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Titlebook: Computational Intelligence in Data Mining - Volume 2; Proceedings of the I Lakhmi C. Jain,Himansu Sekhar Behera,Durga Prasad Conference pr

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31#
發(fā)表于 2025-3-26 21:45:11 | 只看該作者
Strategic Planning for Urban Transportationveness of the proposed method for multi-view human activity recognition in order to conquer the viewpoint dependency. The main contribution of this paper is the application of Random Forests classifier to the problem of multi-view activity recognition in surveillance videos, based only on human motion.
32#
發(fā)表于 2025-3-27 03:25:06 | 只看該作者
Encouraging Family Participation results like valid/invalid data, error rate etc. Fusing two (or more) classifiers may be done by multiplying the hyper-distributions of the parameters. The main advantage of this fusion approach is that it requires less time to classify the data and is easily extensible for large dataset.
33#
發(fā)表于 2025-3-27 08:29:48 | 只看該作者
Multi-objective Design Optimization of Three-Phase Induction Motor Using NSGA-II Algorithm,ing (SA) and Genetic Algorithm (GA) is used for comparing the Pareto solutions. Performance comparison of techniques is done by performing different numerical experiments. The result shows that NSGA-II outperforms other three for the considered test cases.
34#
發(fā)表于 2025-3-27 09:27:32 | 只看該作者
35#
發(fā)表于 2025-3-27 15:04:45 | 只看該作者
An Integrated Approach to Improve the Text Categorization Using Semantic Measures,it is integrated with TRI improves the clustering accuracy which leads to incremental text categorization. Our experimental analysis on different data sets proved that the proposed SETC performing better.
36#
發(fā)表于 2025-3-27 20:39:09 | 只看該作者
Design of Biorthogonal Wavelets Based on Parameterized Filter for the Analysis of X-ray Images,ing the edges with better quality. The various performance metrics like Ratio of Edge pixels to size of image (REPS), peak signal to noise ratio (PSNR) and computation time are compared for various biorthogonal wavelets.
37#
發(fā)表于 2025-3-28 00:20:56 | 只看該作者
38#
發(fā)表于 2025-3-28 02:49:00 | 只看該作者
Analyzing Data Through Data Fusion Using Classification Techniques, results like valid/invalid data, error rate etc. Fusing two (or more) classifiers may be done by multiplying the hyper-distributions of the parameters. The main advantage of this fusion approach is that it requires less time to classify the data and is easily extensible for large dataset.
39#
發(fā)表于 2025-3-28 09:39:10 | 只看該作者
Conference proceedings 2015egration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
40#
發(fā)表于 2025-3-28 13:21:00 | 只看該作者
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