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Motion Optimization of a Six-Degree-of-Freedom Robotic Arm Based on Denavit-Hartenberg Parameter Method and NSGA-II 2

Motion Optimization of a Six-Degree-of-Freedom Robotic Arm B...

引用

2nd IEEE international conference on Electrical, automation and computer engineering, ICEACE 2024

作者： Wang, Zichong Jin, Ziyang China Agricultural University College of Information and Electrical Engineering Beijing China

ISBN: (纸本)9798350368208

This paper presents an optimization approach for the motion of a six-degree-of-freedom robotic arm based on the Denavit-Hartenberg (D-H) parameter method and NSGA-II. The forward kinematic model of the robotic arm is established using the D-H parameter method, and the minimization of end-effector error is formulated as a nonlinear optimization problem. An adaptive gradient descent algorithm is employed, integrating momentum terms and adaptive learning rates to enhance convergence speed and stability. The algorithm incorporates multiple random initialization strategies to avoid local optima. The optimized joint configurations result in precise end-effector positioning, with a minimal end-effector error of 2.1819 × 10-5 mm. Furthermore, an energy minimization objective is introduced, leading to the development of a multi-objective optimization model. This model accounts for the kinetic and potential energy changes resulting from joint rotations, integrating energy consumption into the optimization framework. The NSGA-II algorithm is utilized for solving the multi-objective optimization problem, incorporating adaptive crossover and mutation operations to improve search efficiency. The results demonstrate a trade-off relationship between end-effector error and energy consumption. © 2024 IEEE.

关键词： End effectors

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Optimal design of urban drainage system based on GIS and machine learning 2

Optimal design of urban drainage system based on GIS and mac...

引用

2nd IEEE international conference on Electrical, automation and computer engineering, ICEACE 2024

作者： Meng, Di Zhang, Yunfeng East University of Heilongjiang College of Civil Engineering and Architecture Harbin150000 China Harbin Water Development and Construction Group Emergency Rescue and Non-Excavation Technology Application Center in Cold Regions Harbin150000 China

ISBN: (纸本)9798350368208

How to optimize multi-objective drainage efficiently and accurately is a key problem in urban drainage. In response to this problem, in this paper, a novel method combining geographic information System (GIS), Random Forest Regression (RFR) and Multi-Objective Optimization is proposed. Multi-Objective Forest Regression (MOFR) method provides detailed spatial data and terrain information through GIS, and RFR realizes high-precision prediction of urban drainage system performance, and uses MOO for multi-objective optimization, so as to ensure high prediction accuracy and improve the comprehensive performance of the system. Ultimately, experimental results, obtained through comparative experiments and analysis with traditional machine learning methods, demonstrate that the MOFR method exhibits notable advantages in enhancing prediction accuracy, minimizing function errors, and optimizing water quantity testing. Especially in complex multi-objective optimization scenarios, MOFR method can more accurately find the optimal design scheme and reduce the uncertainty in the decision-making process. This fully verifies the reliability and effectiveness of the architecture in urban drainage system optimization design. © 2024 IEEE.

关键词： Adversarial machine learning

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Optimization study of stacker cranes path in logistics distribution center 2

Optimization study of stacker cranes path in logistics distr...

引用

2nd IEEE international conference on Electrical, automation and computer engineering, ICEACE 2024

作者： Yang, Hai Tang, Qi Wang, Jinbing Zhang, Lei Li, Zhaoqing Liu, Hui Guizhou University School of Mechanical Engineering Guiyang China Guizhou Tobacco Company Guiyang Company Guiyang China

ISBN: (纸本)9798350368208

In order to improve the efficiency of stacker cranes in automated three-dimensional warehouses, an improved simulated annealing algorithm is investigated to optimize the path of stacker cranes. First, a mathematical model with the objective of the shortest access time is established, and the constraint of the maximum loading capacity of the stacker cranes is added. Then, on the basis of simulated annealing algorithm (SA), a genetic algorithm (GA) with strong global search ability is introduced into the simulated annealing algorithm to expand the search range of the solution, and a hybrid simulated annealing genetic algorithm (SAGA) is obtained. Finally, the simulated annealing genetic algorithm is simulated using Matlab in combination with practical application case studies. Through experimental calculations, when using the hybrid genetic algorithm to control the stacker cranes to access the goods, the travel distance of the stacker cranes is better than when using the simulated annealing algorithm, which reduces the time by 13.06% compared with the simulated annealing algorithm, and effectively improves the efficiency of the goods out of the warehouse. © 2024 IEEE.

关键词： Simulated annealing

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Research on Planting Strategies Based on K-Means Cluster Analysis and Spearman Correlation Analysis 2

Research on Planting Strategies Based on K-Means Cluster Ana...

