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Research on intelligent Decision Making for Distributed Photovoltaic Optimization Operation Based on Optimal Power Flow 11

Research on Intelligent Decision Making for Distributed Phot...

引用

11th China international conference on Electricity Distribution, CICED 2024

作者： Liu, Chuan Li, Jisen Hu, Wei Liu, Fan Meng, Yujing Guo, Qiuting Hao, Hao State Grid Beijing Miyun Electric Power Supply Company Beijing China Tsinghua University Department of Electrical Engineering Beijing China

ISBN: (纸本)9798350368345

the combined decision-making method based on SOCR and CNN was established to address the problems of power flow backflow, increased network losses, and voltage exceeding caused by large-scale grid connection of distributed photovoltaics. Firstly, establish an optimal power flow model with the objective functions of minimizing grid loss and maximizing photovoltaic consumption. Secondly, constraints were established and OPF was transformed into a SOCP model, which was solved using the CPLEX solver, the effectiveness of the model was verified through simulation. Finally, the deep learning algorithms are introduced to train historical operational data, construct mapping relationships between load, photovoltaic and operational plans, and combine them with OPF models for combination decision-making. this method can continuously improve decision-making efficiency and has good performance in practical use. © 2024 IEEE.

关键词： Load flow optimization

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Comparison of data Visualization Platforms through European Traffic data 11

Comparison of Data Visualization Platforms Through European ...

引用

11th IEEE international conference on Computational Cybernetics and Cyber-Medical Systems, ICCC 2024

作者： Nagy, Eniko Tamas Ferenc, Gombos Molnar, Gyorgy Óbuda University Antal Bejczy Center for Intelligent Robotics John von Neumann Faculty Budapest Hungary Óbuda University John von Neumann Faculty Budapest Hungary Óbuda University Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary Széchenyi University Apáczai Csere János Faculty of Humanities Education and Social Sciences Győr Hungary

ISBN: (纸本)9798350350142

the most important and valuable resource in the 21st century is data. the age of the internet brought us an era in which humans, within a foreseeable time, are unable to process the vast amount of data that we produce. It's important to understand the data and statistics we have because it can help a company make a well thought out decision on a given dilemma, which is based on reality and data. When choosing a data visualisation platform, the purpose of the application, the type of data and the user needs are also key factors. For the visualisation of traffic data in Europe, a number of established platforms can be considered and are referred to in this paper. this article compares data visualisation platforms currently available and used in industrial environments with open source free platforms, using European traffic data. © 2024 IEEE.

关键词： data visualization

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RECURSIVE TIME SERIES data AUGMENTATION 11

RECURSIVE TIME SERIES DATA AUGMENTATION

引用

11th international conference on learning Representations, ICLR 2023

作者： Aboussalah, Amine Mohamed Kwon, Minjae Patel, Raj G. Chi, Cheng Lee, Chi-Guhn New York University United States University of Virginia United States University of Toronto Canada

Time series observations can be seen as realizations of an underlying dynamical system governed by rules that we typically do not *** time series learning tasks we create our model using available *** on available realizations, where data is limited, often induces severe over-fitting thereby preventing *** address this issue, we introduce a general recursive framework for time series augmentation, which we call the Recursive Interpolation Method (RIM).New augmented time series are generated using a recursive interpolation function from the original time series for use in *** perform theoretical analysis to characterize the proposed RIM and to guarantee its performance under certain *** apply RIM to diverse synthetic and real-world time series cases to achieve strong performance over non-augmented data on a variety of learning *** method is also computationally more efficient and leads to better performance when compared to state of the art time series data augmentation. © 2023 11th international conference on learning Representations, ICLR 2023. All rights reserved.

关键词： Time series

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EEG-Based Emotion Recognition Using Optimized Deep-learning Techniques 11

EEG-Based Emotion Recognition Using Optimized Deep-Learning ...

引用

11th IEEE international conference on Signal Processing and Integrated Networks, SPIN 2024

作者： Dwivedi, Amit Kumar Verma, Om Prakash Taran, Sachin Delhi Technological University Rohini Department of Electronics and Communication New Delhi110042 India

