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Research on intelligent clustering of male upper body

TEXTILE RESEARCH JOURNAL 2022年第13-14期92卷 2174-2193页

作者： Cheng, Pengpeng Zeng, Xianyi Bruniaux, Pascal Wang, Jianping Chen, Daoling Gemtex Ensait Cent Lille 2 Allee Louise & Victor Champier BP 30329 F-59000 Roubaix France Donghua Univ Coll Fash & Design Shanghai Peoples R China Minjiang Univ Clothing & Design Fac Fuzhou Peoples R China

To study the upper body characteristics of young men, the body circumference, length, width, thickness, and angle of young men aged 18-25 and 26-35 years were collected to comprehensively characterize the concave and convex features of the front, back, and side of the human body. The Cuckoo Search-Density Peak intelligent algorithm was used to extract the feature factors of the upper body of men, and to cluster them. To verify the effectiveness of the intelligent algorithm, the clustering results of Cuckoo Search-Density Peak, Density Peak, Particle Swarm Optimization-Density Peak algorithm, Ant Colony Optimization-Density Peak algorithm, Genetic algorithm-Density Peak algorithm, and Artificial Bee Colony-Density Peak algorithm were evaluated by Silouette and F-measures, respectively. The results show that the Cuckoo Search-Density Peak algorithm has the best clustering results and is superior to other algorithms. There are some differences in somatotype characteristics and somatotype indexes between young men aged 18-25 and 26-35 years.

关键词： young men intelligent algorithm cuckoo search-density peak algorithm clustering

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A stable control method for planar robot with underactuated constraints via motion planning and intelligent optimization

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MEASUREMENT & CONTROL 2023年第9-10期56卷 1826-1834页

作者： Huang, Zixin Li, Xinpeng Wei, Ziang Wan, Xiao Wang, Lejun Nankai Univ Coll Artificial Intelligence Tianjin Peoples R China Wuhan Inst Technol Sch Elect & Informat Engn Wuhan Peoples R China Chongqing Univ Posts & Telecommun Chongqing Key Lab Complex Syst & Bion Control Chongqing Peoples R China Chongqing Univ Posts & Telecommun Chongqing Key Lab Complex Syst & Bion Control Chongqing 400065 Peoples R China

For the planar robot with underactuated constraints, a stable control method is presented on the foundation of motion planning method and intelligent optimization, which includes two stages. (1) Designing the controllers to control the actuated manipulators to given target states. (2) Planning the motion trajectory combined with the underactuated constraints between all links, using the intelligent algorithm to find the adaptable trajectory parameters, and tracking such planned trajectories to control full manipulators to the given states simultaneously. At last, multigroup simulations demonstrate the validity of the proposed method.

关键词： Planar underactuated robot motion planning stable control intelligent algorithm

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An intelligent resilience evaluation model for the development of urban underground space with safety concern of surrounding existing built environment

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TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 2024年 149卷

作者： Zhou, Cong Su, Yanqi He, Lei Peng, Luyuan Zhang, Yi Wu, Gang Soh, Chee Kiong Southeast Univ Sch Civil Engn Nanjing 211189 Jiangsu Peoples R China Southeast Univ State Key Lab Safety Durabil & Hlth Operat Long Sp Nanjing 211189 Jiangsu Peoples R China Univ Hong Kong Dept Civil Engn Hong Kong 999077 Peoples R China XCMG KAIGONG Heavy Ind Nanjing CO Ltd Nanjing 211161 Jiangsu Peoples R China

The rationality and safety of Urban Underground Space (UUS) construction are critical aspects of urban development. Given the lack of safety concern of the surrounding environment in existing layout planning research for newly constructed UUS, this study proposed a novel resilience evaluation model for UUS safe development through the cross -application of geotechnical analysis, urban planning theory, and artificial intelligence (AI). By re -using geological information, the proposed model mapping algorithm enables the application of geological models to refined numerical calculations which can accurately locate the range of excavation disturbances of new UUS. Subsequently, the proposed AI algorithm is trained to learn from the existing UUS excavation cases, establishing a mathematical mapping relationship between the main construction parameters of UUS and the safety indexes of surrounding affected buildings. The mapping relationship enables the assessment of the development resilience of UUS in the planned area through the safety evaluation of surrounding affected buildings. Finally, the layout of an underground station for Nanjing Metro Line 13 is used, as an example, to apply the proposed intelligent model. This study contributes to the tools and methods for UUS layout evaluation from a safety perspective, and seeks the breakthrough for the cross -application of geotechnical science and urban planning theory.

