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检索条件"任意字段=4th Conference on Learning and Intelligent Optimization"

共 11649 条记录，以下是761-770 订阅

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Substation Digital Patrol Route optimization Based on Differential Evolution Particle Swarm optimization 4

Substation Digital Patrol Route Optimization Based on Differ...

引用

4th International conference on Mechatronics Technology and intelligent Manufacturing, ICMTIM 2023

作者： Wu, Jianbin Xue, Lei Zheng, Yuming Zhang, Jingyu Li, Qiang State Grid Shanxi Electric Power Company Taiyuan030000 China Economic and Technical Research Institute of State Grid Shanxi Electric Power Company Taiyuan030000 China

ISBN: (纸本)9798350314434

With the continuous progress of digitization in the power industry, the construction of a digital patrol system has become one of the keys of digital production. Traditional patrol algorithm has low accuracy of patrol route, global path planning and local path planning cannot be unified, and patrol path is affected by important parameters. To overcome these shortcomings, an improved particle swarm optimization algorithm based on differential evolution is presented in this paper. It has the advantages of searching ability and a strong iteration effect, and after several iterations, it integrates the local path with global path, and the shortest distance is greatly reduced. © 2023 IEEE.

关键词： Iterative methods

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A Visual Communication optimization Method for Human-Computer Interaction Interfaces Using Fuzzy Logic and Wavelet Transform 4

A Visual Communication Optimization Method for Human-Compute...

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4th International conference on Communication Technology and Information Technology, ICCTIT 2024

作者： Sun, Qi Carnegie Mellon University PittsburghPA United States

ISBN: (纸本)9798331528973

this paper proposes a visual communication optimization method for human-computer interaction interfaces based on fuzzy logic and wavelet transform, aiming to solve the problems of blurred information, unclear edge details, and noise interference in interface visual communication. First, fuzzy logic is used to quantify fuzzy areas and uncertain information in the image, and fuzzy clustering methods are used to achieve precise positioning and feature enhancement of key areas;then, wavelet transform is used to decompose the image into multiple scales to effectively separate low-frequency areas. the overall structural information and edge detail features of high-frequency areas highlight key visual elements in the interface. the optimized human-computer interaction interface has clearer edge contours, effectively suppressed noise, and more accurate expression of visual information. In the experimental part, edge detection, noise suppression evaluation, multi-scale visual detail retention, and user satisfaction comparison experiments were conducted. the results show that after fuzzy logic and wavelet transform processing, the peak signal-to-noise ratio (PSNR) of the interface image is significantly improved, the edge clarity is significantly improved at different scales, and the user satisfaction level is 'satisfied' and 'very satisfied' the rating ratio has increased significantly. this method shows superiority in terms of visual communication quality, information accuracy, and user experience, and has strong practicability and stability. In the future, this method can be further combined with deep learning, personalized recommendations and virtual reality technology to promote the intelligent and efficient development of humancomputer interaction interfaces in more fields. © 2024 IEEE.

关键词： Computer circuits

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ML for Sustainable Solutions: Applications in Renewable Energy optimization and Climate Change Prediction 4

ML for Sustainable Solutions: Applications in Renewable Ener...

引用

4th International conference on Sentiment Analysis and Deep learning, ICSADL 2025

作者： Awachat, Arya Dube, Ananya Chaudhri, Shivnath Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha442001 India Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Wardha442001 India

ISBN: (纸本)9798331523923

this paper delves into the transformative potential of ML in addressing some of the world's most pressing challenges in optimizing renewable energy and mitigating climate change. How ML algorithms work to improve efficiency within solar and wind energy systems, smart grids, and energy storage technologies is revealed by large data sets and predictive analytics. As ML improves the forecasting of energy, minimizes waste, and allows for better grid integration, its contribution to cutting carbon emissions significantly is immense. In addition, it facilitates climate adaptation by accurately predicting extreme weather occurrences and climate variability. Challenges facing the approach include data paucity, computational cost, and integration with older systems. Interdisciplinary collaboration and newer ML models tackle these challenges well. the study recognizes the significant role of machine learning in creating a sustainable environment and notes its ability to actually reconcile environmental, economic, and social objectives toward a robust and greener future. © 2025 IEEE.

关键词： Clean energy

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ACP-based Parallel Multi-Sensor optimization Configuration System for intelligent Vehicles 4

ACP-based Parallel Multi-Sensor Optimization Configuration S...

