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Distributed Parameter Identification Framework Based on intelligent algorithms for Permanent Magnet Synchronous Wind Generator

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ENERGIES 2025年第3期18卷 683-683页

作者： Wu, Xiaoxuan Tian, De Meng, Huiwen Su, Yi North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewable Beijing 102206 Peoples R China

Parameter identification of a permanent magnet synchronous wind generator (PMSWG) is of great significance for condition monitoring, fault diagnosis, and robust control. However, the conventional multi-parameter identification approach for a PMSWG is plagued by deficiencies, including its sluggish identification speed, subpar accuracy, and susceptibility to local optimization. In light of these challenges, this paper proposes a distributed parameter identification framework based on intelligent algorithms. The proposed approach involves the deployment of SSA, DBO, and PSO algorithms, leveraging golden sine ratio and Gaussian variation strategies for multi-parameter optimization and performance enhancement. Second, the optimal solutions of each intelligent algorithm are aggregated to achieve overall optimization performance enhancement. The efficacy of the proposed method is substantiated by a 6 MW PMSWG parameter identification practice simulation result, which demonstrates its superiority. The proposed method was shown to identify parameters more quickly and effectively than the underlying algorithms, which is of great significance for condition monitoring, fault diagnosis, and robust control of the PMSWG.

关键词： permanent magnet synchronous wind generator parameter identification distributed framework intelligent algorithms

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Simulation of entertainment interactive robots based on intelligent algorithms in personalized fitness training systems

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ENTERTAINMENT COMPUTING 2025年 52卷

作者： Ke, Ni Yaqin, Gao Jiangxi Univ Sci & Technol Sch Phys Educ & Arts Ganzhou 341000 Jiangxi Peoples R China Hunan Univ Med Sch Sports Arts Huaihua 418000 Hunan Peoples R China

In the current context of rapid development of information technology and AI, entertainment interactive robots can play an auxiliary role in fitness training. intelligent technical services can provide athletes with timely training course information and gamified sports training. Various data will also be uploaded to technical platforms for analysis. This article studies the design of a personalized fitness training system for entertainment interactive robots based on intelligent algorithms. Firstly, this article analyzes the main technologies of photon integrated biosensors, establishes a linear photon integrated biosensor imaging model. Choose to use intelligent algorithms to optimize coverage for wireless sensor networks. This problem is transformed into a mathematical function model, and then the optimal solution is sought through algorithms, effectively reducing the energy consumption of the network and extending its lifespan. The system improves interaction with humans by collecting training action videos, automatically recognizes the types of human training actions, and automatically extracts key postures from training actions for comparison and analysis with standard postures. The practice and research of human-computer interaction have shown that in addition to the actual performance of social robots, the emotional interaction of social robots can also affect people's trust in their abilities.

关键词： Interactive experience Entertainment robots intelligent algorithms Fitness training

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intelligent algorithms and standards for interoperability in Internet of Things

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2019年 92卷 1187-1191页

作者： Ahmad, Awais Cuomo, Salvatore Wu, Wei Jeon, Gwanggil Bahria Univ Islamabad Pakistan Univ Napoli Federico II Naples Italy Sichuan Univ Chengdu Sichuan Peoples R China Xidian Univ Xian Shaanxi Peoples R China Incheon Natl Univ Incheon South Korea

Research associated with intelligent algorithm and interoperability in internet of things became important topic over the next few years. The topic includes work on (i) infrastructures, platforms, architectures and designs supporting interoperability in IoT, (ii) environment at various levels (data, device, middleware, networking, and application service), (iii) intelligent semantic interoperability solutions, (iv) messaging protocols within IoT to enhance the interoperability of various interactive systems, (v) security- and privacy-aware IoT, monitoring performances and QoS, (vi) intelligent standards and algorithms for Interoperability between different IoT implementations, and (vii) survey on suitability of intelligent standards and algorithms for interoperability and heterogeneity in IoT infrastructures. The papers of this special issue address a variety of issues and concerns in interoperability in IoT: searching and processing IoT, implementing and modelling event and workflow systems, visualization modelling and simulation based on innovative list of solutions. (C) 2018 Published by Elsevier B.V.