ISBN: (纸本)9798350308433

Emotions are crucial in identifying the current mental state. Electroencephalography (EEG) signals can accurately determine the current mental state. the automatic identification and analysis of human emotions using EEG data is vital in the treatment of psychiatric diseases due to the influence that emotions have on interactions, interpretations, and decisions. However, one major problem with EEG recorders is their low spatial resolution. EEG signals are nonlinear and complicated. Advanced signal processing techniques are required to analyze and extract useful characteristics. Emotion recognition using EEG can improve human-machine interactions. A convolutional neural network (CNN) is suggested in this article for automatic feature extraction and categorization of emotions. First, EEG signals are converted into pictures by applying time-frequency representation techniques. Following this, these pictures are fed into CNN and optimized CNN models for training. the optimized CNN model produces better accuracy for classifying emotions. Deep learning (DL) techniques are popular for determining complex patterns. Deep learning methods have shown good results in EEG-based emotion identification. It can automatically extract high-level information. DL's performance depends on hyperparameters. However, optimizing the performance of a deep-learning model requires accurate hyperparameter tuning. the manual hyperparameter tuning method is tiresome, costly, computationally expensive, and time-consuming. As a result, an automated method is required to determine the best hyperparameters to maximize DL's efficacy. To automate the hyperparameter optimization process, the proposed work presents a novel framework based on Bayesian optimization. Bayesian optimization (BO) is used to automate hyperparameter selection to predict emotional states. © 2024 IEEE.

关键词： Emotion Recognition

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data Security in intelligent System for Road Maintenance Using Encryption and HTTPS 11

Data Security in Intelligent System for Road Maintenance Usi...

引用

11th international conference on Electrical engineering, Computer Science and Informatics, EECSI 2024

作者： Hermawan, Hendi Uddin, Nur Alfat, Lathifah Universitas Pembangunan Jaya Department of Informatics South Tangerang Indonesia

ISBN: (纸本)9798350355314

A highly maintained toll road decreases accident risk, improves traffic efficiency, and enhances infrastructure feasibility, resulting in reduced maintenance costs. this study presents the implementation of data security in an intelligent toll road maintenance system using AES encryption and HTTPS protocols. the proposed system consists of NodeMCU ESP-12 as the microcontroller, MPU6050 accelerometer for measuring vehicle vibrations, Neo-6M GPS module for location tracking, and an SD card module for data storage. the collected data is encrypted using AES before being transmitted securely over HTTPS. Experimental results show that the system enhances data security with an encryption time of 1884 ms using AES+HTTP and 5721 ms using AES+HTTPS, demonstrating the feasibility of this approach despite the increased processing time. © 2024 IEEE.

关键词： data security decryption encryption HTTPS intelligent systems

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Bifurcations and Application of the Vallis - Model 11

Bifurcations and Application of the Vallis - Model

引用

11th IEEE international conference on Computational Cybernetics and Cyber-Medical Systems, ICCC 2024

作者： Nagy, Balint Molnar, Gyorgy Joos, Antal Nagy, Eniko Institute of Computer Engineering University of Dunaújváros Department of Mathematics Dunaújváros Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary Institute of Electrophysics Óbuda University Kandó Kálmán Faculty of Electrical Engineering Department of Natural Sciences Budapest Hungary Óbuda University Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary Széchenyi University János Csere Apáczai Faculty Győr Hungary Antal Bejczy Center for Intelligent Robotics Institute of Cyberphysical Systems Óbuda University John von Neumann Faculty Budapest Hungary

ISBN: (纸本)9798350350142

Investigating chaotic systems is a fertile field considering that chaos is an exotic chapter in the theory of differential equations, and it has useful applications in the theory of communications. In this work a well-known chaotic system is investigated from the bifurcation point of view and some applications are also introduced. the data studied are also visualized for better clarity. the results observed can be helpful in the encryption methods of the implementation of different communication channels. © 2024 IEEE.

关键词： Chaotic systems

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Designing Conversational Agents for Emotional Self-Awareness 11

Designing Conversational Agents for Emotional Self-Awareness

引用

11th international conference on Affective Computing and intelligent Interaction (ACIIW)

作者： Shen, Jocelyn Lecamwasam, Kimaya Park, Hae Won Breazeal, Cynthia Picard, Rosalind MIT Media Lab Cambridge MA 02139 USA

ISBN: (纸本)9798350327458

Emotional self-awareness is a crucial social-emotional skill for positive psychology and mental well-being. While prior works have used AI applications to foster emotion awareness, it is unclear what specific design features users prefer in the context of self-awareness skill practice. To better understand these features, we design, deploy, and evaluate Teddy, a mobile conversational agent that helps users practice verbalizing and reflecting on their emotions through experience sampling, affect labeling, and personal storytelling interactions. We conduct a user study with 18 days of interaction data from six participants to evaluate what aspects of Teddy contribute to emotion awareness. We find that users felt comfortable self-disclosing to the agent and found it helpful to verbalize their emotions, but desired more characteristics like social responsiveness and personalization. Based on our pilot study, we outline design insights for future work on AI agents that support practice of social-emotional skills such as emotional self-awareness.

关键词： agent mental health emotional intelligence social emotional learning

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11th international conference on intelligent Computing and Applications, ICRTC 2023

11th International Conference on Intelligent Computing and A...