关键词： Urban underground space (UUS) 3D geological modelling Excavation disturbance intelligent algorithm Development resilience

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Exploring Enhancement of AR-HUD Visual Interaction Design Through Application of intelligent algorithms

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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGIES AND SYSTEMS APPROACH 2023年第2期16卷 1页

作者： Teng, Jian Wan, Fucheng Kong, Yiquan Lingnan Normal Univ Sch Mech & Elect Engn Zhanjiang Peoples R China Sehan Univ Coll Educ Yeongam Gun South Korea Lingnan Normal Univ Sch Mech & Elect Engn Zhanjiang Peoples R China Lingnan Normal Univ Sch Comp & Intelligent Mfg Zhanjiang Peoples R China

This study aims to optimize the visual interaction design of AR-HUD and reduce cognitive load in complex driving situations. An immersive driving simulation incorporating eye-tracking technology was utilized to analyze objective physiological indices and measure subjective cognitive load using the NASA-TLX. Additionally, a visual cognitive load index was integrated into a BP-GA neural network model for load prediction, enabling the derivation of an optimal solution for AR-HUD design. The optimized AR-HUD interface demonstrated a significant reduction in cognitive load compared to the previous prototype. The experimental group achieved a mean total score of 25.63 on the WP scale, whereas the control group scored 43.53, indicating a remarkable improvement of 41.4%. This study presents an innovative approach to optimizing AR-HUD design, effectively reducing cognitive load in complex driving situations. The findings demonstrate the potential of the proposed algorithm to enhance user experience and performance.

关键词： AR-HUD Cognitive Load Eye Tracking intelligent algorithm Interaction Design

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Research on Balance of Unmanned Aerial Vehicle with intelligent algorithms for Optimizing Four-Rotor Differential Control

Research on Balance of Unmanned Aerial Vehicle with Intellig...

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2019 2nd International Conference on Computer Science and Advanced Materials(CSAM 2019)

作者： Zhang Zhibiao Lv Qiang Wei Heng Department of Weapon and Control Academy of Army Armored Forces

The UAV without control surface(UAV) proposed in this paper uses the propeller driven by four electric motors as propulsion and attitude control. The UAV can take off and land vertically(VTOL), but the control of propeller is a particularly complex problem from hovering to cruise flight. A novel control algorithm using optimal estimates similar to multipurpose linear quadratic regulator(LQR) is suitable for the latest developments. One of the technologies can generate the transformation control input available for a time-varying system model, which will be used by aircraft pilots to provide the necessary control signals for UAV propellers. As a result, traditional trained pilots can control this novel UAV without additional training. In addition, it can be predicted that the general control algorithm can be used for autonomous control of UAVs in the future, allowing the autonomous development of novel control strategies to control the required UAVs.

关键词： intelligent algorithm four-rotor differential control UAV balance control

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Distance-Based intelligent Particle Swarm Optimization for Optimal Design of Permanent Magnet Synchronous Machine

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IEEE TRANSACTIONS ON MAGNETICS 2017年第6期53卷 1-4页

作者： Lee, Jin Hwan Kim, Jong-Wook Song, Jun-Young Kim, Dae-Woo Kim, Yong-Jae Jung, Sang-Yong Sungkyunkwan Univ Sch Elect & Elect Engn Suwon 16419 South Korea Dong A Univ Dept Elect Engn Busan 49315 South Korea Chosun Univ Dept Elect Engn Gwangju 61452 South Korea