关键词： intelligent algorithms Internet of Things Semantic interoperability solutions Monitoring performances and QoS IoT implementations Low cost interoperability in IoT

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intelligent algorithms and complex system for a smart parking for vaccine delivery center of COVID-19

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COMPLEX & intelligent SYSTEMS 2022年第1期8卷 597-609页

作者： Jemmali, Mahdi Majmaah Univ Coll Sci Zulfi Dept Comp Sci & Informat Al Majmaah 11952 Saudi Arabia Univ Sousse MARS Lab Sousse Tunisia Univ Monastir Higher Inst Comp Sci & Math Monastir Dept Comp Sci Monastir 5000 Tunisia

Achieving community immunity against the coronavirus disease 2019 (COVID-19) depends on vaccinating the largest number of people within a specific period while taking all precautionary measures. To address this problem, this paper presents a smart parking system that will help the health crisis management committee to vaccinate the largest number of people with the minimum period of time while ensuring that all precautionary measures are followed, through a set of algorithms. These algorithms seek to ensure a uniform distribution of persons in parking. This paper proposes a novel complex system for smart parking and nine algorithms to address the NP-hard problem. The experimental results demonstrate the performance of the proposed algorithms in terms of gap and time. Applying these algorithms to smart cities to ensure precautionary measures against COVID-19 can help fight against this pandemic.

关键词： COVID-19 Smart city intelligent algorithms Complex system Big data Operations management

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intelligent algorithms in Home Energy Management Systems: A Survey

Intelligent Algorithms in Home Energy Management Systems: A ...

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IEEE Conference on SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation

作者： Liu, Qi Dannah, Williams Liu, Xiaodong Shandong Beiming Med Technol Ltd 777 Shunfeng Rd Jinan Peoples R China Nanjing Univ Informat Sci & Technol Jiangsu Collaborat Innovat Ctr Atmospher Environm Sch Comp & Software Nanjing Peoples R China Edinburgh Napier Univ Sch Comp Edinburgh Midlothian Scotland

ISBN: (数字)9781728140346

ISBN: (纸本)9781728140346

The critical role played by Home Energy Management Systems (HEMS) in smart grids has opened up more discussions regarding the control of demand-side energy consumption. intelligent algorithms play a vital role in managing the levels of power consumed by electrical appliances in the household. When energy consumption is efficiently controlled, peak loads are reduced and electrical appliances are switched with respect to their priority levels, thereby keeping the household power consumption rate at a minimal level towards cost saving for residential consumers. In recent years, intelligent systems have become an important aspect of our daily lives, improving our utilization of energy resources and as a result, enhancing our way of living. This paper presents a survey of intelligent algorithms incorporated in various home energy management tools to enhance efficiency in load management.

关键词： intelligent algorithms Home Energy Management Systems Smart Grids Demand-Side

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intelligent algorithms: new avenues for designing nanophotonic devices [Invited]

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Chinese Optics Letters 2021年第1期19卷 31-63页

作者： Lifeng Ma Jing Li Zhouhui Liu Yuxuan Zhang Nianen Zhang Shuqiao Zheng Cuicui Lu Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurements of Ministry of Education Beijing Key Laboratory of Nanophotonics and Ultrafine Optoelectronic SystemsSchool of PhysicsBeijing Institute of TechnologyBeijing 100081China Collaborative Innovation Center of Light Manipulations and Applications Shandong Normal UniversityJinan 250358China

The research on nanophotonic devices has made great progress during the past decades. It is the unremitting pursuit of researchers that realize various device functions to meet practical applications. However, most of the traditional methods rely on human experience and physical inspiration for structural design and parameter optimization, which usually require a lot of resources, and the performance of the designed device is limited. intelligent algorithms, which are composed of rich optimized algorithms, show a vigorous development trend in the field of nanophotonic devices in recent years. The design of nanophotonic devices by intelligent algorithms can break the restrictions of traditional methods and predict novel configurations, which is universal and efficient for different materials, different structures, different modes, different wavelengths, etc. In this review, intelligent algorithms for designing nanophotonic devices are introduced from their concepts to their applications, including deep learning methods, the gradient-based inverse design method, swarm intelligence algorithms, individual inspired algorithms, and some other algorithms. The design principle based on intelligent algorithms and the design of typical new nanophotonic devices are reviewed. intelligent algorithms can play an important role in designing complex functions and improving the performances of nanophotonic devices, which provide new avenues for the realization of photonic chips.

