检索结果-内蒙古大学图书馆

An Entropy-Integrated Adaptive Coding and Scheduling Framework for Optimized Data Transmission in Fog-Cloud IoT Architectures

引用

IEEE Internet of Things Journal 2025年

作者： Lu, Yang Zang, Yuting Bian, Ziyi Zhao, Shuai Zheng, Yan Northeast Forestry University College of Computer and Control Engineering Harbin China Harbin Normal University College of Computer and Information Engineering Harbin China La Trobe University School of Computing Engineering and Mathematical Sciences MelbourneVIC Australia

Entropy-driven network coding has been used as a basis for optimizing data transmission and enhancing resource utilization in Fog-Cloud IoT architectures, including applications in smart cities, industrial automation, environmental monitoring, and healthcare. In Fog-Cloud IoT architectures, conventional data transmission protocols are inefficient because they cannot adapt to dynamic entropy levels, resulting in underutilized bandwidth, increased latency, and higher energy consumption. In this paper, we propose an Enhanced Entropy-Driven Network Coding (E-EDNC) framework to address these problems. Our framework integrates real-time entropy estimation with adaptive coding strategies and employs a hybrid evolutionary-reinforcement learning (HE-RL) algorithm to dynamically optimize coding parameters and scheduling decisions. Experimental results demonstrate that E-EDNC improves bandwidth utilization by 25%, reduces latency by 25%, and decreases energy consumption by 12%, thereby enhancing overall data transmission efficiency and reliability in Fog-Cloud IoT environments. © 2014 IEEE.

关键词： Network coding

来源：评论

学校读者我要写书评

暂无评论

Optimal Operation Strategy of Microgrid Based on TD3 Algorithm 7

Optimal Operation Strategy of Microgrid Based on TD3 Algorit...

引用

7th IEEE International Conference on Power and Renewable Energy, ICPRE 2022

作者： Cui, Chenyu Dong, Ze North China Electric Power University Hebei Technology Innovation Center of Simulation and Optimized Control for Power Generation School of Control and Computer Engineering Baoding China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

It is necessary to optimize the operation of micro power grid in order to improve its economy. Firstly, the mathematical model of optimal dispatching of microgrid is established. Taking the internal battery charge and discharge power, fan and photovoltaic output power of microgrid as the optimization vector and the minimum operation cost of microgrid as the optimization objective, based on the day ahead prediction data, the day is divided into 24h as a dispatching period for optimization. The Twin Delayed Deep Deterministic policy gradient algorithm (TD3) is used to solve the problem, and the power supply composition and cost data are obtained. The simulation results verify the effectiveness of the algorithm and optimal scheduling strategy. © 2022 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Dynamic Curing and Network Design in SIS Epidemic Processes 63

Dynamic Curing and Network Design in SIS Epidemic Processes

引用

63rd IEEE Conference on Decision and control, CDC 2024

作者： Yi, Yuhao Shan, Liren Pare, Philip E. Johansson, Karl H. Sichuan University Institute of Clinical Pathology West China Hospital College of Computer Science Chengdu China Toyota Technological Institute at Chicago United States Purdue University School of Electrical and Computer Engineering West LafayetteIN United States Kth Royal Institute of Technology and They Are Also Affiliated with Digital Futures Division of Decision and Control Systems School of Electrical Engineering and Computer Science StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

This paper studies efficient algorithms for dynamic curing policies and the corresponding network design problems to guarantee fast extinction of epidemic spread in a Markov process-based susceptible-infected-susceptible (SIS) model. We provide a computationally efficient curing algorithm based on the curing policy proposed by Drakopoulos, Ozdaglar, and Tsitsiklis (2014). Since the corresponding optimization problem is NP-hard, finding optimal policies is intractable for large graphs. We provide approximation guarantees on the curing budget of the proposed dynamic curing algorithm. To avoid the waiting period included in the original curing policy, we study network design problems to reduce the total infection rate by deleting edges or reducing the weight of edges. To this end, we provide algorithms with provable guarantees. In summary, the proposed curing and network design algorithms together provide an effective and computationally efficient approach that mitigates SIS epidemic spread in networks. © 2024 IEEE.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

KartalOl: a new deep neural network framework based on transfer learning for iris segmentation and localization task—new dataset for iris segmentation

引用

Iran Journal of computer Science 2023年第4期6卷 307-319页

作者： Khiarak, Jalil Nourmohammadi Oskouei, Amin Golzari Nasab, Samaneh Salehi Jaryani, Farhang Moafinejad, Seyed Naeim Pourmohamad, Rana Amini, Yasin Noshad, Morteza Institute of Control and Computation Engineering Warsaw University of Technology Ul. Nowowiejska 15/19 Warsaw 00-665 Poland Department of Computer Engineering Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran School of Engineering Lorestan University Aleshtar Campus Aleshtar Iran Faculty of Engineering Arak University Arak Iran Department of Physics Shahid Beheshti University Tehran Iran School of Computing Informatics and Decision Systems Engineering Arizona State University AZ United States Faculty of Electrical and Computer Engineering University of Kharazmi Tehran Iran Stanford University Stanford United States

