检索结果-内蒙古大学图书馆

A calorimetric approach to fast entropy-variations extraction for lithium-ion batteries using optimized galvanostatic intermittent titration technique

引用

JOURNAL OF POWER SOURCES ADVANCES 2022年 16卷

作者： Ahmad, Abdul Muiz Thenaisie, Guillaume Lee, Sang-Gug Korea Adv Inst Sci & Technol KAIST Sch Elect Engn Daejeon South Korea

A fast entropy-variations (delta S) extraction method has been proposed based on calorimetry, which determines the heat associated with delta S by analyzing the electro-thermal response of a battery to a sequence of constant current pulses, i.e., the galvanostatic intermittent titration technique (GITT). The rest times in GITT are reduced by only considering limited relaxation of the ionic concentration gradients inside the battery after the current in-terruptions while completely ignoring the thermal equilibrium conditions inside the calorimeter. The resulting thermal signal of the battery is analyzed using an algorithm that adopts exponential regression to characterize the generated heat energy corresponding to each current pulse. Additionally, the polarization heat inside the battery is investigated by taking into account the initial presence of the concentration gradients when a current pulse is applied. Thus, the optimized rest times between the successive current pulses can reduce the mea-surement time manyfold compared to the previously reported methods, which require the battery to reach both electrochemical and thermal equilibriums. This work shows that the delta S profiles of a 1 Ah NMC811/graphite pouch cell with 2.5% state of charge (SOC) resolution can be extracted at least three times faster than the method with unoptimized rest times, in a highly repeatable manner.

关键词： Lithium -ion batteries Calorimetry Entropy GITT optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Towards an effective deep learning-based intrusion detection system in the internet of things

引用

TELEMATICS AND INFORMATICS REPORTS 2022年 7卷

作者： Pampapathi, B. M. Guptha, M. Nageswara Hema, M. S. Sri Venkateshwara Coll Engn Dept Comp Sci & Engn Bengaluru Karnataka India Anurag Univ Dept Informat Technol Hyderabad Telangana India

Distributed Sensor Networks play a vital role in the day-to-day world of computing applications, from the cloud to the Internet of Things (IoT). These computing applications devices are normally attached with the microcontrollers like Sensors, actuators, and Adriano network connectivity. Defensive network with an Intrusion Detection System thus serves as the need of modern networks. Despite decades of inevitable development, the Intrusion Detection System is still a challenging research area as the existing Intrusion Detection System operates using signature-based techniques rather than anomaly detection. The existing Intrusion Detection System are thus facing challenges for improvement in Intrusion Detection, Handling heterogeneous data sources is hard for discovering zero-day attacks in IoT networks. This paper presents Filtered Deep Learning Model for Intrusion Detection with a Data Communication approach. The proposed model is composed of five phases: Initialization of Sensor Networks, Cluster Formation in addition to Cluster Head Selection, Connectivity, Attack Detection, and Data Broker. The proposed Model for Intrusion Detection was found to outperform the existing Deep Learning Neural Network and Artificial Neural Network. Experimental results showed a better result of 96.12% accuracy than the dominant algorithms.

关键词： Filtered deep learning neural network Modified K-means algorithm Advanced message queuing protocol Levy flight based Elephant herding optimization algorithm Message queuing telemetry transport

来源：评论

学校读者我要写书评

暂无评论

Semantic communication-based convolutional neural network for enhanced image classification

Franklin Open

引用

Franklin Open 2024年 9卷

作者： Guler, Nivine Hazem, Zied Ben Department of Computer Science University of Central Asia Naryn 722918 Kyrgyzstan Automation and Sustainability Research Centre (ASRC) Department of Mechatronics Engineering College of Engineering (COE) University of Technology Bahrain Salmabad Bahrain

In AI-IoT environments, the traditional centralized cloud computing approach leads to high network transmission volumes and communication delays, negatively affecting intelligent task performance. This study addresses these issues by introducing an innovative semantic communication system model for intelligent tasks, leveraging deep learning techniques. The research focuses on image classification tasks constrained by bandwidth and delay in AI-IoT scenarios. The proposed model features a tailored semantic communication network architecture, where image feature maps are extracted on IoT devices. These semantic relations are then compressed based on the extracted feature maps to reduce power consumption on IoT devices and mitigate communication transmission pressures. Simulations and comparative analyses of various network performance metrics show that the proposed semantic communication system improves image classification accuracy by 90%% at low signal-to-noise ratios compared to traditional methods. With an 80%% compression ratio, the classification accuracy loss is minimal—within 2%%—when the signal-to-noise ratio exceeds 0. Additionally, at a signal-to-noise ratio of 20, the semantic compression transmission scheme enhances classification accuracy by 30%% compared to random compression. Moreover, the proposed system outperforms traditional approaches in execution time by approximately 80%%. © 2024 The Author(s)