关键词： intelligent algorithms nanophotonic devices deep learning methods swarm intelligence genetic algorithm

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intelligent algorithms and Real-Time Monitoring Systems in Social and Psychological Crisis Intervention

Intelligent Algorithms and Real-Time Monitoring Systems in S...

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2024 International Conference on Power, Electrical Engineering, Electronics and Control, PEEEC 2024

作者： Cao, Di Xue, Hao Zhou, Qiao Yu, Lei Jilin Open University Jilin Changchun130022 China

ISBN: (纸本)9798350378917

In recent years, with the acceleration of social pace and the increase of competitive pressure, people's mental health problems have become increasingly prominent, and psychological crises have occurred frequently, posing a serious threat to social stability and personal well-being. Psychological crisis, as a serious state of psychological imbalance, not only affects an individual's quality of life, but may also trigger a series of social problems. Therefore, how to effectively prevent and guide psychological crises has become an urgent problem to be solved in current social psychological crisis intervention work. This article proposes a real-time monitoring system for social and psychological crisis intervention. This system is based on advanced machine learning (ML) algorithms and can capture and analyze individual psychological changes in real time, providing timely and effective support for psychological crisis intervention. This system integrates multiple technologies such as big data analysis, natural language processing, and emotional computing. By deeply mining text information on social media, online forums, and other platforms, it can accurately identify potential psychological crisis signals. The experimental results indicate that through real-time monitoring and data analysis, the system can promptly identify potential individuals with psychological crises and provide them with personalized psychological assistance. © 2024 IEEE.

关键词： intelligent algorithms Intervention in social and psychological crises real time monitoring system

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Top ten intelligent algorithms towards smart manufacturing

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JOURNAL OF MANUFACTURING SYSTEMS 2023年 71卷 158-171页

作者： Zhang, Meng Tao, Fei Zuo, Ying Xiang, Feng Wang, Lihui Nee, A. Y. C. Chinese Aeronaut Estab Beijing 100029 Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Beihang Univ Int Res Inst Multidisciplinary Sci Digital Twin Int Res Ctr Beijing 100191 Peoples R China Wuhan Univ Sci & Technol Key Lab Met Equipment & Control Technol Minist Educ Wuhan 430081 Peoples R China Wuhan Univ Sci & Technol Hubei Key Lab Mech Transmiss & Mfg Engn Wuhan 430081 Peoples R China KTH Royal Inst Technol Dept Prod Engn SE-10044 Stockholm Sweden Natl Univ Singapore Dept Mech Engn Singapore 117576 Singapore

intelligent algorithms can empower the development of smart manufacturing, since they can provide optimal solutions for detection, analysis, prediction and optimization. In recent ten years, publications on intelligent algorithms in smart manufacturing have increased sharply, showing superior performance in solving problems such as shop-floor scheduling, equipment prognosis, product defect detection and manufacturing service composition, etc. In this context, this paper focuses on the selection of commonly used top ten algorithms by providing a sound understanding of how they contribute to improving manufacturing processes. First, it presents a comprehensive survey and bibliometric analysis according to relevant literature. On this basis, the top ten algorithms are highlighted and reviewed. Then three key issues concerning when to use these algorithms in smart manufacturing, how to use them, as well as why to use them are studied. Finally, the challenges for the ten algorithms are summarized.

