Journal of Automation and Intelligence最新文献_第7页

Practical bipartite consensus for multi-agent systems: A barrier function-based adaptive sliding-mode control approach 多智能体系统的实用二部共识:一种基于障碍函数的自适应滑模控制方法

Journal of Automation and Intelligence Pub Date : 2023-02-01 DOI: 10.1016/j.jai.2023.100019

Boda Ning , Qing-Long Han , Xiaohua Ge

引用次数: 1

Model predictive control for water management and energy security in arid/semiarid regions 干旱/半干旱区水资源管理与能源安全的模型预测控制

Journal of Automation and Intelligence Pub Date : 2022-12-01 DOI: 10.1016/j.jai.2022.100001

D.M. Bajany , L. Zhang , X. Xia

{"title":"Model predictive control for water management and energy security in arid/semiarid regions","authors":"D.M. Bajany , L. Zhang , X. Xia","doi":"10.1016/j.jai.2022.100001","DOIUrl":"10.1016/j.jai.2022.100001","url":null,"abstract":"<div><p>This paper aims to develop a realistic operational optimal management of a water supply system in an arid/semiarid region under climate change conditions. The developed model considers the dynamic variation of water demand, rainfall, weather, and seasonal change in electricity price. It is mathematically developed as a multi-constraint non-linear programming model based on model predictive control principles. The model optimises the quantities of water supplied by each source every month and improves the energy efficiency in a water supply system with multiple types of sources. The effectiveness of the developed MPC model is verified by applying it to a case study and comparing the results with those obtained with an open loop model. Results showed that using the MPC model leads to a 4.16% increase in the water supply cost compared to the open loop model. However, when considering uncertainties in predicting water demands, aquifer recharges, rainfall, and evaporation rate, the MPC model was better than the open loop model. Indeed, the MPC model could meet the water demand at any period due to its predictability of variations, which was not the case with the open loop model. Moreover, a sensitivity analysis is conducted to verify the capacity of the developed model to deal with some phenomena due to climatic changes, such as in rainfall.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"1 1","pages":"Article 100001"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855422000016/pdfft?md5=a33cb644d0b9ca4435716f0923204f10&pid=1-s2.0-S2949855422000016-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77150910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Deep learning and transfer learning for device-free human activity recognition: A survey 无设备人类活动识别的深度学习和迁移学习:综述

Journal of Automation and Intelligence Pub Date : 2022-12-01 DOI: 10.1016/j.jai.2022.100007

Jianfei Yang, Yuecong Xu, Haozhi Cao, Han Zou, Lihua Xie

{"title":"Deep learning and transfer learning for device-free human activity recognition: A survey","authors":"Jianfei Yang, Yuecong Xu, Haozhi Cao, Han Zou, Lihua Xie","doi":"10.1016/j.jai.2022.100007","DOIUrl":"10.1016/j.jai.2022.100007","url":null,"abstract":"<div><p>Device-free activity recognition plays a crucial role in smart building, security, and human–computer interaction, which shows its strength in its convenience and cost-efficiency. Traditional machine learning has made significant progress by heuristic hand-crafted features and statistical models, but it suffers from the limitation of manual feature design. Deep learning overcomes such issues by automatic high-level feature extraction, but its performance degrades due to the requirement of massive annotated data and cross-site issues. To deal with these problems, transfer learning helps to transfer knowledge from existing datasets while dealing with the negative effect of background dynamics. This paper surveys the recent progress of deep learning and transfer learning for device-free activity recognition. We begin with the motivation of deep learning and transfer learning, and then introduce the major sensor modalities. Then the deep and transfer learning techniques for device-free human activity recognition are introduced. Eventually, insights on existing works and grand challenges are summarized and presented to promote future research.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"1 1","pages":"Article 100007"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855422000077/pdfft?md5=9763a994531a1204c951d25f4a816f37&pid=1-s2.0-S2949855422000077-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83128614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Controllability robustness of complex networks 复杂网络的可控性鲁棒性

Journal of Automation and Intelligence Pub Date : 2022-12-01 DOI: 10.1016/j.jai.2022.100004

Guanrong Chen

引用次数: 6

Lyapunov-based fixed-time stabilization control of quantum systems 基于lyapunov的量子系统定时稳定控制

Journal of Automation and Intelligence Pub Date : 2022-12-01 DOI: 10.1016/j.jai.2022.100005

Xiaolei Li , Changyun Wen , Jiange Wang

引用次数: 3

A review on COLREGs-compliant navigation of autonomous surface vehicles: From traditional to learning-based approaches 基于colregs的自主地面车辆导航研究综述:从传统方法到基于学习的方法

Journal of Automation and Intelligence Pub Date : 2022-12-01 DOI: 10.1016/j.jai.2022.100003

Liang Hu , Huosheng Hu , Wasif Naeem , Zidong Wang

引用次数: 4

A survey on computationally efficient neural architecture search 计算效率高的神经结构搜索研究综述

Journal of Automation and Intelligence Pub Date : 2022-12-01 DOI: 10.1016/j.jai.2022.100002

Shiqing Liu , Haoyu Zhang , Yaochu Jin

{"title":"A survey on computationally efficient neural architecture search","authors":"Shiqing Liu , Haoyu Zhang , Yaochu Jin","doi":"10.1016/j.jai.2022.100002","DOIUrl":"10.1016/j.jai.2022.100002","url":null,"abstract":"<div><p>Neural architecture search (NAS) has become increasingly popular in the deep learning community recently, mainly because it can provide an opportunity to allow interested users without rich expertise to benefit from the success of deep neural networks (DNNs). However, NAS is still laborious and time-consuming because a large number of performance estimations are required during the search process of NAS, and training DNNs is computationally intensive. To solve this major limitation of NAS, improving the computational efficiency is essential in the design of NAS. However, a systematic overview of computationally efficient NAS (CE-NAS) methods still lacks. To fill this gap, we provide a comprehensive survey of the state-of-the-art on CE-NAS by categorizing the existing work into proxy-based and surrogate-assisted NAS methods, together with a thorough discussion of their design principles and a quantitative comparison of their performances and computational complexities. The remaining challenges and open research questions are also discussed, and promising research topics in this emerging field are suggested.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"1 1","pages":"Article 100002"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855422000028/pdfft?md5=b41972f5ae9308e54b34304ae70e1d75&pid=1-s2.0-S2949855422000028-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88935241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

On the new era of automation and intelligence 关于自动化和智能的新时代

Journal of Automation and Intelligence Pub Date : 2022-12-01 DOI: 10.1016/j.jai.2022.100009

Yongduan Song Ph.D., PE (Fellow IEEE, AAIA, CAA Editor-in-Chief Journal of Automation and Intelligence https://www.keaipublishing.com/en/journals/journal-of-automation-and-intelligence/)

引用次数: 0