An Efficient Hybrid Improved Feature Vector Manifold Clustering with Neighbour Search Optimization DOI Open Access

L. Dhanapriya,

S Preetha

International Journal of Computational and Experimental Science and Engineering, Journal Year: 2025, Volume and Issue: 11(2)

Published: April 29, 2025

In this paper, the IFMCNSO algorithm a novel hybrid Improved Feature Vector Manifold clustering with Neighbour search optimization —is presented. Many methods for linear or nonlinear manifold have been developed recently. While in many cases they proven to perform better than classic algorithms, majority of these approaches high complexity. order overcome problem, particularly high-dimensional datasets, work provides an effective method called IFMCNSO. By using strategy, domain which feature vector learning and Neighbor techniques can be used is greatly expanded, enabling parameterization real-world data sets. A good nearly optimal solution found acceptable amount time. comprehensive comparison proposed state-of-the-art namely DCNaN, RDMN, HFMST, HFMST-PSO, reveals that achieves higher Rand Index (RI) Adjusted (ARI) scores, underscoring its exceptional performance accuracy

Language: Английский

The distribution of bismuth in the process of reductive smelting of lead agglomerate DOI Open Access

Afrim Osmani,

Bastri Zeka,

Muharrem Zabeli

et al.

International Journal of Computational and Experimental Science and Engineering, Journal Year: 2025, Volume and Issue: 11(1)

Published: Feb. 19, 2025

The world production of bismuth is largely supported by the pyro metallurgical processes obtaining lead, where in this case concentrated gross lead around 94-98 %, from which elementary exploited debismuthization. Bismuth Trepça complex was based on its concentration lead-zinc composite ores, with about 0.17 % Bi. While concentrates varies and ranges 0.03-0.15 Well, addition to also all other by-products process Pb concentrated. As a result this, recovery rate enrichment low 65-78 distribution Bi products refinery as follows: 78 passes into refined bismuth; 6.62 Ca-Mg-Bi powder. Therefore, purpose work intensify debismuthization improving Bi, only use Ca reagent can reduce content up 0.04-0.005 while Mg 0.5 %. joint Mg, ratio 1:2, value 0.01 In cases deep debismuthiation required, then amount Sb molten intervened reduced values 0.004

Language: Английский

Citations

1
A Graph Neural Network Assisted Reverse Polymers Engineering to Design Low Bandgap Benzothiophene Polymers for Light Harvesting Applications DOI

Abrar U. Hassan,

Cihat Güleryüz, Islam H. El Azab

et al.

Materials Chemistry and Physics, Journal Year: 2025, Volume and Issue: unknown, P. 130747 - 130747

Published: March 1, 2025

Language: Английский

Citations

1
An Efficient Hybrid Improved Feature Vector Manifold Clustering with Neighbour Search Optimization DOI Open Access

L. Dhanapriya,

S Preetha

International Journal of Computational and Experimental Science and Engineering, Journal Year: 2025, Volume and Issue: 11(2)

Published: April 29, 2025

In this paper, the IFMCNSO algorithm a novel hybrid Improved Feature Vector Manifold clustering with Neighbour search optimization —is presented. Many methods for linear or nonlinear manifold have been developed recently. While in many cases they proven to perform better than classic algorithms, majority of these approaches high complexity. order overcome problem, particularly high-dimensional datasets, work provides an effective method called IFMCNSO. By using strategy, domain which feature vector learning and Neighbor techniques can be used is greatly expanded, enabling parameterization real-world data sets. A good nearly optimal solution found acceptable amount time. comprehensive comparison proposed state-of-the-art namely DCNaN, RDMN, HFMST, HFMST-PSO, reveals that achieves higher Rand Index (RI) Adjusted (ARI) scores, underscoring its exceptional performance accuracy

Language: Английский

Citations

0