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RSI/ISM International Conference on Robotics and Mechatronics

作者： Hassan Bayani Rasoul Sadeghian Mehdi Tale Masouleh Ahmad Kalhor Department of Mechatronics Engineering Qazvin Branch Islamic Azad University Qazvin Iran Human and Robot Interaction Laboratory Faculty of New Sciences and Technologies University of Tehran Iran

ISBN: (纸本)9781467372350

This paper presents different classical control approaches for planar cable-driven parallel robots. For the proposed robot, PD and PID controllers are designed based on the concept of pole placement method. In order to optimize and tune the controller parameters of planar cable-driven parallel robot, Differential Evaluation, Particle Swarm Optimization and Genetic algorithms are applied as optimization techniques. The simulation results of Genetic algorithm, Particle Swarm Optimization and Differential Evaluation algorithms reveal that the output results of tunes controllers with Particle Swarm Optimization and Differential Evaluation algorithms are more similar than Genetic algorithm and the processing time of Differential Evaluation is less than Genetic algorithm and Particle Swarm Optimization. Moreover, performance of the Particle Swarm Optimization and Differential Evaluation algorithms are better than Genetic algorithm for tuning the controllers parameters.

关键词： Classic Controllers Tuning intelligent algorithms

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Applying intelligent Optimization algorithms for Evaluation of Transformer Black Box Model 6th

Applying Intelligent Optimization Algorithms for Evaluation ...

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6th International Workshop on Soft Computing Applications (SOFA)

作者： Bigdeli, Mehdi Valii, Mohammad Azizian, Davood Islamic Azad Univ Zanjan Branch Dept Elect Engn Zanjan Iran Islamic Azad Univ Abhar Branch Dept Elect Engn Abhar Iran

ISBN: (纸本)9783319184166;9783319184159

To study the behavior of the transformers and the effects of these devices on power network performance in transient states, various models with different objectives are presented. One of the most important objectives is to investigate the overvoltages made in transformer as a result of lightning waves. For this reason, a black box model applied in the analysis of transient state of the transformer high frequency (up to 1.2 MHz). As a new work, the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Imperialist Competitive Algorithm (ICA) are proposed in the estimation of parameters of black box model using the necessary measurements on three-phase transformer 2.5 MVA and 6300/420 V and then compared by analytical methods.

关键词： Transformer Transient analysis Black box model intelligent algorithms

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Empowering research in chemistry and materials science through intelligent algorithms

Artificial Intelligence Chemistry

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Artificial Intelligence Chemistry 2024年第1期2卷

作者： Jinglong Lin Fanyang Mo School of Materials Science and Engineering Peking University Beijing 100871 PR China AI for Science (AI4S)-Preferred Program Peking University Shenzhen Graduate School Shenzhen 518055 PR China

In this review, we explore the integration of intelligent algorithms in chemistry and materials *** begin by delineating the core principles of Machine Learning, Deep Learning, and optimization algorithms, highlighting their bespoke adaptation to these scientific domains. The focus then shifts to the critical processes of data management, including collection, refinement, and feature engineering, alongside strategies for efficient data mining from targeted databases and literatures. Subsequently, we present a concise overview of the diverse applications of these algorithms, emphasizing their transformative impact in both fields. Finally, this review explores the future prospects and challenges of these emerging algorithms.

关键词： intelligent algorithms Machine Learning Deep Learning

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Exergy analysis and thermodynamic optimisation of a steam power plant-based Rankine cycle system using intelligent optimisation algorithms

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AUSTRALIAN JOURNAL OF MECHANICAL ENGINEERING 2022年第1期20卷 54-65页

作者： Elahifar, Samad Assareh, Ehsanolah Moltames, Rahim Islamic Azad Univ Dept Mech Engn Dezful Branch Dezful Iran Sharif Univ Technol Dept Energy Engn Energy Syst Engn Tehran Iran

In this paper, exergy analysis of a steam power plant located in southern Iran named Zarand power plant has been studied. In order to optimize the performance of the Rankine cycle and achieve higher exergy efficiency, several parameters have been considered as decision variables. Knowing that there is the ability to change some of the parameters in the specific range in the process of electricity production in power plant, temperature and output pressure of the boiler and output pressure of four steps of extraction turbine have been selected as six decision variables. Also, exergy efficiency has been considered as the objective function. For this purpose, the exergy efficiency of the system is optimized using intelligent algorithms including bees, fireflies, and algorithm based on teaching and learning and they are compared with each other. The results show that in the case of suitable changes of decision variables and applying appropriate algorithms, exergy efficiency of the studied thermal power plant can be increased from 30.1% to 30.68047%, 30.70368%, and 30.70369%, respectively. It means using optimization algorithms of bees, fireflies, training-learning, exergy efficiency of the Rankine cycle of the studied power plant can be increased by 0.58047%, 0.60368%, and 0.60369%, respectively.