引用

2nd IEEE international conference on Electrical, automation and computer engineering, ICEACE 2024

作者： Wang, Zhuojin Harbin Engineering University Harbin China

ISBN: (纸本)9798350368208

K-Means clustering is a commonly used iterative clustering algorithm in machine learning that categorizes many samples into clusters with the same attributes based on similarities between the samples. At the same time, Spearman correlation analysis is used to characterize possible correlations between different factors. To deepen the combined application of these two methods, this paper combines K-Means cluster analysis and Spearman correlation analysis and applies them to the optimization of planting strategies. Firstly, this paper considers various practical constraints in the planting process and formulates a planning model with the objective of maximizing the total return. Then, through K-Means clustering analysis, crops are divided into clusters with different traits, and Spearman correlation analysis is used to introduce the substitution and complementary relationship between different clusters, so as to construct a planting strategy planning model that better meets the market demand. The model not only has strong practicality, but also provides scientific planting strategies for decision makers. In addition, this paper adopts a combination of multiple machine learning algorithms, which provides a valuable reference for the integration and application of the model. Through this research, we provide new perspectives and tools for agricultural decision-making and promote scientific and rational planting strategies. © 2024 IEEE.

关键词： Cluster analysis

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Simulation Optimization of Tobacco Sorting System Based on Genetic Simulated Annealing Algorithm 2

Simulation Optimization of Tobacco Sorting System Based on G...

引用

2nd IEEE international conference on Electrical, automation and computer engineering, ICEACE 2024

作者： Yang, Yang Wang, Jinbing Wu, Zaiquan Luo, Mingyang Wei, Li Li, Zhaoqing Guiyang Company Guizhou Tobacco Company Guiyang China Guizhou University School of Mechanical Engineering Guiyang China

ISBN: (纸本)9798350368208

The sorting system is the core of the tobacco logistics distribution center, the current distribution center cigarette sorting volume is large, and different order sorting orders have a greater impact on the total processing time of the order, to improve the sorting efficiency of the tobacco logistics distribution center, the establishment of a mathematical model to minimize the total time of the delay of the order as the objective function, the use of improved adaptive genetic annealing algorithm for the solution, and the use of Plant Simulation software to establish a simulation model of the sorting system, the results of the solution in Plant Simulation software simulation verification, it is verified that the use of the algorithm for order sorting, compared with the traditional sequential sorting, effectively reduces the total processing time of the order sorting, and improves the sorting efficiency of the tobacco logistics and distribution center. © 2024 IEEE.

关键词： Simulated annealing

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Optimal Configuration of Waste Heat Boiler and Generator in Smeltery Based on Rankin Cycle 2

Optimal Configuration of Waste Heat Boiler and Generator in ...

引用

2nd IEEE international conference on Electrical, automation and computer engineering, ICEACE 2024

作者： Xiao, Yang Yanjiang, Li Tao, Zhang Bgrimm Technology Group Engineering Company Beijing China

ISBN: (纸本)9798350368208

Construction of waste heat boiler to recover the waste heat of high temperature flue gas, with the generated saturated steam going into the waste heat generator set to produce electrical power, is a feasible scheme to realize the efficient utilization of energy. In order to comprehensively evaluate the waste heat boiler and waste heat generator set of different smelting plants, and consider the generated power and income that can be recovered by the equipment investment, a configuration model of waste heat boiler and waste heat generator set based on Rankin cycle is presented. From the practical point of view of protecting turbine blades from water erosion, an optimization model based on Rankin cycle with the aim of maximum humidity and minimum dryness of steam and water mixture is constructed to correct the actual internal efficiency and power generation of steam turbine. The optimal configuration model of waste heat boiler and waste heat generator set for steam dehumidification was established, by drawing out some initial steam to dehumidify the final stage steam in the turbine. Finally, a waste heat boiler and waste heat generator set of a smelting plant in Zambia are taken as simulation examples, and the rationality and effectiveness of the proposed model are verified by EBSILON simulation. © 2024 IEEE.

关键词： Steam

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computer Aided engineering System of Amorphous Transformers based on Digital Twin Technology

Computer Aided Engineering System of Amorphous Transformers ...

引用

2023 international Russian automation conference, RusAutoCon 2023

作者： Stulov, Alexey Tikhonov, Andrey Karzhevin, Andrey Ivanovo State Power Engineering University Department of Electrical Engineering Ivanovo Russia

ISBN: (纸本)9798350345551

Current trends in the development of the electrical industry are characterized by a constant complication of the design of products and, accordingly, increased requirements for the accuracy and speed of research and development work. The use of digital twin technologies in power and distribution transformer computer aided engineering analysis systems (CAE) is the most effective tool for obtaining the right technical solution. Nowadays modern systems of engineering analysis are based digital twin technologies. Distribution transformers are main objects in the electrical network. Reliability and safety of operation of transformers directly depends on the technical solutions adopted in the process of designing and engineering analysis of equipment. The use of digital twin technology makes it possible to design transformers with high precision. Thus, the problem of development CAE analysis system of amorphous transformers based on digital twin technology is relevant. © 2023 IEEE.

