Partitional data clustering with K-means algorithm is the dividing of objects into smaller and disjoint groups that has the most similarity with objects in a group and most dissimilarity from …
B Saemi, AAR Hosseinabadi, M Kardgar… - … workshop soft computing …, 2016 - Springer
Clustering algorithms are developed as a powerful tool to analyze the massive amount of data which are produced by modern applications. The main goal of these algorithms is to …
G Liang, X Zhao, J Zhao, F Zhou - Remote Sensing, 2021 - mdpi.com
The discrimination of water–land waveforms is a critical step in the processing of airborne topobathy LiDAR data. Waveform features, such as the amplitudes of the infrared (IR) laser …
The performance of data clustering algorithms is mainly dependent on their ability to balance between the exploration and exploitation of the search process. Although some …
Z Aliniya, MR Keyvanpour - Neural Computing and Applications, 2019 - Springer
Optimization is increasingly important due to its application in the real-world problems. The imperialist competitive algorithm (ICA) is a successful optimization algorithm in many …
Z Aliniya, MR Keyvanpour - Journal of Experimental & Theoretical …, 2018 - Taylor & Francis
In this paper, an improved imperialist competitive algorithm called I-ICA is proposed for solving constrained optimisation problems. In I-ICA, the use of differential evolution …
M Houtinezhad, HR Ghaffary - Int. Arab J. Inf. Technol., 2021 - researchgate.net
The goal of optimizing the best acceptable answer is according to the limitations and needs of the problem. For a problem, there are several different answers that are defined to …