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检索条件"任意字段=4th IEEE Conference on Control Technology and Applications, CCTA 2020"

共 3450 条记录，以下是1-10 订阅

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ccta 2020 - 4th ieee conference on control technology and applications

CCTA 2020 - 4th IEEE Conference on Control Technology and Ap...

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4th ieee conference on control technology and applications, ccta 2020

ISBN: (纸本)9781728171401

the proceedings contain 165 papers. the topics discussed include: autonomous human tracking using UWB sensors for mobile robots: An observer-based approach to follow the human path;reinforcement learning in deep structured teams: initial results with finite and infinite valued features;backstepping-induced terminal sliding mode control with strict Lyapunov function;SEBezDANS - stability estimation via Bezoutians of the domain of attraction for nonlinear systems;stability versus maneuverability of non-holonomic differential drive mobile robot: focus on aggressive position control applications;experimental evaluation of an adaptive cruise control and cooperative merging concept;stochastic modeled grid outage effect on home energy management;model-predictive spiral and spin upset recovery control for the generic transport model simulation;and a new digital control technique for solar energy harvesting systems in DC micro-grids.

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4th ieee conference on control technology and applications [Front matter]

4th IEEE Conference on Control Technology and Applications [...

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control technology and applications (ccta),

ISBN: (数字)9781728171401

ISBN: (纸本)9781728171418

conference proceedings front matter may contain various advertisements, welcome messages, committee or program information, and other miscellaneous conference information. this may in some cases also include the cover art, table of contents, copyright statements, title-page or half title-pages, blank pages, venue maps or other general information relating to the conference that was part of the original conference proceedings.

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Proceedings of 2020 ieee 4th Information technology, Networking, Electronic and Automation control conference, ITNEC 2020

Proceedings of 2020 IEEE 4th Information Technology, Network...

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4th ieee Information technology, Networking, Electronic and Automation control conference, ITNEC 2020

ISBN: (纸本)9781728143903

the proceedings contain 531 papers. the topics discussed include: IoBTChain: an integration framework of Internet of battlefield things (IoBT) and blockchain;power consumption-based anomaly detection for relay protection;research on switched reluctance motor speed control system with variable universe fuzzy PID;research on data transmission security and early warning;digital twin system design for dual-manipulator cooperation unit;fast mode decision algorithm for intra prediction in HEVC;DeepFaFM :a field-array factorization machine based neural network for CTR Prediction;and the research of material sorting system based on machine vision;robust controller design of 3-DOF helicopter.

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Gesture and Voice controlled Wheelchair 4

Gesture and Voice Controlled Wheelchair

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

作者： Gawli, Palomi Desale, Tejas Deshmukh, Tejas Dongare, Sudarshana Gaikwad, Varun Hajare, Swapnil Vishwakarma Institute of Technology Pune India Vishwakarma Institute of Technology Department of Multidisciplinary Engineering Pune India

ISBN: (纸本)9798331523923

the paper depicts the design and execution of a mobile robotic wheelchair controlled by voice and gesture using Mecanum wheels, with an ESP8266 micro controller used for further command processing. the novel system uses a gesture recognition module, which is intended to obtain commands based on hand movements to reflect into motion commands to the wheelchair. Voice command enables one to use the hands-free interface for mobility impaired individuals. the Mecanum wheel mechanism enables omnidirectional movement, which makes it easy to maneuver in tight locations and dynamic environments. the ESP8266 micro controller has been handy because it consumes less power, processes efficiently, and facilitates real-time communication. the paper demonstrates the challenges that pose gesture and voice control on an omnidirectional mobility platform and creates awareness concerning reliability, accuracy, and robustness in real-life applications. this was quite important, since the essence of this whole project is primarily contributing in two aspects: a step-forward in shared mobility solutions and being an intuitive, flexible, and efficient aid for the use of physically disabled persons. © 2025 ieee.

关键词： Wheelchairs

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A CNN and HBA Based Approach for Grape Disease Identification 4

A CNN and HBA Based Approach for Grape Disease Identificatio...