Iris segmentation and localization in unconstrained environments are challenging due to long distances, illumination variations, limited user cooperation, and moving subjects. Some existing methods in the literature have somehow mitigated some of the above-mentioned issues. In this paper, motivated by these weaknesses, we propose a framework that employs a deep neural network-based approach to iris segmentation and localization. The proposed framework is based on a U-Net architecture initialized with a pre-trained MobileNetV2 model. In addition, to better study the detectors in iris recognition scenarios, we have collected 1000 images. The provided dataset (KartalOl) is made publicly available for the research community. In the proposed framework, to have better generalization, we fine-tuned the MobileNetV2 model on the provided data for NIR-ISL 2021 from the CASIA-Iris-Asia, CASIA-Iris-M1, and CASIA-Iris-Africa and our dataset. Likewise, data augmentation techniques are applied on images. We chose the binarization threshold for the binary masks by iterating over the images in the provided dataset. The proposed framework is trained and tested in CASIA-Iris-Asia, CASIA-Iris-M1, and CASIA-Iris-Africa, along with the KartalOl dataset. The experimental results highlight that our method surpasses state-of-the-art methods on mobile-based benchmarks. The implementation source code of KartalOl is made publicly available at https://***/Jalilnkh/KartalOl-NIR-ISL2021031301. © The Author(s) 2023.

关键词： Iris segmentation Localization MobileNetV2 model Unconstrained environment

来源：评论

学校读者我要写书评

暂无评论

Description and comparison of fault detection algorithms based on a selected building automation device

引用

Bulletin of the Polish Academy of Sciences: Technical Sciences 2025年第3期73卷

作者： Wlostowska, Sandra Kawa, Bartlomiej Borkowski, Piotr Department of Electrical Apparatus Faculty of Electrical Electronics Computer and Control Engineering Lodz University of Technology Lódź Poland

The article compares selected classification algorithms and those dedicated to anomaly detection. The models used temperature measurements in four rooms simulated in the MATLAB Simscape environment as test signals. The empirical part of the work consists of two parts. In the first one, an example data from the simulated building heating model object, models were built using unsupervised and supervised machine learning algorithms. Then, data from the facility was collected again with changed parameters (failures occurred at times other than the test ones, and the temperature patterns differed from those recorded and used to train the models). The algorithm effects and test signals (temperature changes) were saved in the database. The results were presented graphically in the Grafana program. The second part of the work presents a solution in which the analysis of the operating status of the heating system takes place in real time. Using an OPC server, data was exchanged between the MATLAB environment and the database installed on a virtual machine in the Ubuntu system. The conclusions present the results and collect the authors’ suggestions regarding the practical applications of the discussed classification models. © 2025 The Author(s).

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

ICEEMDAN-IWOA-BiLSTM Hybrid Algorithm-based Model for Short-term Load Forecasting 2

ICEEMDAN-IWOA-BiLSTM Hybrid Algorithm-based Model for Short-...

引用

2023 2nd International Conference on Energy Internet and Power Systems, ICEIPS 2023

作者： Dong, Enchong Luan, Wenting School of Control and Computer Engineering North China Electric Power University Beijing China College of Intelligence Science and Technology National University of Defense Technology Changsha China

Given the uncertain, random, and volatile characteristics of power load, accurate forecasting of power load becomes challenging. To address this issue, this paper proposes an optimized prediction model by using a modified Adaptive White Noise Complete Integrated Empirical Modal Decomposition Algorithm (ICEEMDAN) and the improved Whale Optimization Algorithm (IWOA) for bidirectional short-term and long-term memory networks (BiLSTM). First of all, Australian power load data is preprocessed in this study. Then, the load data is decomposed into a series of sequences by using ICEEMDAN. After that, the improved whale algorithm is employed to analyze the BiLSTM super parameter optimization. Finally, each decomposed component is input into the IWOA-BiLSTM model for load forecasting. The results demonstrate that the proposed algorithm achieves higher accuracy in power load forecasting, compared to individual benchmark models and most portfolio models, indicating its applicability and practical value. © 2023 Published under licence by IOP Publishing Ltd.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Optimal denial-of-service attack scheduling for remote state estimation via sequential observations 43

Optimal denial-of-service attack scheduling for remote state...