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4th IEEE International conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Zhou, Min Li, Mengyu Chen, Qifang Song, Haifeng Dong, Hairong Beijing Jiaotong University School of Automation and Intelligence Beijing100044 China Beijing Jiaotong University School of Electrical Engineering Beijing100044 China Beihang University School of Electronic Information Engineering Beijing100191 China

ISBN: (纸本)9798350349252

Perception technology plays a significant role in ensuring driving safety and other aspects. However, achieving the optimal configuration of multi-source sensors is a complex problem when designing an intelligent vehicle perception system. In this paper, the ACP method (artificial system, computational experiments, and parallel execution) is introduced to address the problem of optimally configuring multi-source sensors in intelligent vehicles. Firstly, an artificial system is constructed to simulate the effects of different scenarios on the performance of sensing sensors. Secondly, the configuration method for different sensing sensors, under the condition of maximum coverage of the sensing area, is determined through computational experiments. this includes determining the number of installations, positions, and directions. Finally, dynamic optimization of the configuration scheme is achieved through parallel execution, resulting in an optimal configuration scheme of multi-source sensors for intelligent vehicles that meets the requirements of different scenarios. Additionally, this paper generates a multi-sensor configuration scheme through computational experiments based on a hypothetical car model. the effectiveness of the parallel optimal configuration method proposed in this paper is verified by evaluating the coverage of the perception area under various scenarios. © 2024 IEEE.

关键词： Model automobiles

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Research on optimization of Selective Maintenance Decisions of Metro Tracks 4

Research on Optimization of Selective Maintenance Decisions ...

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4th International conference on Electrical Engineering and Mechatronics Technology, ICEEMT 2024

作者： Xiao, Zhiqun Liu, Yu Lei, Chong Li, Qiuyi Qian, Xinbo Jiang, Xuepeng China Railway Siyuan Survey and Design Group Co. LTD Wuhan China Wuhan University of Science and Technology Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan China Wuhan University of Science and Technology School of Resources and Environment Engineering Wuhan430081 China

ISBN: (纸本)9798350356472

To conduct research on selective maintenance decision optimization for the metro rail system, a selective maintenance decision optimization model is established. this model considers non-maintenance, incomplete maintenance, and replacement maintenance as possible maintenance behaviors. Constrained by a given sky-light time and other maintenance resources, the model is formulated to optimize equipment reliability of the metro rail system. the optimal selective maintenance scheme is obtained by solving the model using genetic algorithm. through case analysis and comparison results, the selective maintenance decision optimization model for metro track can provide the most reasonable maintenance decisions under limited maintenance resources. the model offers theoretical support and decision support for intelligent maintenance of the metro rail system. © 2024 IEEE.

关键词： Subways

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Deadline and Cost optimization based Task Scheduling (DCOTS) in Cloud Computing Environment 4

Deadline and Cost Optimization based Task Scheduling (DCOTS)...

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4th International conference on intelligent Engineering and Management, ICIEM 2023

作者： Grewal, Sanjiv Kumar Mangla, Neeraj Department of CSE Mullana Ambala India

ISBN: (纸本)9798350341126

Deadline and cost optimization are the important issues in cloud computing environment. Lack of these two factors discourages the cloud users from using the services of clouds. the proposed task scheduling considers fulfilling user's requirements with in time and budget constraints. Cloud users always try to maximize their profit and finish the task or job within a predetermined time. thus, proposed Deadline and Cost optimization based Task Scheduling (DCOTS) guarantees to satisfy user's need and try to maximize the profit of cloud providers. Proposed approach measures the QoS parameters i.e make span, load balancing, response time, throughput etc of cloud resources and these parameters are also associated with deadline and cost. the effectiveness of proposed scheduling algorithm is compared with existing cost and time based scheduling algorithm. © 2023 IEEE.

关键词： Scheduling algorithms

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Trade-offs in Performance and optimization Techniques in Unity 3D to Achieve Realism 4

Trade-offs in Performance and Optimization Techniques in Uni...

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4th International Mobile, intelligent, and Ubiquitous Computing conference

作者： Osman, Shand Hussein, Omar Younes, Ibrahim Elsayed, Shaheer El Bendary, Seif Hesham, Mirna Hassan, Yomna M., I Univ Canada Egypt Fac Math & Computat Sci UPEI Cairo Branch Cairo Egypt

ISBN: (纸本)9798350367782;9798350367775

As games grow in complexity, their performance drops. this creates the challenge of optimizing performance without sacrificing quality. A challenge many developers face. this paper explores the optimization techniques in Unity, a game engine widely used in the gaming and film industries. Addressing the challenges of balancing performance, complexity, and quality, developers utilize optimization techniques like Static Batching, GPU Instancing, Occlusion Culling, Mesh optimization, and Light Baking, each with different trade-offs. this paper analyzes the impact of each of these techniques on hardware performance, focusing on Static Batching's reduction in draw calls, GPU Instancing's ability to offload computation, Occlusion Culling's role in reducing rendered vertices and triangles, Mesh optimization's effects on frame rates and memory usage, and Light Baking's potential to improve realism and performance with some limitations like static lighting and file size increase. Applying these techniques to a game developed for this study, the Forest Explorer shows a notable performance gain. Triangles and vertex count were reduced, leading to better frame rates and memory efficiency. Lowered CPU and GPU usage due to light baking. Reduction in the geometry complexity due to mesh optimization. the paper concludes that employing these optimization techniques enables developers to strike a desired balance between performance and user experience quality in Unity-based projects.

