检索结果-南通市图书馆

intelligent Automation & Soft Computing 2023年第4期36卷 745-760页

作者： A.Jegatheesh M.Germin Nisha N.Kopperundevi department of ECE Arunachala College of Engineering for WomenVellichanthai629203Tamil NaduIndia department of EEE St Xaviers Catholic College of EngineeringNagercoil290036Tamil NaduIndia department of ECE Swarnandhra College of Engineering and TechnologyNarasapur534280Andhra PradeshIndia

Interacting The highest storage capacity of a circular tank makes it pop-ular in process *** of the varying surface area of the cross-sec-tions of the tank,this two-tank level system has nonlinear *** theﬂow rate of liquid is one of the most difﬁcult challenges in the production *** proposed effort is critical in preventing time delays and errors by managing theﬂuid *** scholars have explored and explored ways to reduce the problem of nonlinearity,but their techniques have not yielded better *** types of controllers with various techniques are implemented by the proposed *** Mode Controller(SMC)with Fractional Order PID Controller based on intelligent Adaptive Neuro-Fuzzy Infer-ence System(ANFIS)is a novel technique for liquid level regulation in an inter-connected spherical tank system to avoid interferences and achieve better performance in comparison of rise time,settling time,and overshoot *** the simulated results acquired by the controller yields the efﬁciency of the proposed *** simulated results were produced using MATLAB 2018 and the FOMCON ***,the performance of the conventional controller(FOPID,PID-SMC)and proposed ANFIS based SMC-FOPID control-lers are compared and analyzed the performance indices.

关键词： Nonlinear system performance indices ANFIS based sliding mode controller with fractional order PID PID controller

Minimum Airflow Rate Algorithm for VAV Systems

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Minimum Airflow Rate Algorithm for VAV Systems

Research on Time Synchronization Technology of Heterogeneous Network in Distribution Network Based on 5G

第40届中国控制会议

作者： Tian Xing Qianchuan Zhao Jili Zhang Center for intelligent and Networked Systems Department of AutomationTsinghua University Faculty of Infrastructure Engineering Dalian University of Technology

Variable Air Volume（VAV） system is a widely used scheme for Heating Ventilating and Air-Conditioning（HVAC） systems in large *** based methods are still widely used in VAV systems because of the *** control methods have disadvantages of poor anti-disturbance ability,slow response speed,and high energy *** control methods for VAV systems have been studied and implemented in recent *** the control effect of predictive control method is better than PID,zone airflow rates remain relatively large,which increases the cooling energy consumption of the *** this paper,focusing more on energy efficiency,we proposed a Minimum Airflow Rate（MAR） algorithm for VAV *** MAR follows the framework of predictive control and further optimizes the airflow rates of VAV zones while meeting indoor climate *** with predictor,conventional predictive control,and MAR algorithm are tested in a threezone VAV system by *** show that,compared with conventional methods,the MAR algorithm maintains the advantages of predictive control algorithms and further reduces the cooling energy consumption in the control process.

关键词： MAR algorithm predictive control energy-saving optimization VAV system

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Research on Time Synchronization Technology of Heterogeneous...

Additive manufacturing of biodegradable magnesium-based materials:Design strategies,properties,and biomedical applications

第三十九届中国控制会议

作者： Xiong Wen Shao Shuai Lao Yongzhao Cui Shijie Xu Quan Guangzhou Power Supply Bureau Co. Ltd. State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences Institutes for Robotics and intelligent manufacturing Chinese Academy of Sciences Electric Power Research Institute CSG.

At present, high-precision time synchronization technology plays an important role in many industries. In smart grid, wide area measurement system（WAMS）, event sequence recording（SOE）, and fault recording all need unified reference time for synchronization, which improves the application level of power grid accident analysis and stability control, and improves the power supply network efficiency. It can improve grid reliability and efficiency. This paper designs the time synchronization technology of heterogeneous network in distribution network with the help of 5G URLLC network technology. It can switch clock types according to different synchronization regions, and can coordinate time synchronization between heterogeneous networks, without additional protocol overhead and equipment development cost, and has good network compatibility.

