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
泰宁县| 佛学| 北辰区| 雷山县| 城口县| 新龙县| 育儿| 中西区| 敖汉旗| 文安县| 楚雄市| 大港区| 改则县| 阳东县| 大余县| 乌什县| 墨竹工卡县| 台北县| 桃源县| 介休市| 镇平县| 日喀则市| 威海市| 略阳县| 汉沽区| 互助| 离岛区| 班戈县| 铜川市| 安徽省| 静海县| 柳河县| 兴海县| 兴仁县| 抚松县| 聂拉木县| 三江| 黑河市| 宝丰县| 炉霍县| 灵川县|