关键词： Reliability analysis

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Evaluating importance of AI in Robotics and automation in Healthcare for Different age Groups 1

Evaluating importance of AI in Robotics and Automation in He...

引用

1st international conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Abu Eid, Aws Ismail Pethkar, Rajendra Huda, Bintul Patil, Jaykar Bhaskar Gatla, Ranjith Kumar Kumbhar, Ramchandra Arab Open University Faculty of Computing Studies Amman Jordan Jaywant College of Engineering and Polytechnic Department of Mechanical Engineering Karad India Sharda University Department of Computer Science & Technology Srinagar India Jaywant Institute of Management Karad India Institute of Aeronautical Engineering Department of Electrical and Electronics Engineering Hyderabad India Department of Radio-Diagnosis Karad India

ISBN: (纸本)9798350360707

Nowadays robotics is mostly used in the world. There are many industries which used robots for reducing time and to have high precision of work. The use of artificial intelligence is now increasing which helps in automations and processing of machines. Thus, the focus of study is to find the different applications of automation of robotics (i.e. robotic process automation) in the field of healthcare and its impact on the employment of medical field. Four major categories can be used to group AI applications in healthcare: expressive, analytical, prognostic, and prescriptive. The only way to close the skills gap in the healthcare industry is to increase the application of artificial intelligence. Hospitals are developing mental commit robots to treat their patients. Through physical contact, these robots can have an impact on humans' psyche, physiology, and social interactions. Thus, in coming time most of the healthcare industry will be with the robots which will reduces the human interventions with the patients through one of the host servers. © 2024 IEEE.

关键词： Medical robotics

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Leveraging Smart Contracts for Automated Counterfeit Prevention in E-Commerce 2

Leveraging Smart Contracts for Automated Counterfeit Prevent...

引用

2nd IEEE international conference on IoT, Communication and automation Technology, ICICAT 2024

作者： Laxmaiah, Bagam Subburam, S. Al-Fatlawy, Ramy Riad Sravanthi, Jajimoggala Sharma, Himanshu Rajaram, Gnanajeyaraman Department of CSE CMR Technical Campus Telangana Hyderabad India New Prince Shri Bhavani College of Engineering and Technology Department of IT Tamil Nadu Chennai600073 India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq GRIET Bachupally Department of CSE Telangana Hyderabad India GLA University Department of Computer Engineering & Applications Mathura India Saveetha Institute of Medical and Technical Sciences SIMATS Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350368109

This research's abstract highlights the use of intelligent contracts for the automation of counterfeit prevention in online retailing. The manuscript shows a considerable decrease in the number of counterfeit events and identification time, including the integration of machine learning nacle models with blockchain smart contracts. The analyses presented points out that the use of ML models in detecting fake goods based on their characteristics enhances the ability of counterfeit reduction since the models demonstrate high accuracy in their performance. Besides, with the help of smart contracts, actual operations can be monitored and checked in real-time to learn whether they adhere to the rules they are supposed to or not. However, as the results indicate, several challenges, including the compliance with regulations and the issue of interoperability, must be solved to push for the wider adoption of smart contracts in e-commerce environments. As it follows, further research should pay attention to optimizing smart contract management, work on an increased system's capacity, and counter present novel risks represented in counterfeiting. Thus, preparing for further research, it is also possible to emphasize the fact that the use of smart contracts will lead to the creation of a more trusting atmosphere in e-commerce for both consumers and businesses due to increased trust, transparency, and security of online transactions. © 2024 IEEE.

关键词： Smart contract

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Research on automation of Standard Document Classification and Information Extraction Supported by Knowledge Graphs 4

Research on Automation of Standard Document Classification a...

引用

4th international conference on Electronic Information engineering and computer Communication, EIECC 2024

作者： Wang, Zewen Zhang, Hongqi The 38th Research Institute China Electronics Technology Group Corporation Anhui Hefei230031 China

ISBN: (纸本)9798331534622

The classification and information extraction of standard documents is a critical topic in the field of knowledge management. This study designs and implements an intelligent processing system for standard documents supported by knowledge graphs. The system employs a layered architecture and an improved deep learning model, utilizing knowledge graphs for dynamic updates of domain knowledge. The system significantly outperforms traditional methods in document classification accuracy and information extraction efficiency. Deployed using a microservice architecture, the system demonstrates excellent scalability and stability, providing an effective technical solution for intelligent management of standard documents. © 2024 IEEE.

关键词： Knowledge graph

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