In this study, ground observation data were selected from January 2016 to 2020. First, six machine learning methods used predict visibility. We verified the accuracy of method with and without principal components analysis (PCA) by combining actual examples European Centre for Medium-Range Weather Forecast (ECMWF) National Centers Environmental Prediction (NECP) data. The results show that PCA ...

Biclustering is an unsupervised machine learning technique that simultaneously clusters rows and columns in a data matrix. has emerged as important approach plays essential role various applications such bioinformatics, text mining, pattern recognition. However, finding significant biclusters NP-hard problem can be formulated optimization problem. Therefore, different metaheuristics have been a...

We introduce a new framework for solving an important class of computational problems involving finite permutation groups, which includes calculating set stabilisers, intersections subgroups, and isomorphisms combinatorial structures. Our techniques are inspired by generalise ‘partition backtrack’, is the current state-of-the-art algorithm introduced Jeffrey Leon in 1991. But, instead ordered p...