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Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

computers, Materials & Continua 2022年第1期70卷 1053-1067页

作者： Lijo Jacob Varghese K.Dhayalini Suma Sira Jacob Ihsan Ali Abdelzahir Abdelmaboud Taiseer Abdalla Elfadil Eisa Department of Electrical and Electronics Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Information Systems King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia

Peer-to-Peer(P2P)electricity trading is a significant research area that offers maximum fulfilment for both prosumer and *** also decreases the quantity of line loss incurred in Smart Grid(SG).But,uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and *** recent times,numerous Machine Learning(ML)-enabled load predictive techniques have been developed,while most of the existing studies did not consider its implicit features,optimal parameter selection,and prediction *** order to overcome fulfill this research gap,the current research paper presents a new Multi-Objective Grasshopper Optimisation Algorithm(MOGOA)with Deep Extreme Learning Machine(DELM)-based short-term load predictive technique i.e.,MOGOA-DELM model for P2P Energy Trading(ET)in *** proposed MOGOA-DELM model involves four distinct stages of operations namely,data cleaning,Feature Selection(FS),prediction,and parameter *** addition,MOGOA-based FS technique is utilized in the selection of optimum subset of ***,DELM-based predictive model is also applied in forecasting the load *** proposed MOGOA model is also applied in FS and the selection of optimalDELM parameters to improve the predictive *** inspect the effectual outcome of the proposed MOGOA-DELM model,a series of simulations was performed using UK Smart Meter *** the experimentation procedure,the proposed model achieved the highest accuracy of 85.80%and the results established the superiority of the proposed model in predicting the testing data.

关键词： Peer to Peer energy trade smart grid load forecasting machine learning feature selection

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Energy Efficient Hybrid Routing for Different Energy Levels Using Fuzzy Logic

Energy Efficient Hybrid Routing for Different Energy Levels ...

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2023 International Conference on IoT, Communication and Automation Technology, ICICAT 2023

作者： Singh, Kalpana Pandey, Prashant Ahamad, Firoj Rajkiya Engineering College Department of Computer Science Engineering Uttar Pradesh Sonbhadra231206 India Rajkiya Engineering College Department of Electronics Engineering Uttar Pradesh Sonbhadra231206 India School of Computer and System Sciences Jawaharlal Nehru University New Delhi Delhi 110067 India

ISBN: (纸本)9798350302820

Collection of sensor nodes and base station called as Wireless Sensor Networks. While, communicating with other nodes within network this type of network uses huge amount of energy. And, node has limited life time due to battery power. For efficiently utilizing these nodes energy and power, clustering was considered as a best approach. In proposed paper, we work on heterogeneous node, in such environment nodes are differ by their energy level, power, computation, communication etc. The protocol proposed for Energy Efficient Hybrid Routing in different energy levels using fuzzy logic provides three different network for three different initial energy level of nodes such that. 3J,. 4J and. 5J under same area (500∗500) m2 in which super node region uses multipath routing and clustering approach uses for transmitting packet/ data to base station and normal type nodes will uses single path routing transmitting packet/ data to Base station. The proposed protocol discussed different energy levels for finding best initial energy value of node in network and improved throughput, stability, lifetime of network on. 4J energy level as compare to. 3J and. 5J. To optimize the cluster formation we used predetermined technique i.e. inverted binary tree. This technique helps in balancing the load of super nodes region. The proposed model simulated in MATLAB, result shows better performance at 0.4J initial energy. © 2023 IEEE.

关键词： Fuzzy logic

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Sensing Metric-Based Hybrid Underlay/Overlay Transmission Framework for CR-IoT Networks for Smart City Applications 7

Sensing Metric-Based Hybrid Underlay/Overlay Transmission Fr...

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7th IET Smart Cities Symposium, SCS 2023

作者： Bala, Indu Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Ibrahim, Abdelhameed School of Electrical and Electronics Engineering Lovely Professional University Punjab India Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services. To address this issue, Cognitive Internet of Things (CR-IoT) enables devices to optimize their efficiency and enhance their communication capabilities by intelligently accessing available bandwidth. This is achieved through the use of soft sensing metrics, where devices continuously monitor the RF environment and transmit data opportunistically in overlay mode if a free channel is detected, or in underlay mode if not. In this paper, a soft sensing metric based hybrid transmission framework is proposed for CR-IoT devices to meet the data rate requirement for the smart city applications. The efficacy of this approach is demonstrated through simulation results. © The Institution of engineering & Technology 2023.

关键词： Smart city

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Improved High-Speed Thermal Analysis Based on Two-Step Simulation for High-Frequency Transformers 14

Improved High-Speed Thermal Analysis Based on Two-Step Simul...