关键词： optimization Unity Realism Static Batching GPU Instancing

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Crop Intelligence: Optimizing Agriculture through Machine learning-guided Recommendations 4

Crop Intelligence: Optimizing Agriculture through Machine Le...

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4th International conference on Multimedia Processing, Communication and Information Technology, MPCIT 2024

作者： Ankitha, K. Patil, Shruti Dept. of Artificial Intelligence and Data Science Nitte Karkala India SJEC Dept. of Intelligent Computing and Business System Vamanjur Mangalore India

ISBN: (纸本)9798350375466

Crop Intelligence, powered by Machine learning (ML) and data analytics, is a transformative paradigm poised to revolutionize modern agriculture. this approach involves harnessing the capabilities of Machine learning (ML) to provide tailored recommendations and insights to farmers, enabling data-driven decision-making for optimizing crop yield, resource utilization, and sustainability. this paper explores the potential and advancements in crop intelligence, focusing on how ML-guided recommendations can significantly enhance agricultural practices. Key challenges such as data quality, local adaptability, and user acceptance are identified and discussed, providing a holistic view of the landscape. Additionally, the paper highlights future directions, including personalized recommendations, integration of IoT and remote sensing, and collaborative platforms, as crucial steps toward realizing the full potential of crop intelligence. Ultimately, crop intelligence stands as a promising avenue to bolster global food security, sustainable farming, and the livelihoods of farmers through the fusion of agricultural knowledge with cutting-edge technology. © 2024 IEEE.

关键词： Artificial Intelligence Crop prediction KNN Machine learning

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Research on Optimal Design Strategy of Sport Building Facade in Cold Region Based on intelligent Interaction 4th

Research on Optimal Design Strategy of Sport Building Facade...

引用

4th International conference on Civil Engineering and Architecture (ICCEA)

作者： Quan, Y. Mei, H. Harbin Inst Technol Sch Architecture Key Lab Cold Reg Urban & Rural Human Settlement E Minist Ind & Informat Technol 66 Xidazhi St Harbin 150001 Peoples R China Architectural Design & Res Inst HIT 73 Huanghe Rd Harbin 150090 Peoples R China

ISBN: (纸本)9789811669323;9789811669316

the participation of the crowd has gradually become an important indicator of building facade, and the building facade design has changed from the aesthetic stage to the interactive stage. In this study, applications of intelligent interaction in architectural facade design were investigated using qualitative and quantitative methods and building facade design was optimized based on intelligent interaction. the methods of intelligent facade intervention in architecture were reviewed. Based on intelligent facade design methods, we propose aesthetic optimization strategies for facades, optimization strategies for facade lighting and ventilation, optimization strategies for energy efficiency of facades, and a systematic optimization design strategy of building facades with intelligent interactions. In the era of information and interaction, building facades with intelligent interactions will provide more options to interactions of people, buildings and the environment and become the future direction of building facades.

关键词： Building facade Sport building intelligent interaction

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A Reinforcement learning-based Adaptive Digital Twin Model for Forests 4

A Reinforcement Learning-based Adaptive Digital Twin Model f...

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4th International conference on Applied Artificial Intelligence (ICAPAI)

作者： Damasevicius, Robertas Maskeliunas, Rytis Vytautas Magnus Univ Akademija Lithuania

ISBN: (纸本)9798350349764;9798350349771

We present a Reinforcement learning-based Adaptive Digital Twin (RL-ADT) model designed for forest ecosystems, utilizing advanced IoT data collection and spatiotemporal graph modeling. It focuses on dynamically representing forests for optimized health resource management and sustainability, simulating environmental interactions, and adapting to changing conditions for real-time monitoring and efficient resource usage. the implementation of the model substantially improved the energy and resource efficiency of the digital twin. the construction of spatiotemporal graphs within the model has led to a more accurate and precise representation of the complex interactions within forest ecosystems. this improvement in model fidelity is crucial to understanding and managing the dynamic nature of forests effectively. the adaptability of the RL algorithms is instrumental in managing the dynamic aspects of forests. the RL algorithm has optimized the trade-off between model accuracy and computational overhead, which is vital for the real-time application of the model in forest management. the insights gained from this study have substantial implications for the sustainable management of forest resources. By improving efficiency in resource use, technology aligns closely with sustainability goals and responsible stewardship of natural resources.

关键词： Digital Twin Forest Ecosystem Management Reinforcement learning Spatiotemporal Data Analysis Real-time Ecosystem Modeling Resource optimization in Forestry

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