关键词： intelligent algorithms Artificial intelligence Smart manufacturing Machine learning intelligent optimization

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Smart grid management: Integrating hybrid intelligent algorithms for microgrid energy optimization

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ENERGY REPORTS 2024年 12卷 2997-3019页

作者： Pramila, V. Kannadasan, R. Bharathsingh, J. Rameshkumar, T. Alsharif, Mohammed H. Kim, Mun-Kyeom BS Abdur Rahman Crescent Inst Sci & Technol Dept Elect & Elect Engn Chennai 600048 India Sri Venkateswara Coll Engn Dept Elect & Elect Engn Sriperumbudur 602117 India Kalasalingam Acad Res & Educ Krishnankoil Dept Comp Sci & Engn Srivilliputhur 626126 India KPR Inst Engn & Technol Elect & Elect Engn Coimbatore 641407 India Sejong Univ Coll Elect & Informat Engn Dept Elect Engn 209 Neungdong Ro Seoul 05006 South Korea Chung Ang Univ Sch Energy Syst Engn 84 Heukseok Ro Seoul 06974 South Korea

The increasing global demand for power drives the need for advancements in generation, control, and supply technologies. While bulk power generation remains cost-effective, it depends on transmission and distribution systems for delivery. Integrating distributed generators into the grid enhances reliability and direct power supply to consumers. Micro Grids (MGs) are a promising solution, offering smoother and more reliable operations. This study explores MGs, incorporating the latest loads and distributed generators to minimize operating costs for electrical power providers. This work utilizes intelligent algorithms, including the Firefly algorithm, Spider Monkey Optimization (SMO), and a hybrid approach combining both. The Firefly algorithm, inspired by swarm intelligence, mimics fireflies' light emission to optimize solutions. SMO, based on spider monkeys' social behavior, balances exploration and exploitation to achieve optimal results. A novel hybrid algorithm is developed to minimize MG operating costs by combining SMO's exploration with the Firefly algorithm's neighborhood optimization;enhancing navigation through the complex constraint solution space of MGs. Case studies on a modified IEEE 33-bus test feeder are conducted. The study compares three metaheuristic methods with nonconvex solution spaces to MG operational algorithms. The results demonstrate the hybrid method's efficacy in determining the optimal location and size of real and reactive power support devices for MG operation. Numerical results show the hybrid algorithm's superiority over existing methods, reducing operating costs by 7.5 %, real power loss by 36.5 %, and reactive power loss by 1.7 %, and voltage deviation by 16.895. By considering MG constraints, the hybrid algorithm consistently delivers better outcomes, optimizing operating costs and ensuring efficient power supply. This study presents a novel MG optimization approach, enhancing future energy systems with improved solutions.

关键词： Microgrid Optimization intelligent algorithms Distributed Generation Firefly Algorithm Spider Monkey Optimization Hybrid Optimization algorithms

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Application of particle swarm optimization and simple intelligent algorithms in building nonlinear models for predicting formation fracture initiation pressure

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ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 2024年第1期46卷 17136-17152页

作者： Hossein, Mohammadi Mohammad Ali, Riahi Hessam, Mansouri Siahgoli Univ Amirkabir Dept Petr Engn Tehran Iran Univ Iran Inst Geophys Tehran Iran

The main objective of this study is to estimate the FIP on Sarvak and Ilam formations using neural networks and intelligent algorithms. For this purpose, we first calculate the geomechanical parameters and the formation FIP of three wells, using well log data and experimental relationships. Secondly, we employ neural networks to estimate the FIP in three wells which randomly selected. Thirdly, we obtain a nonlinear mathematical model to calculate the formation FIP using simple genetic algorithms and particle swarm optimization (PSO). Based on our experiments, the PSO performs better than the genetic algorithm. Using the two new nonlinear models we estimated the pore pressure to be between 34.47 and 48.26 MPa, vertical stress between 75.84 and 131 MPa. Maximum and minimum horizontal stress between 62.05 and 87.7 MPa, FIP between 87.7 and 110.3 MPa.

关键词： Formation fracture initiation pressure particle swarm optimization intelligent algorithms nonlinear model well log

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