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Research on Electric Vehicle Charging Station Planning based on Genetic Algorithm and Particle Swarm Optimization Algorithm (GAIPSO) 9

Research on Electric Vehicle Charging Station Planning based...

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9th international conference on big data and Information Analytics, bigDIA 2023

作者： Zhou, Yilong Tan, Suoyi Ou, Chaomin National University of Defense Technology College of Systems Engineering Changsha China

ISBN: (纸本)9798350330076

thanks to the advancement of the electric vehicles (EVs) technology, the demand on electric vehicles is on a hideous rise. So follows the demand on corresponding charging stations (CSs) and its facilities. Several countries have witness the rapid growth in the adoption of EVs after they issued incentive policies. However, the current EV charging network cannot shoulder the demand once a considerable number of vehicles in the world migrate to EVs and continuous efforts are still required for the transition. the leading company, Tesla, is setting the benchmark for the industry and on track to help the US to fulfil its switchover to all-electric as the company released its secret patent for superchargers. this strategy not only turns out to be money-saving for Tesla, but also spurs the construction of the charging facilities worldwide. Particularly for city-planners, the architecture of the CS network is in a dire need and that is the focus of this paper. We are supposed to determine the amount and allocation of the CSs and design the charging network for a district or a country. Meanwhile, we shall sort out the construction scheme for the following several years' time. We would henceforth analyse the construction need for the USA and South Korea using our model and sort out the growth plan and the timeline. We would also talk about the external factors that would influence our decision and bring a classification system. © 2023 IEEE.

关键词： Particle swarm optimization (PSO)

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An automated storage and retrieval system optimization with MILP methods 5

An automated storage and retrieval system optimization with ...

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Chen, Yixin Fan, Boning Li, Jiaming Lin, Jianfeng Lin, Mengmeng School of Automotive and Transportation Engineering Hefei University of Technology Anhui Hefei230009 China Xuteli School Beijing Institute of Technology Beijing100081 China School of Automation Southeast University Jiangsu Nanjing211100 China School of Power and Mechanical Engineering Wuhan University Wuhan430072 China College of Engineering Northeast Agricultural University Heilongjiang Harbin150030 China

ISBN: (纸本)9781510662520

In this paper, we consider the problem of scheduling an automatic guided vehicle (AGV) in an automated storage and retrieval system (AS/RS). In this system, the AGV acts as a transfer station and performs the task of depositing and taking out goods. It is assumed that the number and location of shelves are known, as well as the number and type of goods on each shelf. the AGV performs transport tasks with decisions that include finding the optimal transport sequence between different shelves and the optimal sequence of goods within each shelf. therefore, these decisions jointly minimize the total transport distance. Using mixed-integer linear programming (MILP), the AGV can not only complete the task with the shortest working route but also return to the sorting station with the shortest path after completing the task. Using MATLAB software to simulate the two cases, the results of obtaining the optimal solution verified the correctness of the algorithm. the results show that the algorithm has high performance for optimizing AS/RSs. © 2023 SPIE.

关键词： Automatic guided vehicles

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Application of Computer Aided 5G technology in Wireless Intelligent Network Communication System 4

Application of Computer Aided 5G Technology in Wireless Inte...

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4th IEEE Annual Flagship India Council international Subsections conference, INDISCON 2023

作者： Xu, Yunwu Li, Yan College of Guangdong Songshan Polytechnic Electrical Engineering Guangdong Shaoguan China

ISBN: (纸本)9798350333558

the application of computer-aided 5G technology in wireless intelligent network communication systems has completely changed our communication methods. 5G technology is the fifth generation mobile network, providing faster network speed, lower latency, and higher capacity. this technology has been integrated into wireless intelligent network communication systems to enhance communication between devices. the use of 5G technology in wireless intelligent network communication systems enables faster and more efficient data transmission, which is crucial for real-time applications such as video conferencing, online games and autonomous vehicle. In addition, this technology improves the reliability of wireless networks by reducing interference and increasing coverage. In addition, computer-aided 5G technology makes it possible to develop new applications that were previously impossible to implement due to connection limitations. For example, remote surgery can now be performed using augmented reality technology that requires high-speed internet connectivity. In summary, the application of computer-aided 5G technology in wireless intelligent network communication systems has changed our communication methods by providing faster network speeds, lower latency, higher capacity, and new applications. therefore, this technology will continue to shape our future by strengthening the connections between various industries. © 2023 IEEE.