关键词： CNN IoT optimization algorithm Semantic communication

来源：评论

学校读者我要写书评

暂无评论

Multi-objective scheduling and optimization for smart energy systems with energy hubs and microgrids

引用

Engineering Science and Technology, an International Journal 2024年 51卷

作者： Yanliang Wang Bo Wang Hashem Farjam School of Economics and Management Yanshan University Qinhuangdao 066004 China EED Sun-Life Company Baku Azerbaijan

This paper introduces a novel model for optimizing microgrid systems by integrating multi-purpose renewable energy (MEM) and cutting-edge technologies, including electric vehicles (EVs). The proposed MEM demand response programs encompass various energy sources such as wind energy, multi-carrier energy storage technologies, boilers, combined heat and cooling units, EVs, P2G (power-to-gas), and demand response capabilities. The primary objective is to minimize the total operational cost of the microgrid system. A distinctive aspect of the proposed method lies in considering the prices of all energy carriers as unknown variables. Market prices are integrated into the modeling process, incorporating scenarios with reasonable probabilities and taking into account demand-side management programs. Moreover, the model allows for customizable programming of different parts of the multi-energy microgrids, with a focus on maintaining convexity principles for the operating area of each CHP (combined heat and power) unit. To tackle the unique complexity of this optimization problem, a developed blue whale optimization algorithm is proposed. This algorithm builds upon the main whale optimization algorithm (WOA), a promising population-based optimization approach. However, the effectiveness of WOA heavily relies on the careful setting of exploration and exploitation parameters, which may lead to being trapped in local optima. To address this challenge, the paper introduces a self-adaptation modification based on wavelet theory to enhance the WOA's performance. The proposed model and optimization method are thoroughly evaluated through simulation studies for different scenarios, showcasing their efficacy in achieving cost-efficient and sustainable microgrid operation. The combination of MEM and emerging technologies like EVs, along with the improved optimization algorithm, marks a significant contribution to advancing the planning and operation of microgrid systems towards low-cos

关键词： Multi-energy microgrids Demand side management optimization algorithm Economic planning Combined energy system Renewable resources

来源：评论

学校读者我要写书评

暂无评论

Parameter inversion of nonlinear constitutive model of rockfill materials using observed deformations after dam construction

引用

ROCK AND SOIL MECHANICS 2014年 35卷 61-+页

作者： Li Shou-ju Zhang Jun Liang Jin-quan Sun Zhen-xiang Dalian Univ Technol State Key Lab Struct Anal Ind Equipment Dalian 116024 Liaoning Peoples R China Liaoning Pushihe Pumped Storage Co Ltd Dandong 118000 Liaoning Peoples R China

In order to determine nonlinear constitutive model parameters of rockfill materials, the inversion procedure based on response surface method is proposed. The sequential impoundment processes of concrete-faced rockfill dam are simulated by using nonlinear finite element method. The response surface functions of forecasting dam settlement for every observing point are presented. The coefficients of response surface function are calculated. Model parameters of nonlinear constitutive relationship of rockfill materials are determined using observed deformations after dam construction and response surface functions of forecasting dam settlement. The practical applications show that the proposed inversion procedure is of higher computing efficiency;and the forecasted dam settlements agree well with observed values.

关键词： model parameter inversion concrete-faced rockfill dam constitutive model dam settlements response surface optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Application of algorithms in optimal operation of natural gas pipeline network

Xinan Shiyou Xueyuan Xuebao/Journal of Southwestern Petroleu...

引用

Xinan Shiyou Xueyuan Xuebao/Journal of Southwestern Petroleum Institute 2006年第1期28卷 79-82页

作者： Yang, Yi Li, Chang-Jun Southwest Petroleum Institute Chengdu 610500 China

The mathematical models about the optimal operation of natural gas pipeline network were described, including two kinds of objective functions: one is about maximum return and the other is about maximum flow of pipeline network as well as eight constraint conditions. Three optimized algorithms (linearization optimized algorithm, complex optimized algorithm and feasible direction optimized algorithm) to resolve that models through researching kinds of classic optimized algorithms were determined, and the application program was written. These three optimized algorithms were analyzed and compounded, and the result showed the difference of these three optimized algorithm means's result was about 1%. The example showed the linearization optimized algorithm possesses faster searching speed, better result and practicability.

关键词： Application Natural gas pipe network Optimal operation optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

New Approaches to Speech Enhancement Using Phase Correction in Wiener Filtering

New Approaches to Speech Enhancement Using Phase Correction ...