引用

43rd Chinese control Conference, CCC 2024

作者： Yang, Xinxin Ni, Yuqing Chen, Xiaomeng Chen, Shan Liu, Fei Jiangnan University The Key Laboratory of Advanced Process Control for Light Industry Ministry of Education School of Internet of Things Engineering Wuxi214122 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong999077 Hong Kong

ISBN: (纸本)9789887581581

This study investigates the optimal allocation problem of attack energy in multi-system remote state estimation for Cyber-Physical Systems (CPSs). We consider a scenario where there are M independent systems, each equipped with a remote sensor monitoring system. The local estimates from these systems are sent to a remote estimator through a packet loss channel. The objective of the attacker is to degrade the communication channel between the sensors and the remote estimator. Due to capacity limitations, the attacker is restricted to attacking at most one out of M channels. We incorporate interference from other sensors or interference sources into the communication model based on the SINR (Signal-to-Interference-plus-Noise Ratio) model. It should be noted that the same attack power can lead to different packet loss rates in different network environments. From the attacker's perspective, the goal is to find the optimal attack strategy that maximizes the average estimation error of the remote estimator. Given the uncertainties of wireless network environments, we employ the sequentially-observed Markov decision process (SOMDP) framework to solve the problem. By observing the wireless channels, we gather additional information and incorporate it into the decision-making policy, resulting in better performance than using a standard Markov decision process (MDP). The simulation results support our theoretical findings. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

Futures Price Forecasting Based on LSTM Model Using Public Opinion Sentiment Analysis 42

Futures Price Forecasting Based on LSTM Model Using Public O...

引用

42nd Chinese control Conference, CCC 2023

作者： Shi, Panfeng Song, Shifan Lang, Qi Liu, Xiaodong School of Control Science and Engineering Dalian University of Technology Dalian116024 China School of Computer Science and Information Technology Northeast Normal University Changchun130117 China

ISBN: (纸本)9789887581543

As the economy continues to develop and the futures market grows, more and more attention is being paid to the subject of futures price forecasting. The factors influencing the futures market are complex, and the existing forecasting models tend to ignore the acquisition of information other than market information. Therefore, this paper proposes a futures price forecasting model based on sentiment analysis of online public opinions. Several futures products are selected for training and validation of the model, and the Chinese posts in the futures bar are used as input for public opinion, which is processed by the investor sentiment analysis fusion module to obtain sentiment values as a priori information for the task. Three groups of control experiments are set up to verify the validity of the proposed model and to compare the effect of sentiment feature fusion. Finally, the experimental results show that the proposed model incorporating public opinion gets better results in the selected futures product price prediction task. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Time series analysis

来源：评论

学校读者我要写书评

暂无评论

A Spectral Mask - Based on Method for Applying into Generalized Sidelobe Canceller Beamformer 12th

A Spectral Mask - Based on Method for Applying into Gener...

引用

Proceedings of the12th International Conference on Information Technology and its Applications, CITA 2023

作者： Huy, Nguyen Ba Anh, Pham Tuan The, Quan Trong Faculty of Control Systems and Robotics University ITMO St.Petersburg Russia Faculty of Software Engineering and Computer Systems University ITMO St.Petersburg Russia

ISBN: (纸本)9783031368851

The problem of signal processing is extracting the desired target speaker while suppressing the annoying background noise in complex recording situation, where exists third-party talker, transport vehicle or interference, noise. Speech quality or speech intelligibility are the major characteristics, which confirm the effectiveness of processed method. In speech applications, such as hearing-aids, hands-free telephony, teleconferencing, acoustic instruments, microphone array (MA) is applied for increasing the speech quality. MA uses the spatial response, the priori information about direction - of - arrival (DOA) of interest signal, the properties of recording environment to obtain speech components and remove noise. Generalized Sidelobe Canceller (GSC) is one of the most widely exploited in microphone array beamforming, due to its convenience and effective noise reduction. However, in several situations, the performance of GSC beamformer is often degraded, because of the imprecise DOA. In this paper, the authors suggested an additive spectral mask for improving the evaluation of GSC beamformer. The resulting experiment proves the received advantage of the author’s proposed algorithm to increase in the term of the signal-to-noise ratio (SNR). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Deep Reinforcement Learning-based Computing Offloading and Resource Allocation Algorithm in Internet of Vehicles 11

Deep Reinforcement Learning-based Computing Offloading and R...

引用

2023 IEEE 11th International Conference on Information, Communication and Networks, ICICN 2023

作者： Yuan, Yiping Chen, Xin Jiao, Libo Wang, Yijie Beijing Information Science & Technology University School of Control Science and Engineering Beijing China Beijing Information Science & Technology University School of Computer Science Beijing China

ISBN: (纸本)9798350314014

With the rapid emergence of the Internet of Vehicles (IoV) and 6G networks, the exponential growth in data traffic has presented a formidable challenge to the limited computational capabilities of in-vehicle devices. To overcome this challenge, mobile edge computing (MEC) offers a viable solution by offloading computationally intensive tasks to the edge servers. In this study, we design a novel joint optimization approach that leverages deep reinforcement learning (DRL) to inform decisions on computational offloading, energy consumption, and resource allocation. Our proposed scheme considers the involvement of both the base station (BS) and road side units (RSUs) in providing computing resources to the user while simultaneously minimizing energy consumption and reducing latency of computational tasks. Our simulations unequivocally establish the efficacy of the Deep Reinforcement Learning-based computing offloading and resource allocation (DCORA) algorithm. The proposed DCORA algorithm outperforms alternative baseline schemes by approximately 15% in direct comparison. © 2023 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：