of the neural networks mainly depend on the selection of the correct
data centers. The K-means algorithm is a widely used clustering algorithm in various …

The tunicate swarm algorithm (TSA) is a newly proposed population-based swarm optimizer
for solving global optimization problems. TSA uses best solution in the population in order …

In neural networks, training a network with a large datasets put a heavy load to computation
time and does not guarantee networks accuracy. As dataset may contains outlier or missing …

Image segmentation which is generally one of the first step of algorithms for image
processing is an important process that renders the data more meaning full for users. It is a …

In this paper we propose a new incremental Gene Expression Programming (GEP)
ensemble classifier. Our base classifiers are induced from a chunk of data instances using …

The paper proposes an incremental Gene Expression Programming classifier. Its main
features include using two‐level ensemble consisting of base classifiers in form of genes …

The paper addresses dynamic combinatorial clustering. First, a systematic literature survey
on dynamic/online clustering is presented (problems, methods, applications). Second …

The paper proposes a new ensemble classifier using Gene Expression Programming as the
induction engine. The approach aims at predicting unknown class labels for datasets with …

In the paper, we propose two gene expression programming (GEP)‐based ensemble
classifiers with different drift detection mechanisms. In the related work section, we briefly …