找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: ;

[復(fù)制鏈接]
樓主: 無法仿效
21#
發(fā)表于 2025-3-25 06:20:16 | 只看該作者
https://doi.org/10.1007/978-1-349-12613-2d to set the CAV dedicated lane dynamically according to the traffic flow and the penetration of CAVs. The performance has been evaluated by using Plexe that is a platoon simulation platform. Simulation results show that the proposed method improves traffic flow 25.3% compared with the benchmark method.
22#
發(fā)表于 2025-3-25 11:07:19 | 只看該作者
https://doi.org/10.1007/978-3-030-88185-6ices were used to evaluate the forecasting accuracy. Results show the good accuracy of the method for forecasting traffic volumes in the case study. Based on the results obtained in this paper, it could provide reference for traffic volume forecasting for intelligent transportation systems.
23#
發(fā)表于 2025-3-25 14:33:56 | 只看該作者
An Experimental Method for CAV Dedicated Lane Setting Strategyd to set the CAV dedicated lane dynamically according to the traffic flow and the penetration of CAVs. The performance has been evaluated by using Plexe that is a platoon simulation platform. Simulation results show that the proposed method improves traffic flow 25.3% compared with the benchmark method.
24#
發(fā)表于 2025-3-25 18:56:34 | 只看該作者
25#
發(fā)表于 2025-3-25 23:10:29 | 只看該作者
https://doi.org/10.1007/978-3-662-46756-5lem of traffic velocity missing data recovery as the problem of sparse vectors recovery. Based on a large-scale dataset, we verify the effectiveness of the proposed algorithm. Experimental results show that our STC-CS solution can achieve better recovery performance even if the level of data missing is high.
26#
發(fā)表于 2025-3-26 03:49:30 | 只看該作者
27#
發(fā)表于 2025-3-26 08:21:26 | 只看該作者
28#
發(fā)表于 2025-3-26 11:47:33 | 只看該作者
A Visualization Analysis Approach for Logistics Customer Maintenanceation between continuous features and binary class labels to facilitate classification modeling. A data visualization analysis framework is developed using weight of evidence (WOE), where a semi-supervised approach is proposed to discretize the continuous features for WOE computation targeting on th
29#
發(fā)表于 2025-3-26 14:27:47 | 只看該作者
The Influence of Text Length on Text Classification Modelxt length leads to higher training costs of algorithms. It allows us to find that the common text classification algorithm models have shown significant?influence on the standard English dataset and Reddit mental illness dataset. The length of text or a string, especially for controlling the maximum
30#
發(fā)表于 2025-3-26 19:03:15 | 只看該作者
Roland W. Mitchell,Kirsten T. Edwardsrid. We first investigate the relationship between non-uniform error and query intersection area, and utilize the linear least square to fit the linear relation between them. Then we deduce the optimal partition granularity by minimizing non-uniform error and noise error. In the experiments, we use
 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| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-7 09:33
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
台北县| 武山县| 福贡县| 吐鲁番市| 牙克石市| 济宁市| 万州区| 谷城县| 宝山区| 吉水县| 基隆市| 革吉县| 贵溪市| 镶黄旗| 玛多县| 洞口县| 永昌县| 额济纳旗| 南丰县| 大姚县| 临朐县| 武城县| 宁津县| 合川市| 大足县| 嘉峪关市| 海城市| 胶州市| 长岭县| 太仓市| 锡林郭勒盟| 晋州市| 涞源县| 宝清县| 贵溪市| 通江县| 高青县| 拜城县| 镇沅| 牟定县| 汝南县|