关键词： Exergy efficiency intelligent algorithms Rankine cycle thermal power plant

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Application of digital entertainment experience based on intelligent interactive system in personalized fitness training system

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ENTERTAINMENT COMPUTING 2025年 52卷

作者： Geng, Shuai Sichuan Minzu Coll Coll Phys Educ Kangding 626001 Sichuan Peoples R China

The application of digital media in fitness environments can improve the entertainment of the fitness process, allowing users to watch entertainment videos while engaging in fitness activities. At the same time, we can add relevant game elements to the fitness process, such as playing tennis through gesture movements, thereby increasing user interest in fitness participation. Therefore, this article has developed a personalized fitness training system using optical sensors and intelligent algorithms, and conducted testing experiments on blood oxygen saturation under two sports states: running and cycling. This article analyzes the intelligent optimization algorithm for optical signals. This algorithm has strong adaptability and intelligence level, and can directly learn and adjust the model based on the characteristics of the data. The automation performance of the intelligent algorithm can effectively reduce labor costs and improve efficiency. Finally, this article provides a basic analysis and testing of the personalized fitness training system. Through the obtained data, personalized guidance is provided to users, helping people make fitness more scientific and intelligent, and improving fitness efficiency.

关键词： Optical sensors Dynamic spectroscopy intelligent algorithms Personalized fitness training

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Research Progress on Key Technologies of Modularized intelligent Reconnaissance and Early Warning Satellites

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JOURNAL OF AERONAUTICS ASTRONAUTICS AND AVIATION 2025年第1期57卷 55-79页

作者： Gao, Mingliang Yang, Jingyu Zhang, Faming He, Jingjie Ling, Yunxiao Kuai, Enze Shenyang Aerosp Univ Space Solar Power Stn Lab Intelligent Aircraft Syst Theory & Technol Lab 37Daoyi South St Shenyang 110136 Peoples R China Shenyang Goddard Intelligent Equipment Technol Co Res & Dev Dept Shenyang 110001 Peoples R China Shenyang Aircraft Design & Res Inst 40Tawan St Shenyang 110087 Peoples R China

The origin of reconnaissance satellites can be traced back to the last century. After decades of development, reconnaissance satellites have a variety of payloads, mainly including optical reconnaissance payload, radar payload and electronic reconnaissance payload. According to the different functional requirements of each system of reconnaissance and early warning satellite, this paper mainly analyzes the key technology progress of payload, data processing and communication module. It includes the advantages and disadvantages of various payloads and existing capabilities, radar image processing algorithm, image classification and recognition algorithm, and image high-speed encryption scheme. In addition, some technologies and schemes of satellite attitude control, orbit control and thermal control are analyzed. Within this framework, the sensor module discusses the current applications and scenarios of payloads, which is the basis of satellite missions;The data processing module describes the imaging and recognition algorithm in detail, which is the key to the intelligence of reconnaissance satellite;The communication module is particularly noteworthy for its encryption method and technology, which will ensure that the data is protected from unauthorized access;The quality of the control effect will have an impact on the reconnaissance effect. This paper shows an example of high-precision control in the control module. It is undeniable that reconnaissance satellites will develop towards miniaturization, modularization, intelligence and constellation networking. In the space-based reconnaissance and early warning system, various types of satellites cooperate with each other to undertake the reconnaissance and early warning tasks to the ground.

关键词： Modularization reconnaissance satellites intelligent algorithms on-board SAR satellite optical payloads

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intelligent Bi-directional Verification System for Hydropower Engineering Construction Inspection 30th

Intelligent Bi-directional Verification System for Hydropowe...

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30th International Conference on Computational and Experimental Engineering and Sciences

作者： Chen, Zuwen Yang, Rui Li, Zichang Lin, Peng Zhou, Chenghao Zhou, Wenting Gao, Xiangyou Liu, Xinyi Wang, Zhengqing POWERCHINA Guiyang Engn Corp Ltd Guiyang 550081 Peoples R China Tsinghua Univ Sichuan Energy Internet Res Inst Chengdu 610213 Peoples R China Tsinghua Univ Dept Hydraul Engn Beijing 100084 Peoples R China

ISBN: (纸本)9783031774911;9783031774898;9783031774881

Due to large project size of hydropower engineering, construction quality inspection is normally conducted by overseeing, with supplementary monitoring and data evaluation when available. With the rapid advancement of artificial intelligence in recent years, intelligent technology has been increasingly applied in the practice of engineering construction and inspection. To improve the efficiency and intelligence of construction quality inspection, an intelligent bi-directional verification system based on algorithms, such as ZoeDepth and EDTER, was developed. First, a virtual field of the physical world is generated using the depth estimation approach. Image processing techniques, such as image object recognition and object delineation identification, are used to establish the location, position and posture of actual objects in images as well as measure their dimensions. Second, object-to-object matching is accomplished by aligning the engineering design in BIM models with the objects identified in the images. As a result, image processing models can be calibrated for intelligent object recognition. Object dimensions can then be measured in the virtual field. Corresponding object design information can be retrieved from the BIM model for construction quality examination. Finally, an inspection report is automatically generated and can be synchronized to a comprehensive engineering management platform, when network communication is available. Based on the aforementioned technical framework, a single-person intelligent inspection wearable was developed and tested for technical evaluation. The results indicated that the proposed algorithms can quickly identify construction objects for in-situ comparison with the design in BIM models and the device satisfies the requirement of being simple to wear and operated by one person when perform the engineering inspection.