In this paper, we propose a novel particle swarm optimization (PSO), which is based on the Euclidian distance of particles. In the conventional PSO, the convergence speed is decreased, since several particles that are far from swarm does not converge but wander around search area. The proposed algorithm, which is named after distance based intelligent PSO, assigns a new position and velocity to the furthest particle. Therefore, all particles gather around global optimum, and it is able to search for global optimum faster than that of the conventional PSO. To validate effectiveness of the proposed algorithm, we compare it to the conventional PSO using three numerical test functions. In addition, interior permanent magnet synchronous motor (IPMSM), which has characteristic of magnetic saturation in magnetic steel sheet, is chosen as target model of optimal design. Total harmonic distortion of back-electromotive force is optimized by optimization of rotor topology. Through optimal design of IPMSM, effectiveness of the proposed algorithm for electric machine design is verified.

关键词： intelligent algorithm interior permanent magnet synchronous machine (IPMSM) optimal design particle swarm optimization (PSO)

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intelligent MODELLING METHOD OF ENERGY HUB BASED ON DIRECTED MULTI-GRAPH

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THERMAL SCIENCE 2022年第1期26卷 681-691页

作者： Cai, Qingsen Luo, Xingqi Gao, Chunyang Zhao, Peiyu Wang, Peng Xian Univ Technol Inst Water Resources & Elect Power Xian Peoples R China Xian Univ Technol Xian Intelligent Energy Key Lab Xian Peoples R China

An energy hub, consisting of a combination of electricity, heat power, cooling pow-er, natural gas, and other energy sources, is considered a key component of the energy internet. It requires quick and accurate optimization and control as well as a standardized and programmable model. This study proposes an intelligent modelling method based on a directed multigraph. This method starts from an input-output model and then establishes a directed multigraph in which a vertex indicates energy and an edge indicates energy conversion equipment and its pa-rameters. Then, an adjacency matrix is obtained by processing and simplifying the directed multigraph. This adjacency matrix is searched using an intelligent algorithm to obtain the coupling matrix model of the energy hub. A hydrodynamic laboratory consisting of electricity, natural gas, heating, and cooling energy is used as a case study to verify the reliability and accuracy of the modelling process and to provide standardized data for deep learning uses in the energy internet. The obtained results show that the proposed method can quickly and effectively estab-lish the energy hub model. This method is also effective when an energy storage device is added to or removed from the energy hub.

关键词： energy internet energy hub intelligent algorithm matrix model directed multigraph

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A hybrid approach of process reasoning and artificial intelligence-based intelligent decision system framework for fatigue life of belt grinding

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2024年第1-2期130卷 311-328页

作者： Zhang, Youdong Xiao, Guijian Ma, Ji Gao, Hui Zhu, Bao Huang, Yun Chongqing Univ Coll Mech & Vehicle Engn 174 Shazhengjie St Chongqing 400044 Peoples R China Chongqing Univ State Key Lab Mech Transmiss Adv Equipment 174 Shazhengjie St Chongqing 400044 Peoples R China Chongqing Midea Gen Refrigerat Equipment Co Ltd 15 Rose Rd Chongqing 400044 Peoples R China

Belt grinding is widely used as the final step in the fabrication of fatigue-resistant surfaces of nickel-based superalloy components, and fatigue life after grinding is one of the most concerning issues. However, the response mechanism of fatigue life under different grinding parameter excitation conditions is not well understood for a long time. In this study, a system framework of fatigue life prediction for nickel-based superalloy abrasive belt based on process reasoning and artificial intelligence algorithm is proposed. Based on the process reasoning method, the mathematical relationship between grinding parameters and fatigue life is established. The equation is solved by RNN and LSMT algorithms embedded in the system, and the excitation response model of process parameters to fatigue life is obtained. The results show that the prediction accuracy of the system is high. The mean squared error (MSE) of the LSTM algorithm is below 0.0441, and the R-squared can be above 0.9956. In addition, experimental verification has been carried out, the observation of the specimen section shows that the process parameters have an effect on the initiation position, distribution, and crack length of the fatigue crack source, which are related to the stress concentration and residual stress distribution at the depth of the grinding scratches. Furthermore, using Spring Boot framework, an intelligent decision-making system based on this system framework is developed by using java and python.

