The multi-level thresholding is a popular method for image segmentation. However, the
method is computationally expensive and suffers from premature convergence when level …

In this paper, we propose a cellular edge detection (CED) algorithm which utilizes cellular
automata (CA) and cellular learning automata (CLA). The CED algorithm is an adaptive …

Many real-world optimization problems are dynamic, in which the environment, ie the
objective function and restrictions, can change over time. In this case, the optimal solution (s) …

The spread of the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) which
causes CoronaVirus Disease 2019 (COVID-19) has challenged many countries. To curb the …

One of the effective techniques for improving the rate of convergence in the particle swarm
optimisation (PSO) is modifying the inertia weight parameter. This parameter can specify the …

Computational Intelligence Re-meets Medical Image Processing Analysis of Machine
Learning Algorithms for Diagnosis of Diffuse Lung Diseases Background In the last …

Many real-world problems are dynamic optimization problems. In this case, the optima in the
environment change dynamically. Therefore, traditional optimization algorithms disable to …

Interaction between users in online social networks plays a key role in social network
analysis. One on important types of social group is full connected relation between some …

In recent years, social network services provide a suitable platform for analyzing the activity
of users in social networks. In online social networks, interaction between users plays a key …

Many real-world phenomena can be modelled as dynamic optimization problems. In such
cases, the environment problem changes dynamically and therefore, conventional methods …