找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Big Data; 11th CCF Conference, Enhong Chen,Yang Gao,Wanqi Yang Conference proceedings 2023 The Editor(s) (if applicable) and The Author(s),

[復(fù)制鏈接]
樓主: 討論小組
21#
發(fā)表于 2025-3-25 03:37:59 | 只看該作者
,A Study of?Electricity Theft Detection Method Based on?Anomaly Transformer,ployment of smart meters has led to the collection of massive amounts of electricity consumption data, which can help identify electricity theft. However, the challenge of detecting electricity theft is heightened by the category imbalance in the electricity consumption data collected. In this study
22#
發(fā)表于 2025-3-25 07:48:53 | 只看該作者
23#
發(fā)表于 2025-3-25 12:57:56 | 只看該作者
24#
發(fā)表于 2025-3-25 18:05:38 | 只看該作者
,A Transfer Learning Enhanced Decomposition-Based Hybrid Framework for?Forecasting Multiple Time-Ser domains such as energy consumption, network traffic, and solar radiation. The framework is compared with the conventional self-built MVMD-hybrid framework in terms of ARIMA model fitting time and normalized root mean square error (NRMSE) for forecasting accuracy. The results demonstrate that the pr
25#
發(fā)表于 2025-3-25 21:44:36 | 只看該作者
26#
發(fā)表于 2025-3-26 02:06:47 | 只看該作者
The Convolutional Neural Network Combing Feature-Aligned and Attention Pyramid for Fine-Grained Viseliability of high-level feature information are maintained. 2) Attention pyramid: pass the detailed information of low-level features in a bottom-up path to enhance the feature representation; 3) ROI feature refinement: dropblock and zoom-in are used for feature refinement to effectively eliminate
27#
發(fā)表于 2025-3-26 04:37:35 | 只看該作者
OCWYOLO: A Road Depression Detection Method,ed attention mechanisms to existing components without increasing the complexity of the model and achieving the goal of improving accuracy. In addition, we conducted a large number of experiments to verify the superiority of our model. We not only compare it on our road depression dataset but also c
28#
發(fā)表于 2025-3-26 09:26:18 | 只看該作者
29#
發(fā)表于 2025-3-26 12:46:00 | 只看該作者
30#
發(fā)表于 2025-3-26 18:41:14 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-9 14:03
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
连州市| 剑川县| 犍为县| 松潘县| 平凉市| 崇州市| 友谊县| 抚顺市| 内乡县| 循化| 阜南县| 定陶县| 木兰县| 乌拉特后旗| 屏东县| 盱眙县| 乾安县| 将乐县| 扶风县| 阳新县| 汾西县| 贵南县| 马鞍山市| 新干县| 巴里| 沈丘县| 宁波市| 西贡区| 七台河市| 长治县| 怀化市| 静乐县| 巴东县| 乌兰县| 屯留县| 乐东| 周口市| 龙州县| 马尔康县| 屯昌县| 扶余县|