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Titlebook: Global Trends in Information Systems and Software Applications; 4th International Co P. Venkata Krishna,M. Rajasekhara Babu,Ezendu Ariw Con

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41#
發(fā)表于 2025-3-28 18:07:37 | 只看該作者
https://doi.org/10.1007/978-3-642-87241-9Embedding (SLLE) is applied in the first phase to reduce dimension of the datasets and in next phase classification through K-NN and SVM is done. Experiments are carried on different high dimensional datasets and then we compared of different dimension reduction and classification methods.
42#
發(fā)表于 2025-3-28 20:42:52 | 只看該作者
https://doi.org/10.1007/978-3-642-57369-9, we study some basic set theoretic operations on the types of rough sets formed by the topological characterization. In addition to that, we provide a real life example for the depth classification of the concept.
43#
發(fā)表于 2025-3-29 01:42:50 | 只看該作者
Krebsrisiken im Kopf-Hals-Bereichtations like premature convergence which is resolved by Intelligent Dynamic Swarm (IDS) algorithm. IDS could produce the reduct set in a smaller time complexity but lacks the accuracy. In this paper we propose an improvised algorithm of IDS for feature selection.
44#
發(fā)表于 2025-3-29 03:57:39 | 只看該作者
45#
發(fā)表于 2025-3-29 08:21:31 | 只看該作者
46#
發(fā)表于 2025-3-29 13:57:00 | 只看該作者
47#
發(fā)表于 2025-3-29 17:36:58 | 只看該作者
Topological Characterization of Rough Set on Two Universal Sets and Knowledge Representation,, we study some basic set theoretic operations on the types of rough sets formed by the topological characterization. In addition to that, we provide a real life example for the depth classification of the concept.
48#
發(fā)表于 2025-3-29 23:17:32 | 只看該作者
Improved Intelligent Dynamic Swarm PSO Algorithm and Rough Set for Feature Selection,tations like premature convergence which is resolved by Intelligent Dynamic Swarm (IDS) algorithm. IDS could produce the reduct set in a smaller time complexity but lacks the accuracy. In this paper we propose an improvised algorithm of IDS for feature selection.
49#
發(fā)表于 2025-3-30 02:44:04 | 只看該作者
Estimating Database Size and Its Development Effort at Conceptual Design Stage, on the database volume. In this paper, a set of metrics have been proposed and validated for estimating database size using ER and Enhanced ER diagram artifacts. The effort of database development based on the proposed size metrics have been validated using COCOMO model.
50#
發(fā)表于 2025-3-30 07:37:03 | 只看該作者
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