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14th Annual IEEE Applied Power electronics Conference and Exposition, APEC 2025

作者： Yi, Zheyuan Sun, Kai Li, Qiang Liu, Zengyang Tsinghua University State Key Laboratory of Power System Department of Electrical Engineering Beijing China Delta Electronics Shanghai Co. Ltd. Shanghai China University Blacksburg Center for Power Electronics Systems The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State BlacksburgVA United States

ISBN: (纸本)9798331516116

Thermal analysis is a crucial and time-consuming step in the optimization design process of high-frequency transformers (HFTs). This paper proposes an improved thermal analysis method based on heat dissipation-conduction two-step simulation, significantly reducing the computation time while ensuring the accuracy of thermal analysis. Simulation results validate the accuracy and of the proposed method and demonstrate that the proposed method saves 82% of computation time for a single thermal analysis case compared to direct CFD. Experimental results further verify the accuracy of the proposed method. An exemplary application of the proposed method in the optimization design of the HFT illustrates a 98% reduction in computation time for thermal analysis during the optimization process. © 2025 IEEE.

关键词： Thermal modeling

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Machine Learning-based Evaluation of Heart Rate Variability Response in Children with Autism Spectrum Disorder 3

Machine Learning-based Evaluation of Heart Rate Variability ...

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3rd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2023

作者： Mohammed, Vazeer Ali Mohammed, Mehmood Ali Mohammed, Murtuza Ali Logeshwaran, J. Jiwani, Nasmin Lewis University Department of Computer and Information System IL United States University of the Cumberlands Department of Information Technology WilliamsburgKY United States Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9781665462167

At present, various electronic devices are used to monitor human heart rates. However, its functions are to avoid predicting the problems caused by heart rate variability in advance and analyzing its implications. It makes it difficult to diagnose problems caused by heart rate variability. A human should have an average heart rate of 72. At the same time, the newborn's heart should beat between 120 and 160 beats per minute. A baby born with autism spectrum disorder may have a lower-than-average heart rate. Complete blockage of the heart at birth is rare. Abnormal heart rate leads to heart block. So, there is a high chance of the child's death due to permanent heart blockage at any time. Most heart diseases in children with Autism Spectrum Disorder (ASD) are present at birth. A significant congenital disability is a hole in the heart. Many people do not realize that having holes in the heart is a common occurrence. Before the baby is born, tiny holes form in the muscular wall that divides the heart into the right and left halves. This paper proposed Machine Learning-Based Evaluation to identify the Heart Rate Variability Response in Children with Autism Spectrum Disorder with Autism Spectrum Disorder. The reasons for this are yet to be identified. However, 70 per cent of perforations resolve spontaneously before or after birth. Exceptionally, Children with Autism Spectrum Disorder with perforations that do not close properly may require surgery or a perforator brace, depending on the location and size of the perforation. © 2023 IEEE.

关键词： Heart

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Leveraging Adaptive Algorithms for Real-Time Data Analysis 15

Leveraging Adaptive Algorithms for Real-Time Data Analysis

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sahoo, Girija Shankar Hannah Jessie Rani, R. Goyal, Manish Kumar Mohammed, Vazeer Ali Jana, D Little Femilin Wasatkar, Namrata N. Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Electrical and Electronics Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Lewis University Illinois Department of Computer & Information System United States Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350370249

This paper proposes the use of adaptive algorithms for real-time data analysis. Adaptive algorithms are a set of practical methods used for acting information-driven optimization and studying. They have a wide variety of applications and may be implemented to a selection of facts analysis obligations. This paper offers an overview of existing adaptive algorithms and descriptions of several new programs in the area of actual-time facts analysis. In particular, the paper discusses the notion of adaptive thresholding, which allows for practical real-time evaluation of large datasets. The paper also provides a novel technique for making use of these algorithms in an online learning environment. Results from simulations illustrate the ability of the proposed method in real-international packages. Sooner or later, the paper presents numerous key lessons discovered and affords recommendations for future research and packages in this area. © 2024 IEEE.

关键词： Adaptive algorithms

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Hybrid CNN LSTM Approach for Sentiment Analysis of Bengali Language Comment on Facebook 2

Hybrid CNN LSTM Approach for Sentiment Analysis of Bengali L...

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2nd IEEE International Conference on Integrated Circuits and Communication systems, ICICACS 2024

作者： Nobel, SM Nuruzzaman Swapno, S M Masfequier Rahman Ramachandra, A.C. Shajeeb, Hasibul Hossain Islam, Md Babul Haque, Rezaul Bangladesh University of Business and Technology Dept of Computer Science and Engineering Dhaka Bangladesh Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India UNICAL Dept. of Computer Modeling Electronic and System Engineering Rende Italy East West University Dept of CSE Dhaka1212 Bangladesh