关键词： Distribution network communication time synchronization Heterogeneous network 5G

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Journal of Magnesium and Alloys 2023年第3期11卷 801-839页

作者： Farzad Badkoobeh Hossein Mostaan Mahdi Rafiei Hamid Reza Bakhsheshi-Rad Seeram Rama Krishna Xiongbiao Chen School of Metallurgy and Materials Engineering College of EngineeringUniversity of TehranTehranIran Faculty of Engineering Department of Materials and Metallurgical EngineeringArak UniversityArakIran Advanced Materials Research Center Department of Materials EngineeringNajafabad BranchIslamic Azad UniversityNajafabadIran department of Mechanical Engineering National University of Singapore9 Engineering Drive 1Singapore 117576Singapore department of Mechanical Engineering College of EngineeringUniversity of SaskatchewanSaskatoonSK S7N 5A9Canada

Magnesium(Mg)-based materials are a new generation of alloys with the exclusive ability to be biodegradable within the human/animal *** addition to biodegradability,their inherent biocompatibility and similar-to-bone density make Mg-based alloys good candidates for fabricating surgical bioimplants for use in orthopedic and traumatology *** this end,nowadays additive manufacturing(AM)along with three-dimensional(3D)printing represents a promising manufacturing technique as it allows for the integration of bioimplant design and manufacturing processes specific to given ***,this technique also faces many new challenges associated with the properties of Mg-based alloys,including high chemical reactivity,potential for combustion,and low vaporization *** this review article,various AM processes to fabricate biomedical implants from Mg-based alloys,along with their metallic microstructure,mechanical properties,biodegradability,biocompatibility,and antibacterial properties,as well as various post-AM treatments were critically ***,the challenges and issues involved in AM processes from the perspectives of bioimplant design,properties,and applications were identified;the possibilities and potential scope of the Mg-based scaffolds/implants are discussed and highlighted.

关键词： Magnesium alloy Additive manufacturing 3D Printing Bone tissue engineering Scaffold Mechanical and biological properties

Modeling of Optimal Deep Learning Based Flood Forecasting Model Using Twitter Data

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

intelligent Automation & Soft Computing 2023年第2期35卷 1455-1470页

作者： G.Indra N.Duraipandian department of Computer Science and Engineering RMK College of Engineering and TechnologyChennai601206India department of Computer Science and Engineering Saveetha Engineering CollegeChennai602106India

Aﬂood is a signiﬁcant damaging natural calamity that causes loss of life and *** work on the construction ofﬂood prediction models intended to reduce risks,suggest policies,reduce mortality,and limit property damage caused byﬂ*** massive amount of data generated by social media platforms such as Twitter opens the door toﬂood *** of the real-time nature of Twitter data,some government agencies and authorities have used it to track natural catastrophe events in order to build a more rapid rescue ***,due to the shorter duration of Tweets,it is difﬁcult to construct a perfect prediction model for determiningﬂ*** learning(ML)and deep learning(DL)approaches can be used to statistically developﬂood prediction *** the same time,the vast amount of Tweets necessitates the use of a big data analytics(BDA)tool forﬂood *** this regard,this work provides an optimal deep learning-basedﬂood forecasting model with big data analytics(ODLFF-BDA)based on Twitter *** suggested ODLFF-BDA technique intends to anticipate the existence ofﬂoods using tweets in a big data *** ODLFF-BDA technique comprises data pre-processing to convert the input tweets into a usable *** addition,a Bidirectional Encoder Representations from Transformers(BERT)model is used to generate emotive contextual embed-ding from ***,a gated recurrent unit(GRU)with a Multilayer Convolutional Neural Network(MLCNN)is used to extract local data and predict theﬂ***,an Equilibrium Optimizer(EO)is used toﬁne-tune the hyper-parameters of the GRU and MLCNN models in order to increase prediction *** memory usage is pull down lesser than 3.5 MB,if its compared with the other algorithm *** ODLFF-BDA technique’s performance was validated using a benchmark Kaggle dataset,and theﬁndings showed that it outperformed other recent approaches signiﬁcantly.