关键词： Online systems

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A Statistical Method-Based Auto-Fitted Genetic Algorithm for Damage Diagnosis 5th

A Statistical Method-Based Auto-Fitted Genetic Algorithm for...

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5th international conference on Innovative Product Design and Intelligent Manufacturing Systems, ICIPDIMS 2023

作者： Sahu, Sasmita Das, Monalisa Jena, Shakti P. Sahu, Rita Kumari Nayak, Bijaya Bijeta Parhi, Dayal R. School of Mechanical Engineering Kalinga Institute of Industrial Technology Deemed to Be University Odisha Bhubaneswar751024 India Nalanda Institute of Technology Odisha Bhubaneswar754005 India Department of Mechanical Engineering National Institute of Technology Odisha Rourkela769008 India

ISBN: (纸本)9789819767311

From the last two decades, lots of research have been done on the non-destructive testing (NDT) and structural health monitoring (SHM) techniques. though the conventional NDT methods are effective, the complete reliability on them is not possible due to the countable time period. For all the catastrophic failure, time plays an important role. If appropriate time of structural and mechanical failure will not be estimated, it will be disastrous. So, in this paper, method describing on online technique has been proposed. An evolutionary algorithm has been used to generate an online method to identify and detect the damage. In the application of any evolutionary algorithm, large numbers of data are required. It has been observed that during the collection of data, error is accumulated. Error needs to be reduced. So, to minimize the error amount during the data collection, the relation between dependent variables and independent variables has been figured out. In this work, the result from the genetic algorithm (GA) and the auto-fitted GA has been compared. From the comparison, it can be clearly noticed that the results from the auto-fitted GA are more convergent and the percentage of error is less. the novelty of this study is the application of hierarchical GA with the statistical bootstrap method for damage detection and its severity measurement. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Errors

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Enhancing Tomato Cultivation for Quality Yield and Demand Fulfillment 5

Enhancing Tomato Cultivation for Quality Yield and Demand Fu...

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5th international conference on Advancements in Computing, ICAC 2023

作者： Kavinda, W.W.H. Imalsha, R.C. Athapaththu, A.H.M.C.P. Edirisinghe, S.A. Kasthuriarachchi, Sanvitha Pabasara, Chamali Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798350358131

Tomato farming is critical to meeting the growing demand for high-quality tomato products. With a growing population and shifting dietary tastes, there is an increased demand for sustainable and efficient farming practices that can ensure the production of premium-quality tomatoes. this study article provides a comprehensive strategy for optimizing tomato growing, from the farming process to the final product, to fulfil the ever-expanding market demands. Damage caused by nutrient deficiencies, damage caused by various insects, damage caused by various diseases affecting the crop and damage caused by wild animals can be mentioned as the reasons for reducing the optimum yield of tomato cultivation. the main objective of this research is to reduce the damage caused to tomato cultivationdue to these reasons. For this, models have been trained with the help of machine learning, algorithms, and image processing. the final product is a user-friendly mobile application. through this mobile application, the user can get information about the nutritional deficiency, whether the insectthat has come to the plantation is harmful to the plantation or not, and what the disease is, by uploading an image of the relevant part of the plant showing signs of suspected nutritional deficiency, uploading images of insects coming to the plantation, uploading an image of the diseased part of the plant if a disease has developed. the results of this research demonstrate the successful development of a user-friendly mobile application that utilizes machine learning, algorithms, and image processing to provide information about nutrient deficiencies, harmful insects, and diseases affecting tomato plants, thereby reducing damage to tomato cultivation. © 2023 IEEE.