关键词： Engineering inspection intelligent algorithms image processing bi-directional verification equipment development

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Improved adaptive snake optimization algorithm with application to multi-UAV path planning

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2025年第8期47卷 1639-1650页

作者： Liu, Peng Sun, Nianyi Wan, Haiying Zhang, Chengxi Zhao, Jin Wang, Guangwei Guizhou Univ Key Lab Adv Mfg Technol Minist Educ Guiyang 550025 Peoples R China Guizhou Univ Sch Mech Engn Guiyang Peoples R China Jiangnan Univ Key Lab Adv Proc Control Light Ind Minist Educ Wuxi Peoples R China

Metaheuristic swarm-based intelligent algorithms are extensively employed for engineering optimization tasks due to their efficacy in addressing nonlinear and high-dimensional challenges. This study presents an improved snake optimization algorithm (SOEA) to overcome the limitations of the standard snake optimization algorithm (SOA), such as slow convergence, subpar optimization accuracy, and vulnerability to local optima. The integration of elite opposition-based learning strategy enables the adjustment of snake population positions, thereby enhancing the algorithm's global search capacity and iteration speed. Moreover, the incorporation of the adaptive threshold method enhances its local search performance and convergence speed. Experimental results demonstrate the superior performance of the proposed SOEA algorithm in achieving global optimization and accelerating convergence speed. The SOEA algorithm achieves a remarkable 34% reduction in the average number of iterations required compared to the SOA algorithm, and it also exhibits a lower mean squared error. Finally, the effectiveness of the proposed algorithm is validated through its successful application to solving the multi-UAV path planning problem.

关键词： Snake optimization algorithm metaheuristic swarm-based algorithm intelligent algorithms adaptive threshold method

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Deep characteristic learning model for real-time flow monitoring based on H-ADCP

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JOURNAL OF HYDROLOGY-REGIONAL STUDIES 2025年 57卷

作者： Li, Yu Zhao, Xin Wang, Yibo Zeng, Ling Changjiang Water Resources Commiss Bur Hydrol Wuhan 430010 Peoples R China

Study region: The Luohu hydrological station, located in southeastern China, which has unstable water level- discharge relationship caused by tides. Study focus: Real-time flow monitoring based on horizontal-acoustic Doppler current profiler (HADCP), which remains insufficient to deal with low monitoring accuracy, complex flow characteristics, and large data volumes caused by the construction and operation of hydraulic engineering, backwater, tides, siltation changes, and high-frequency monitoring. This study proposed a deep characteristic learning (DCL) model to identify and extract the nonlinear characteristics between flow velocity of H-ADCP cell and river cross section by incorporating multiple intelligent algorithms. New hydrological insights for the region: The DCL model performs efficiently with a determination coefficient (R2) of 0.93 between the simulated and observed discharge, which is obviously better than the single intelligent algorithm-based models. The DCL model allows for adaptive algorithm selection and parameter adjustment according to the characteristics of river cross section and HADCP data. It shows strong self-learning capability and good simulation accuracy even with few training samples. Additionally, the DCL model is demonstrated to be stable and applicable in terms of model structure and practical performance. This study can serve as a reference for realtime flow monitoring under complex hydrological conditions.

关键词： Deep characteristic learning H-ADCP Real-time flow monitoring intelligent algorithms

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Structural edge damage detection based on wavelet transform and immune genetic algorithm

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SCIENTIFIC REPORTS 2025年第1期15卷 1-18页

作者： Zhao, Jianwei Zhou, Zhuo Guan, Deqing Gong, Liang Changsha Univ Sci & Technol Dept Civil Engn Changsha Hunan Peoples R China Hunan Univ Informat Technol Changsha Hunan Peoples R China Changsha Univ Sci & Technol Sch Grad Changsha Hunan Peoples R China

The wavelet transform (WT) has gained significant attention for its ability to identify damage details within strain modes. However, edge damage in structures often remains obscured and unrecognizable when WT is applied, primarily due to edge effects. intelligent algorithms used to assess structural damage severity often face challenges such as premature convergence and a tendency to settle on local optima. To address these challenges, damage location is analyzed using WT with a fitting extension of the original vibration signal, effectively mitigating edge effects. Additionally, an immune-genetic algorithm, integrating genetic and immune algorithms, is employed to overcome limitations of traditional intelligent algorithms in damage severity identification. The two-stage method's effectiveness was validated through finite element simulations of fixed beam and frame structures, as well as vibration tests of fixed and cantilever beams, for locating and assessing edge damage. This method showed clear advantages, including precise damage characterization, noise robustness, and high sensitivity to edge damage.

关键词： Edge effect Fitting extension Wavelet transform intelligent algorithms Immune-genetic

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