关键词： Big data analytics predictive models deep learning ﬂood prediction twitter data hyperparameter tuning

A Graph Theory Based Self-Learning Honeypot to Detect Persistent Threats

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

intelligent Automation & Soft Computing 2023年第3期35卷 3331-3348页

作者： R.T.Pavendan K.Sankar K.A.Varun Kumar department of Mathematics College of EngineeringAnna UniversityChennai600025India department of Networking and Communications School of ComputingSRM Institute of Science and TechnologyKattankulathur602203India

Attacks on the cyber space is getting exponential in recent *** penetrations and breaches are real threats to the individuals and *** security systems are good enough to detect the known threats but when it comes to Advanced Persistent Threats(APTs)they *** APTs are targeted,more sophisticated and very persistent and incorporates lot of evasive techniques to bypass the existing ***,there is a need for an effective defense system that can achieve a complete reliance of *** address the above-mentioned issues,this paper proposes a novel honeypot system that tracks the anonymous behavior of the APT *** key idea of honeypot leverages the concepts of graph theory to detect such targeted *** proposed honey-pot is self-realizing,strategic assisted which withholds the APTs actionable tech-niques and observes the behavior for analysis and *** proposed graph theory based self learning honeypot using the resultsγ(C(n,1)),γc(C(n,1)),γsc(C(n,1))outperforms traditional techniques by detecting APTs behavioral with detection rate of 96%.

关键词： Graph theory Domination Connected Domination Secure Connected Domination honeypot self learning ransomware

Comprehensive Overview of Multi-agent Systems for Controlling Smart Grids

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

CSEE Journal of Power and Energy Systems 2022年第1期8卷 115-131页

作者： Om Prakash Mahela Mahdi Khosravy Neeraj Gupta Baseem Khan Hassan Haes Alhelou Rajendra Mahla Nilesh Patel Pierluigi Siano Power System Planning Division Rajasthan Rajya Vidyut Prasaran Nigam Ltd.Jaipur-302005India Media Integrated Communication Laboratory Graduate School of EngineeringOsaka UniversityOsakaJapan Computer Science and Engineering department Oakland UniversityRochesterUSA department of Electrical and Computer Engineering Hawassa UniversityHawassa 1530Ethiopia Faculty of Mechanical and Electrical Engineering Tishreen UniversityLattakiaSyria department of Electrical Engineering National Institute of Technology Kurukshetra department of Management&Innovation Systems University of Salerno84084 SalernoItaly

Agents are intelligent entities that act flexibly and autonomously and make wise decisions based on their intelligence and experience.A multi-agent system(MAS)contains multiple,intelligent,and interconnected collaborating agents for solving a problem beyond the ability of a single agent.A smart grid(SG)combines advanced intelligent systems,control techniques,and sensing methods with an existing utility power *** controlling smart grids,various control systems with different architectures have already been ***-based control of power system operations has been shown to overcome the limitations of time required for analysis,relaying,and protection;transmission switching;communication protocols;and management of plant *** systems provide an alternative for fast and accurate power network *** paper provides a comprehensive overview of MASs used for the control of smart *** paper provides a wide-spectrum view of the status of smart grids,MAS-based control techniques and their implementation for the control of smart *** of MASs in the control of various aspects of smart grids-including the management of energy,marketing energy,pricing,scheduling energy,reliability,network security,fault handling capability,communication between agents,SG-electrical vehicles,SG-building energy systems,and soft grids—have been critically *** than a hundred publications on the topic of MAS-based control of smart grids have been critically examined,classified,and arranged for fast reference.

