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: Recent Innovations in Artificial Intelligence and Smart Applications; Mostafa Al-Emran,Khaled Shaalan Book 2022 The Editor(s) (if applicab

[復制鏈接]
樓主: 母牛膽小鬼
51#
發(fā)表于 2025-3-30 10:37:53 | 只看該作者
52#
發(fā)表于 2025-3-30 15:27:11 | 只看該作者
Markov Switching Model for Driver Behavior Prediction: Use Cases on Smartphones,e driver actions, sensitivity, distraction, and response time. As the data collection is one of the major concerns for learning and validating different driving situations, we present a driver behavior switching model validated by a low-cost data collection solution using smartphones. The proposed m
53#
發(fā)表于 2025-3-30 19:55:47 | 只看該作者
Understanding the Impact of the Ontology of Semantic Web in Knowledge Representation: A Systematic ations of this relationship on knowledge representation and real-life solutions in various industries. PRISMA guidelines were used to select the papers and the authors focused on the most important 10 resources papers to investigate the research questions. It is concluded that semantic-web ontologie
54#
發(fā)表于 2025-3-30 22:27:21 | 只看該作者
55#
發(fā)表于 2025-3-31 03:28:56 | 只看該作者
Robotics and AI in Healthcare: A Systematic Review,timated to climb to 9 billion. By 2037, with a growth rate getting lower each year, we expect to have many older adults by then. With the increase in the price of caregivers and medication year by year, it is getting harder to maintain their longevity. The research papers reviewed will include the l
56#
發(fā)表于 2025-3-31 07:16:12 | 只看該作者
57#
發(fā)表于 2025-3-31 11:27:47 | 只看該作者
Book 2022art cities, telemedicine, and robotics. It sheds light on the recent AI innovations in classical machine learning, deep learning, Internet of Things (IoT), Blockchain, knowledge representation, knowledge management, big data, and natural language processing (NLP). The edited book covers empirical an
58#
發(fā)表于 2025-3-31 13:43:52 | 只看該作者
59#
發(fā)表于 2025-3-31 18:06:52 | 只看該作者
60#
發(fā)表于 2025-3-31 22:35:40 | 只看該作者
Exploring the Hidden Patterns in Maintenance Data to Predict Failures of Heavy Vehicles,acy, 68.09 and 41.24% Prediction of Issue Accuracy. So fleet managers should look into the historical data they have and let AI algorithms find the hidden patterns and employ them for better predictive maintenance schedules.
 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 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-11-1 15:54
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 返回頂部 返回列表
闸北区| 陈巴尔虎旗| 青海省| 英吉沙县| 铅山县| 同仁县| 民勤县| 开阳县| 清流县| 迁安市| 衡阳市| 凤山县| 务川| 大渡口区| 常熟市| 大安市| 镇安县| 鸡泽县| 昆山市| 广宗县| 灵宝市| 汉川市| 龙陵县| 油尖旺区| 进贤县| 桐城市| 安泽县| 民勤县| 营口市| 钟山县| 沛县| 和平区| 新竹市| 临高县| 沿河| 柳林县| 大庆市| 穆棱市| 呼伦贝尔市| 阿瓦提县| 元朗区|