关键词： Machine learning

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Domain Adaptation Using Generative Adversarial Networks for Medical Image Synthesis 5th

Domain Adaptation Using Generative Adversarial Networks for ...

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5th international conference on data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Ganesh, D. Verma, Upendra K. Patil, Smita Alam, Intekhab Karnataka Bangalore India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India 3School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Latest advancements in state-of-the-art scientific photograph evaluation depend heavily on the availability of large new datasets of cutting-edge annotated scientific photographs for version training. Unfortunately, obtaining massive samples of cutting-edge categorized scientific picas is ultra-modern high-priced, or impossible. Area edition is a way to generalize a version educated on a selected dataset to a brand new area, wherein the model turned into not directly educated. Generative adverse Networks (GANs) were used to generate realistic artificial photographs. It has enabled the opportunity present day the usage of GANs to bridge the domain hole via generating artificial medical photos, which could then be used for education fashions. On this paper;we evaluate the latest progress in making use of area edition the use of GANs for scientific photosynthesis, with an emphasis on applications including pathology, scientific imaging, and optical acceptable imaging. We talk about the benefits of ultra-modern using GANs for area adaptation and present processes for each present day of the above programs. We also speak about various challenges and future directions in this field. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Generative adversarial networks

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Development of an Integrated Off-Grid Audio and Haptic Wearable Vest for Visually Impaired Navigation 5

Development of an Integrated Off-Grid Audio and Haptic Weara...

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5th international conference on Biomedical engineering, IBIOMED 2024

作者： Pimentel, Angelino A. Huang, Ji-Jer Ventura, Carlamae Nicole D. Laygo, Alyssa Jean M. Sagabaen, Teofilo M. Reyes, Rojan I. See, Aaron R. Baldovino, Renann G. Southern Taiwan University of Science and Technology Electrical Eng'g Dept. Tainan City Taiwan Saint Mary's University Nueva Vizcaya Philippines Saint Mary's University Electronics Eng'g Dept Nueva Vizcaya Philippines National Chin-Yi University of Technology Electronics Eng'g Dept. Taichung City Taiwan De La Salle University Mgf Eng'g & Mgmt Dept. Manila Philippines

ISBN: (纸本)9798350389265

Visual impairments afflict millions globally, significantly impacting mobility and quality of life (QoL) for approximately 253 million individuals, including 36 million who are blind. their most used tools for navigation were guide dogs and white canes;however, their effectiveness is limited by their speed, coverage, and capabilities. Additionally, related systems where internet connectivity-dependent (on-grid). With that, this study proposed an integrated system development of an off-grid audio-haptic wearable vest for visually impaired navigation. Specifically, the study will develop a personalized audio and haptic wearable navigation system tailored for the blind and visually impaired individuals, develop a prototype with IoT capabilities, and assess the system's accuracy by determining the distance and direction for wearable navigation through audio-haptic feedback. Processing GY-273 magnetometer data for bearing and NRF52810 BLE scanning for distance, were completed considering both unobstructed and obstructed real-world scenarios within the school campus. Results showed that system was capable of auditory directional notification such as 'turn left', 'turn right' and 'destination address' simultaneously with haptic feedback thru vibrations. Also, using the nonparametric Mann-Whitney U test, for obstructed (real-life) distances, the accuracy ranged is up to 91.43%. While unobstructed distances accuracy was up to 100%. Obstructed (real-life) bearing accuracy from up to 100%, while unobstructed bearing accuracy was also up to 100%. Indicating that there is slight difference between the expected and actual values for distance while bearing measurements prove no difference enabling the seamless integration of haptic and aural commands to improve navigation support for individuals with visual impairments. © 2024 IEEE.