引用

11th international conference on intelligent Computing and Applications, ICRTC 2023

ISBN: (纸本)9789819717231

the proceedings contain 70 papers. the special focus in this conference is on intelligent Computing and Applications. the topics include: RNN learning for Dynamic Selection of Channel Access Scheme in FANETs;a Crime Knowledge Discovery Scheme Based on Entity Recognition, Relation Extraction, and Development of Criminal Profiling Using Modus Operandi;optimized Biometric Key Management System for Enhanced Security;human Posture Identification and Recognition Using Deep learning Techniques;twitter Sentiment Analysis Using Different Machine learning Techniques;exploring Empirical Mode Decomposition for Music Genre Classification Using Deep learning;a Comparative Analysis of Fog Computing’s Problems, Challenges and Future Directions;explainable Artificial Intelligence Insight: An Orderly Survey;deep learning-Based Sign Language Translator;Analysis of Arrhythmia from Electrocardiogram (ECG) data Using ML Framework;brain Tumor Detection Using Quantum Neural Network;augmented Reality-Based Application for Indian Monuments;fog Obscurity Mitigation;a Load Balancing Using Multi-population Grasshopper Optimization Approach for Workflow Tasks in Clouds;parental Control for Techie Child Using Keylogger;modified Box Filter Design and Noise Analysis on Two-Dimensional Images;Change Detection in Remote Sensing SAR Image Using a Ratio-Based Operator;automatic Question Generation: A Comparative Analysis of Rule-Based and Neural Network-Based Models;mango Leaf Images Quality Improvement Techniques Using Subjective Approach of Image Enhancement;real-Time 3D Texture and Motion Analysis for Face Anti-spoofing Using Deep learning and Computer Vision;Hybrid Sentiment Polarity Prediction Scheme in Social Networks using Attention Mechanism and Improved CNN;survival Analysis of Heart Failure Patients with Advanced Machine learning Models;a Differential Privacy Perturbation with Random Forest Classifier in Medical database;smart Application for Early Detection of Rice Plant Disease Using Incept

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A STATISTICAL FRAMEWORK FOR PERSONALIZED FEDERATED learning AND ESTIMATION: thEORY, ALGORIthMS, AND PRIVACY 11

A STATISTICAL FRAMEWORK FOR PERSONALIZED FEDERATED LEARNING ...

引用

11th international conference on learning Representations, ICLR 2023

作者： Ozkara, Kaan Girgis, Antonious M. data, Deepesh Diggavi, Suhas Department of Electrical and Computer Engineering University of California Los Angeles United States

A distinguishing characteristic of federated learning is that the (local) client data could have statistical heterogeneity. this heterogeneity has motivated the design of personalized learning, where individual (personalized) models are trained, through collaboration. there have been various personalization methods proposed in literature, with seemingly very different forms and methods ranging from use of a single global model for local regularization and model interpolation, to use of multiple global models for personalized clustering, etc. In this work, we begin with a statistical framework that unifies several different algorithms as well as suggest new algorithms. We apply our framework to personalized estimation, and connect it to the classical empirical Bayes' methodology. We develop novel private personalized estimation under this framework. We then use our statistical framework to propose new personalized learning algorithms, including AdaPeD based on information-geometry regularization, which numerically outperforms several known algorithms. We develop privacy for personalized learning methods with guarantees for user-level privacy and composition. We numerically evaluate the performance as well as the privacy for both the estimation and learning problems, demonstrating the advantages of our proposed methods. © 2023 11th international conference on learning Representations, ICLR 2023. All rights reserved.

关键词： learning algorithms

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Research on Street View Information Extraction Method Based on Convolutional Neural Network 6

Research on Street View Information Extraction Method Based ...

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6th IEEE international conference on Power, intelligent Computing and Systems, ICPICS 2024

作者： Chen, Zijing Yang, Hao College of Urban Construction and Design Urban Vocational College of Chengdu Chengdu China Guangdong Engineering Polytechnic Faculty of Architectural Engineering Qingyuan China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374315

As the largest public space in the city, street is an important part of residents' life, and the study of street is conducive to improving the overall image of the city. However, the traditional street scene research relies on low throughput survey and limited data sources, and its efficiency is relatively low, which can no longer meet the growing needs of street research. With the combination of artificial intelligence learning technology and landscape architecture, it is possible to identify and evaluate streets intelligently. the results show that the semantic segmentation model has good performance in street view image processing, accuracy rate and mIOu value. the research of this paper lays a foundation and provides a thought for the evaluation of the elements after semantic segmentation of a large number of complex street view images at the same time, and provides technical support for automated street landscape evaluation. © 2024 IEEE.

关键词： Semantic Segmentation

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