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

作者： Vishnuvarthan, K. Renugadevi, R. Santhi, S. Kit - Kalaignarkarunanidhi Institute of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798331523923

Grapes are among the most extensively cultivated fruit crops globally, with over 10,000 varieties. they serve as a significant economic resource for many nations due to their diverse applications, including wine production, fresh juice consumption, raisin production, and juice manufacturing. However, grape diseases pose a severe threat to the viticulture industry, leading to substantial financial losses and a decline in wine quality. Manual evaluation is the foundation of traditional disease detection techniques, which are error-prone in addition to saving time. this highlights the need for an automated system capable of analyzing plant health, identifying diseases, and addressing undernourishment efficiently and reliably. Accurate disease diagnosis and timely control measures are crucial for mitigating these challenges. Many scholars have studied various algorithms such as CNN, SVM, Neural Networks, Random Forests, etc., yet each has disadvantages. So we have proposed an automated deep learning-based approach that integrates the Honey Badger Algorithm (HBA) with Convolutional Neural Networks (CNN) for the detection of grape diseases. A phenomenal 95% accuracy rate was attained by the prototype after it was trained on a dataset of 10,000 photos. Its performance was evaluated across various grape varieties and environmental conditions, demonstrating its robustness and adaptability. © 2025 ieee.

关键词： Wine

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Simplification Process in Supply Chain Management through Artificial Intelligence 4

Simplification Process in Supply Chain Management Through Ar...

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

作者： Sharma, Ayushi Kumar, Rakesh Kumar, Deepak Pandey, Purnendu Shekhar Awasthi, Shashank Uttaranchal Institute of Management Uttaranchal University Uttarakhand Dehradun India Graphic Era Deemed to Be University Department of Management Studies Dehradun India Army Institute of Technology Pune India G.L. Bajaj Institute of Technology and Management India

ISBN: (纸本)9798331523923

the aim of this study is to examine Artificial Intelligence(AI) applications in the supply Chain process. According to recent research on Supply Chain Management (SCM) in AI technology and various other technologies (machine learning, deep learning, neural network, expert vision, artificial neural network). Supply Chain Management (SCM) is transforming to artificial intelligence (AI), which improves sustainability, accuracy, and efficiency. this study explores AI in inventory management, warehouse management, customer satisfaction etc. AI Transportation, inventory control, and demand forecasting are all made easier by technologies like computer vision, robotics, and machine learning. Global sustainability goals are in line with AI, but adoption is hampered by issues like labour skill gaps, algorithmic biases, cybersecurity threats, and data quality. Training for the workforce, effective data management, and sustainable procedures are among the recommendations. AI is a key component of SCM's future since it can promote innovation, operational excellence, and sustainable development. the study contributes the objectives to analysis about AI reduced overall cost in supply chain management and also to study and analysis about AI enhanced quality and quantity of product in supply chain management. the study also discussed the SCM through the demand and supply concept economically. there are many challenges like biasness in the algorithm, skill person, and compromise with accuracy which need to be addressed. Finally, the study recommends suggestions and discusses the limitations of AI in supply chain management including sustainable future scope. © 2025 ieee.

关键词： Customer satisfaction

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Evaluating Artificial Neural Networks and Emerging Machine Learning Methods for Engine Performance and Emissions Prediction: A Review 4

Evaluating Artificial Neural Networks and Emerging Machine L...

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

作者： Galat, Umesh Rewatkar, Rajendra Kothare, Chandrakant Datta Meghe Institute of Research and Higher Education Aids Faculty of Engineering and Technology Department of Computer Science and Engineering Maharashtra Wardha India Shri Shankarprasad Agnihotri Collge of Engineering Department of Mechanical Engineering Maharashatra Wardha India

ISBN: (纸本)9798331523923

these due to the shift towards the cleaner energy generation and newer and sophisticated engine technologies the prediction of the performance and emission of engine is of vital importance for the designer for the purpose of ANR as well as the emission control standards. this review also assesses the performance of ANNs and the new machine learning techniques in this area. ANNs especially the single layer and multi-layer networks have shown good levels of predictions of engine performance and emission for ethanol-gasoline, bioethanol and other fuel blends. For example, the models based on Levenberg-Marquardt optimization and the Bayesian regularization have revealed essential correlation coefficients and minimized mean squared errors. Based on comparative analyses, the further improvement of the predictive ability and speed of ANNs is stressed, including applications of ANNs integrated with other approaches like Response Surface Methodology (RSM), and other developing approaches like Extreme Learning Machines (ELM) and Support Vector Regression (SVR). However, challenges are concluded to remains including data quality, model complexities and computational resources. this review reveals that, for tackling these issues and enhancing the progress in developing efficient and sustainable engine solutions, detailed databases and refined mathematical modeling approaches are required. the directions for future research are to obtain better quality data, enhance computational time, and determine more fuel blends and engine settings for the model. © 2025 ieee.