关键词： Assistive technology

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Weld defect recognition method based on improved DenseNet 5

Weld defect recognition method based on improved DenseNet

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Li, Huadu Luo, Renze Tang, Xiang Wu, Yong Li, Yalong Faculty of Electrical Information Southwest Petroleum University Sichuan Chengdu610500 China Faculty of Science and Technology Southwest Petroleum University Sichuan Chengdu610500 China Sichuan Jiacheng Oil and Gas Pipeline Quality Inspection Ltd Sichuan Chengdu610000 China

ISBN: (纸本)9781510662520

there are many subjective influencing factors, poor recognition effect and low efficiency in manual evaluation of pipeline weld defects. An intelligent identification method of pipeline weld defects based on improved DenseNet network is proposed. this method firstly uses the form of multi-channel convolution of different scales to improve the DenseNet network, thereby improving the generalization ability of the network;then, the feature extraction ability of the network is improved by stacking two convolutions of the same scale;Finally, an attention mechanism module is introduced into the dense connection block of the network to achieve the effect of improving beneficial features and suppressing useless features. the experimental results show that the method can achieve 92% accuracy in the identification of pipeline weld defects, which is about 13% higher than the original method, and has high efficiency, which can fully achieve the purpose of industrial application. © 2023 SPIE.

关键词： Convolution

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Quantum Multi-Agent Reinforcement Learning as an Emerging AI technology: A Survey and Future Directions 5

Quantum Multi-Agent Reinforcement Learning as an Emerging AI...

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5th international conference on Computer and Applications, ICCA 2023

作者： Yu, Wenhan Zhao, Jun Nanyang Technological University Gradute College Singapore Nanyang Technological University School of Computer Science and Engineering Singapore

ISBN: (纸本)9798350303254

this paper surveys Quantum Multi-Agent Reinforcement Learning (QMARL), an emerging fusion of quantum computing and multi-agent systems. It begins by introducing the transformative potential of quantum computing in computational capabilities. Examining the principles of multi-agent reinforcement learning (MARL), the paper explores how quantum computing enhances learning efficiency and decision-making. Focusing on the current state of QMARL, it reviews literature, methodologies, and case studies showcasing the integration of quantum algorithms with MARL frameworks. the survey addresses challenges and opportunities arising from quantum technologies in multi-agent systems, such as entanglement and superposition, exploring their implications for agent coordination and learning dynamics. Practical applications in domains like cybersecurity and finance underscore QMARL's transformative potential. Concluding, the paper identifies research gaps and proposes future directions, emphasizing the need for scalable quantum algorithms, exploring quantum-resistant strategies in adversarial settings, and integrating quantum principles in agent communication and collaboration. this concise survey serves as a foundational guide for researchers and practitioners, offering insights into the current state and future possibilities of QMARL. © 2023 IEEE.

关键词： Multi agent systems

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Implementing a land registration system using non-fungible tokens to represent land in the system and side-chain for data storage 5

Implementing a land registration system using non-fungible t...

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5th international conference on Control, Communication and Computing, ICCC 2023

作者： Kunjumon, Cyril Mutharia, Aditya Shareef, Salemula Suchithra, M.S. Indian Institute of Information Technology Department of Computer Science and Engineering Kottayam India

ISBN: (纸本)9798350334128

Blockchain technology has been increasing in popularity in recent times due to its decentralized nature, immutability, transparency, high security and transparency. Several private and public organisations have been using it to develop new and innovative projects like cryptocurrency, NFTs, Metaverse, etc., and also to upgrade and improve old technologies like supply chains in agriculture and government voting systems. Land Registration is one such sector that can be upgraded using blockchain because in the current system there are a lot of middlemen involved and data is centralized and not secure, these things make the current system vulnerable to frauds and corruption. In this paper we have proposed a new implementation for the existing land registration system in the country that uses Non-Fungible tokens in the blockchain to represent a property and a sidechain like IPFS for storing its data in a decentralized manner. With our implementation we can overcome the flaws in the old system and make land registration secure, transparent and trustless. Here by "trustless"we mean that users do not have to trust any centralized authority or intermediary to verify transactions or maintain the integrity of the system. Instead, trust is placed in the system's consensus mechanism and cryptographic protocols. © 2023 IEEE.

关键词： Smart contract

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