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Titlebook: Artificial Intelligence and Evolutionary Computations in Engineering Systems; Proceedings of ICAIE Subhransu Sekhar Dash,Paruchuri Chandra

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21#
發(fā)表于 2025-3-25 06:01:36 | 只看該作者
https://doi.org/10.1007/978-3-031-60920-6ue and as a PV series-connected system that uses ANFIS-MPPT technique. The proposed PV systems were tested under uniform and partial shading weather conditions. The results show that MPPT could be tracked accurately with the ANFIS-DMPPT for both cases of uniform irradiance and partial shaded irradiance conditions.
22#
發(fā)表于 2025-3-25 08:34:13 | 只看該作者
23#
發(fā)表于 2025-3-25 12:37:26 | 只看該作者
24#
發(fā)表于 2025-3-25 18:39:48 | 只看該作者
Vladimir Matveev,Violetta Shaninality to include preferences for different aspects of items using weighted trees and user ratings as well. This paper addresses the challenge of using recursive weighted tree similarity in hybrid recommendation system. We established theoretical and experimental evaluation among a few example trees using our proposed recommendation systems.
25#
發(fā)表于 2025-3-25 23:29:37 | 只看該作者
26#
發(fā)表于 2025-3-26 03:56:48 | 只看該作者
Impact of Poor Data Quality in Remotely Sensed Data,lts suggest .-nearest neighbour as a superior approach to handling missing data, especially when regression imputation is used. Most classifiers achieve lower accuracy when listwise deletion is used. Nonetheless, RF is much less robust to missing data compared to other classifiers such as ANN and SVM.
27#
發(fā)表于 2025-3-26 06:36:43 | 只看該作者
Self Regulating Power Saving System for Home Automation,om temperature with LM-35 sensor. By using ACS712 Current Sense Module, we control the current flow. And also we can control the appliances through mobile when the user is not at home. All the data can be stored in cloud for future reference.
28#
發(fā)表于 2025-3-26 08:35:50 | 只看該作者
Recommendation System Based on Generalized-Weighted Tree Similarity Algorithm,lity to include preferences for different aspects of items using weighted trees and user ratings as well. This paper addresses the challenge of using recursive weighted tree similarity in hybrid recommendation system. We established theoretical and experimental evaluation among a few example trees using our proposed recommendation systems.
29#
發(fā)表于 2025-3-26 12:53:23 | 只看該作者
30#
發(fā)表于 2025-3-26 20:39:52 | 只看該作者
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