引用

International Symposium on Telecommunications

作者： P. Fardkhaleghi M. H. Savoji Electrical and Computer Engineering Faculty - Shahid Beheshti University

ISBN: (纸本)9781424481835

Typical speech enhancement algorithms that operate in the Fourier domain only modify the magnitude component of the noisy speech. It is commonly understood that the phase component is perceptually unimportant, and thus, it is passed directly to the output. Nevertheless, it has been reported in recent experiments that the Short-Time Fourier Transform (STFT) phase spectrum contributes significantly to speech intelligibility. Motivated by this, we investigated the role of phase spectrum in speech enhancement using Wiener filtering and Martin's minimum statistics. In this paper we report on results obtained using optimization algorithms, for phase correction of each processed frame, that intend to match the waveform of the zero-phase Wiener filtered speech to the conventional filter output obtained with noisy phase characteristic. No a priori information on the original phase is assumed. We show that better results are achieved using phase correction for different noise types. Different criteria are used for optimization with results similar to the case when the actual clean speech phase is at hand. Almost as good results are also obtained when minimizing the Wiener filter impulse response dispersion. The achieved improvement is assessed through different measurements such as signal to noise ratio (SNR), Segmental signal to noise ratio, and Perceptual Estimation of Speech Quality (PESQ).

关键词： Speech enhancement Phase correction optimization algorithm Wiener filtering

来源：评论

学校读者我要写书评

暂无评论

Power Transformer Fault Classification by Combining Genetic Reduction with Optimized Multilayer Support Vector Machine

Power Transformer Fault Classification by Combining Genetic ...

引用

IEEE Innovative Smart Grid Technologies - Asia

作者： H.Z. Li S.X. Chen T. Qian W.H. Tang Q.H. Wu Foshan Power Supply Bureau of Guangdong Province No. 1 Fenjiang South Rd. Chancheng District Foshan 528000 China School of Electric Power Engineering South China University of Technology Guangzhou 510641 China

ISBN: (纸本)9781509012398

This paper presents a novel fault diagnosis model for oil-immersed power transformers based on dissolved gas analysis. The model is rooted on the theories of rough set and support vector machine. A fitness function based on attribute dependence is developed to identify fault features to improve classification accuracy of transformer fault samples by using Genetic algorithm. To get improved classification performance, grid search, genetic algorithm and particle swarm optimization are applied to search parameters of support vector machine. Compared with modified Rogers and back propagation neural network, the superiority of the established model is verified.

关键词： genetic reduction multilayer support vector machine optimization algorithm rough set transformer fault diagnosis

来源：评论

学校读者我要写书评

暂无评论

Energy-aware traffic routing and resource allocation in WDM optical networks

Energy-aware traffic routing and resource allocation in WDM ...

引用

SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference

作者： Nereida L. Valdivia Monica de Lacerda Rocha Amilcar Careli Cesar University of Sao Paulo School of Engineering of Sao Carlos

ISBN: (纸本)9781467394932

The growth of data traffic in telecommunication networks has increased the power consumption and its saving has become a key issue in planning and management of telecommunication networks. On the other hand, to guarantee availability and reliability, core optical networks have redundant resources to support extra traffic demand or infrastructure fault. The dedicated path protection (DPP) is an effective and widely used scheme to manage fault. However, networks supporting such strategy keep protection paths in active state, even in conditions where they are not carrying traffic, thus consuming power unnecessarily. To overcome this inefficiency, an effective strategy for decreasing wasted power is an adaptive traffic routing based on sleep mode, which is a state of low power consumption able to change quickly to an active state. The strategy is to route the traffic in order to maximize the amount of network components used by protection paths that can be set in sleep mode. In general, reported strategies reduce power consumption at the expense of increasing blocking probability. In this article, we address the power saving problem in WDM networks using DPP scheme proposing a wider resource search routing and wavelength assignment (RWA), named in-depth (ID-) RWA. Computer simulations based on the COST239 topology showed that the ID-RWA has better performance regarding the compromise between blocking probability and power consumption. Moreover, it manages to decrease the blocking probability while boosting the energy awareness.

关键词： Optical network WDM RWA Energy saving optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Multi-Vth technique based on potential critical paths for NBTI effect and leakage tradeoff

Multi-Vth technique based on potential critical paths for NB...

引用

IEEE International Conference on Electronic Measurement & Instruments

作者： Zhang Yao Yi Maoxiang Wang Keke Wu Qingwu Ding Li Liang Huaguo Department of Electronic Science and Applied Physics Hefei University of Technology Hefei 230009 Hefei China

NBTI-induced PMOS transistor aging has become an important influence factor of the circuit reliability in the current technological dimension. In this paper, Multi-Vth technique based on potential critical paths for NBTI effect and leakage tradeoff is proposed. The potential critical paths can be found at the preset timing margin and the critical gates in the potential critical paths can be replaced with the low threshold voltage type through the optimization algorithm mentioned in our paper. The experimental results on ISCAS85 benchmark circuits at 45nm node show that the after-aging delay improvement rate is up to 12.95%, which is obviously better than the current multi-threshold voltage scheme. Simultaneously, the leakage power overhead is less. Our method is more effective for the larger circuit in the anti-aging aspect.

关键词： Negative bias temperature instability (NBTI) potential critical paths Multi-threshold voltage optimization algorithm

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：