关键词： Adversarial machine learning

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Unleashing WSN Potential: Bowerbird Optimized Energy-Conscious Multipath Clustering with Causal Dilated Cosine for Enhanced Load Balancing 4

Unleashing WSN Potential: Bowerbird Optimized Energy-Conscio...

引用

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

作者： Joon, Rakesh Kumar Anitha, R. Selvan, Saravana Latha Mageshwari, P.S. Gayathri Priya, S. Malathi, K. Ganga Institute of Technology and Management Department of Electronics and Communication Engineering Haryana Kablana124104 India S.A. Engineering College Department of Artificial Intelligence and Data Science Tamil Nadu Chennai600077 India School of Professional Engineering Manukau Institute of Technology Auckland2104 New Zealand Tamil Nadu Kavaraipettai601206 India R.M.D. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Kavaraipettai601206 India Saveetha Engineering College Department of Artificial Intelligence and Machine Learning Tamil Nadu Chennai602105 India

ISBN: (纸本)9798331523923

Wireless Sensor Networks (WSNs) are essential in the collection of real time data across different fields, including environmental monitoring and process control. However, due to the bounded amount of energy in sensor nodes, network lifetime becomes an issue, which hinders performance and reliability. thus, optimization of WSN performance in an attempt to minimize energy consumption is essential for reliable data transmission. In conventional routing and clustering models, network load distribution is not achieved adequately, resulting in a more significant loading of nodes and faster exhaustion of energy. To solve these problems, it is necessary to carefully design load distribution and path finding algorithms to support long-term WSN operation. the objective of this research is to design a framework-Ski-CDiCo-BO-that integrates Skill Optimization for clustering, and ensuring an energy-efficient paths while reducing redundant transmissions on nodes and conserving node energies, and uses the Causal Dilated Cosine Architecture for sophisticated load balancing, and Bowerbird Optimization for improving the parameterization of neural networks. Analysis reveals that the presented Ski-CDiCo-BO framework provides improved performance of various parameters including data delivery success rate of above 99.8% and network lifetime gain by up to 99.5%. Also, load distribution accuracy remains above 99.3%, which indicates that the framework is capable of avoiding node overload and end-to-end delay improved upon by 99.6%, indicating that the solution maintains high parameters even in dynamically changing conditions. In conclusion, Ski-CDiCo-BO maximizes WSN efficiency by implementing cutting-edge clustering, load balancing, and optimization techniques, setting new standards for energy-conscious and reliable sensor network performance across diverse applications. © 2025 ieee.

关键词： Sensor nodes

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Distance-Based Planar Formation control using Orthogonal Variables 4

Distance-Based Planar Formation Control using Orthogonal Var...

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4th ieee conference on control technology and applications (ieee ccta)

作者： Liu, Tairan de Queiroz, Marcio Sahebsara, Farid Louisiana State Univ Dept Mech & Ind Engn Baton Rouge LA 70803 USA

ISBN: (纸本)9781728171401

In this paper, we propose a novel approach to the problem of augmenting distance-based formation controllers with a secondary feedback variable for the purpose of preventing formation ambiguities. We introduce two variables that form an orthogonal space and uniquely characterize a triangular formation in two dimensions. We show that the resulting controller ensures the almost-global asymptotic stability of the desired formation for an n-agent system without conditions on the triangulations of the desired formation or control gains.

关键词： controllers

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Experimental Evaluation of an Adaptive Cruise control and Cooperative Merging Concept 4

Experimental Evaluation of an Adaptive Cruise Control and Co...

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4th ieee conference on control technology and applications (ieee ccta)

作者： Schwab, Alexander Reichelt, Lisa-Marie Welz, Philipp Lunze, Jan Ruhr Univ Bochum Inst Automat & Comp Control Bochum Germany

ISBN: (纸本)9781728171401

this paper presents an experimental evaluation of a concept for platooning and cooperative merging of networked vehicles in case of an upcoming lane reduction. In order to test the platooning and merging concept, differential-driven robots are used. Low level path controllers are designed to guide the robots to a prescribed path on which the robots can be represented by linear models. Furthermore, a lane changing approach will be presented that maintains the longitudinal inter-robot distance while moving laterally to the other lane. the effectiveness of the proposed methods is discussed with experimental results.

关键词： Merging

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