关键词： Coordinated control multi-agent systems renewable energy sources smart energy infrastructure smart grid

Machine Learning Prediction Models of Optimal Time for Aortic Valve Replacement in Asymptomatic Patients

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

intelligent Automation & Soft Computing 2023年第7期37卷 455-470页

作者： Salah Alzghoul Othman Smadi Ali Al Bataineh Mamon Hatmal Ahmad Alamm Biomedical Engineering department The Hashemite UniversityZarqaJordan department of Electrical and Computer Engineering Norwich UniversityNorthfieldVermont05663USA department of Biochemistry and Molecular Biology The Hashemite UniversityZarqaJordan National Centre for Big Data Science and Artificial Intelligence AmmanJordan

Currently,the decision of aortic valve replacement surgery time for asymptomatic patients with moderate-to-severe aortic stenosis(AS)is made by healthcare professionals based on the patient’s clinical biometric records.A delay in surgical aortic valve replacement(SAVR)can potentially affect patients’quality of *** using ML algorithms,this study aims to predict the optimal SAVR timing and determine the enhancement in moderate-to-severe AS patient survival following *** study represents a novel approach that has the potential to improve decision-making and,ultimately,improve patient *** analyze data from 176 patients with moderate-to-severe aortic stenosis who had undergone or were indicated for *** divide the data into two groups:those who died within the first year after SAVR and those who survived for more than one year or were still alive at the last *** then use six different ML algorithms,Support Vector Machine(SVM),Classification and Regression Tree(C and R tree),Generalized Linear(GL),Chi-Square Automatic Interaction Detector(CHAID),Artificial Neural Net-work(ANN),and Linear Regression(LR),to generate predictions for the best timing for *** results showed that the SVM algorithm is the best model for predicting the optimal timing for SAVR and for predicting the post-surgery survival *** optimizing the timing of SAVR surgery using the SVM algorithm,we observed a significant improvement in the survival period after *** study demonstrates that ML algorithms generate reliable models for predicting the optimal timing of SAVR in asymptomatic patients with moderate-to-severe AS.

关键词： Aortic stenosis aortic valve replacement machine learning survival period enhancement artificial intelligence in cardiology

Social Energy:Mining Energy From the Society

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 466-482页

作者： Jun Jason Zhang David Wenzhong Gao Yingchen Zhang Xiao Wang Xiangyang Zhao Dongliang Duan Xiaoxiao Dai Jun Hao Fei-Yue Wang department of Electrical and Computer Engineering Ritchie School of Engineering and Computer ScienceUniversity of Denver IEEE National Renewable Energy Laboratory Qingdao Academy of intelligent Industries(QAII) QingdaoShandongChinaand SKL-MCCSCASIA School of Automation Science and Electrical Engineering Beihang University department of Electrical and Computer Engineering College of Engineering and Applied ScienceUniversity of Wyoming State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Research Center of Computational Experiments and Parallel Systems National University of Defense Technology

The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social *** this perspective,we define "social energy" as a complex sociotechnical system of energy systems,social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system *** recent advancement in intelligent technology,including artificial intelligence and machine learning technologies,sensing and communication in Internet of Things technologies,and massive high performance computing and extreme-scale data analytics technologies,enables the possibility of substantial advancement in socio-technical system optimization,scheduling,control and *** this paper,we provide a discussion on the nature of energy,and then propose the concept and intention of social energy systems for electrical power.A general methodology of establishing and investigating social energy is proposed,which is based on the ACP approach,i.e., "artificial systems"(A), "computational experiments"(C) and "parallel execution"(P),and parallel system methodology.A case study on the University of Denver(DU) campus grid is provided and studied to demonstrate the social energy *** the concluding remarks,we discuss the technical pathway,in both social and nature sciences,to social energy,and our vision on its future.

关键词： ACP distribution locational marginal pricing intelligent operation in power systems parallel control parallel intelligence parallel management social energy socio-technical energy systems