ISBN: (纸本)9798350317558

This study addresses the challenge of sentiment analysis in Bengali Facebook comments, where users express their opinions on various topics. Existing sentiment analysis techniques have difficulty achieving high accuracy in this situation, which has inspired the creation of a fresh methodology. To improve sentiment analysis of Bengali Facebook comments, we suggest a model that combines a hybrid convolutional neural network (CNN) and a long short-term memory network (LSTM). Our research adds to the expanding area of sentiment analysis, especially for languages with few resources, such as Bengali. The success of the Hybrid CNN LSTM model opens the door for more precise and context-aware sentiment analysis on social media platforms, allowing for a better understanding of user sentiments and boosting user experiences. Our study focused on dividing comments into five groups according to their emotional content: troll, not bully, sexual, religious, and threat. We carefully generated the handmade dataset and ensured the quality and relevance of a dataset of 50,000 Bengali comments before using it to train and test our algorithm. The Hybrid CNN LSTM model outperforms conventional approaches and achieves an outstanding accuracy rate of 92.09%, demonstrating amazing efficiency in sentiment recognition. This dramatic increase in precision indicates that machine learning techniques are successful in sentiment analysis of Bengali Facebook comments. © 2024 IEEE.

关键词： Bengali Language CNN Comment Facebook Fully Connected Layer Hybrid LSTM NLP Predict Sentiment

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Peak-Average-Power Ratio Techniques for 5G Waveforms Using D-SLM and D-PTS

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computer systems Science & engineering 2023年第5期45卷 1199-1210页

作者： Himanshu Sharma karthikeyan Rajagopal G.Gugapriya Rajneesh Pareek Arun Kumar HayaMesfer Alshahrani Mohamed K.Nour Hany Mahgoub Mohamed Mousa Anwer Mustafa Hilal Department of Computer Science&Engineering JECRC UniversityJaipurIndia Centre for Nonlinear Systems Chennai Institute of TechnologyChennaiIndia School of Electronics Engineering Vellore Institute of TechnologyChennaiIndia Department of Electronics and Communication Engineering JECRC UniversityJaipurIndia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Electrical Engineering Department Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Multicarrier Waveform(MCW)has several advantages and plays a very important role in cellular *** generation(5G)MCW such as Non-Orthogonal Multiple Access(NOMA)and Filter Bank Multicarrier(FBMC)are thought to be important in 5G *** Peak to Average Power Ratio(PAPR)is seen as a serious concern in MCW since it reduces the efficiency of amplifier use in the user *** paper presents a novel Divergence Selective Mapping(DSLM)and Divergence Partial Transmission Sequence(D-PTS)for 5G *** is seen that the proposed D-SLM and PTS lower PAPR with low computational *** work highlighted a combination of multi-data block partial transmit schemes along with tone *** this,an overlapping factor is used to determine the number of data blocks for every ***,considering only those data blocks that have minimum signal power,the use of DSLM and DPTS are required to eliminate the segment’s *** results reveal that the suggested hybrid technique proves to be better than the conventional PTS ***,the power saving performance of FBMC and NOMA is compared with the Orthogonal Frequency Division Multiplexing(OFDM)waveform.

关键词： 5G PAPR D-SLM D-PTS

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Optical Satellite Networks

Optical Satellite Networks

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2023 Optical Fiber Communications Conference and Exhibition, OFC 2023

作者： Chan, Vincent W.S. Massachusetts Institute of Technology Research Laboratory of Electronics Steve Schwarzman College of Computing Ai and Decision System Sector Department of Electrical Engineering and Computer Science United States

We will explore the architecture of optical satellite networks at 100G-1Tbps. The challenge is to architect the system and the network protocols with large bandwidth-delay products and the presence of atmospheric turb... 详细信息

ISBN: (纸本)9781957171180

关键词： Atmospheric turbulence

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Feature Map Guided Strategy for Robust Multi-Resolution Image Dehazing

Feature Map Guided Strategy for Robust Multi-Resolution Imag...

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2024 International Conference on Electrical, electronics and Computing Technologies, ICEECT 2024

作者： Kumar, Avishek Kumar, Nagendra Mishra, Akhilesh Kumar Pathak, Gouransh Chatterjee, Amit IIT Delhi Centre for Sensors Instrumentation and Cyber-Physical System Engineering New Delhi110016 India NIT Jamshedpur Department of Electronics and Communication Engineering Jamshedpur831014 India IILM Univeristy Department of Electrical and Electronics Engineering Greater Noida201306 India PIEMR-Indore Department of Computer Science and Engineering Indore452010 India DIT University School of Computing Dehradun248009 India

ISBN: (纸本)9798350378092

Presence of haze in digital images poses significant challenges in computer vision applications, adversely impacting tasks like image segmentation and object detection. To tackle this issue, this paper introduces a fusion-based dehazing strategy by integrating color conversion, adaptive gamma correction, and parameter estimation. Through multi resolution fusion of chromatic and brightness maps, the algorithm efficiently removes haze, surpassing conventional single-image approaches while maintaining computational efficacy. From comparative analysis it is evident that, the proposed strategy is highly effective in terms of improving image quality for diverse applications. © 2024 IEEE.

关键词： Demulsification

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