关键词： Belt grinding Fatigue life prediction intelligent algorithm Prediction system framework Software development

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Application of four intelligent models for the estimation of formation pressure of natural gas hydrate

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2024年 207卷 281-294页

作者： Song, Yi-Lun Guo, Ping Liu, Huang Sun, Bo-Wen Southwest Petr Univ State Key Lab Oil & Gas Reservoir Geol & Exploitat Rd 8 Chengdu 610500 Sichuan Peoples R China

Natural gas hydrate is a clean and efficient resource that contains lots of heat energy. The production, processing and transportation of natural gas can be influenced dramatically by natural gas hydrate. Natural gas hydrate will accumulate at the bottom of the pipeline, even block the pipeline and reduce the flow rate of the natural gas. This article presents four intelligent models named GWO-SVM (Grey Wolf Optimizer connected with Support Vector Machine), GWO-LSSVM (Grey Wolf Optimizer connected with Least Squares Support Vector Machine), GALSSVM (Genetic algorithm connected with Least Squares Support Vector Machine), and GWO-RBF (Grey Wolf Optimizer connected with Radial Basis Function) to predict the formation pressure of natural gas hydrate in different systems. In order to determine the degree of influence of each input variable on the formation pressure of natural gas hydrate, this paper uses Spearman correlation analysis method to calculate the correlation coefficients between the formation pressure of natural gas hydrate and various influencing factors. The contradistinction among different intelligent models shows that the GWO-LSSVM model has the exceptional performance of the smallest average absolute relative deviation (AARD=2.89%), the minimum standard deviation (SD=0.05) with all 244 data of natural gas hydrate formation pressure in different systems. When compared to six commonly used empirical models for predicting formation pressure in common natural gas hydrate, the GWO-LSSVM model has the highest prediction accuracy, with an AARD of only 1.82%. Furthermore, when compared to three thermodynamic models employed for predicting formation pressure in sour natural gas hydrate, the GWO-LSSVM model has the highest prediction accuracy, with an AARD of 2.38%. The leverage method demonstrates that four intelligent models have excellent robustness in reflecting the inner relationships among natural gas hydrate formation pressure and influential factors. The f

关键词： Gas hydrate Formation pressure intelligent algorithm

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intelligent model for speech recognition based on SVM: A case study on English language

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JOURNAL OF intelligent & FUZZY SYSTEMS 2021年第2期40卷 2721-2731页

作者： Hou, Qian Li, Cuijuan Kang, Min Zhao, Xin Shaanxi Univ Chinese Med Sch Foreign Languages Xianyang Shaanxi Peoples R China Betjing 263 Enterprise Commun Co Ltd Beijing Peoples R China Baidu Online Network Technol Beijing Co Ltd Beijing Peoples R China

English feature recognition has a certain influence on the development of English intelligent technology. In particular, the speech recognition technology has the problem of accuracy when performing English feature recognition. In order to improve the English feature recognition effect, this study takes the intelligent learning algorithm as the system algorithm and combines support vector machines to construct an English feature recognition system and uses linear classifiers and nonlinear classifiers to complete the relevant work of subjective recognition. Moreover, spectral subtraction is introduced in the front end of feature extraction, and the spectral amplitude of the noise-free signal is subtracted from the spectral amplitude of the noise to obtain the spectral amplitude of the pure signal. By taking advantage of the insensitivity of speech to the phase, the phase angle information before spectral subtraction is directly used to reconstruct the signal after spectral subtraction to obtain the denoised speech. In addition, this study uses a nonlinear power function that simulates the hearing characteristics of the human ear to extract the features of the denoised speech signal and combines the English features to expand the recognition. Finally, this study analyzes the performance of the algorithm proposed in this study through comparative experiments. The research results show that the algorithm in this paper has a certain effect.

关键词： SVM intelligent algorithm English features feature recognition

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