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43rd Chinese control Conference, CCC 2024

作者： Li, Haodong Yin, Jiateng Tang, Tao D'Ariano, Andrea You, Mengxing Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Beijing100044 China Beijing Jiaotong University School of Systems Science Beijing100044 China RomaTre Universily Computer Science and Aeronautical Technologies Engineering Department of Civi Rome0018511 Italy Nanchang Rail Transit Group CO. Ltd Jiangxi330038 China

ISBN: (纸本)9789887581581

Train platooning, which allows multiple train units to be virtually coupled into a platoon with very short following distances, has become an emerging technology in railway industry. Our study investigates the energy-efficient operation of train platoons to reduce the energy consumption of trains while satisfying time-varying passenger demands in practice. We develop a mixed integer programming (MIP) model to optimize the timetable, running speed and coupling strategies of trains. Considering that the small-size train platoons consume much less energy but can serve fewer passengers, our model involves bi-objectives, i.e., to minimize the passenger waiting time and to minimize the overall energy consumption of trains. We also construct a series of model constraints to limit the movement of trains as well as the time-dependent flows of passengers, since a part of passengers during the peak period may have to wait for a longer time due to the capacity limitation of different sizes of trains. Finally, we conduct real-world case studies on the Beijing subway Yizhuang line to verify the effectiveness of our approach. The results indicate that the energy-efficient operation of train platoons can achieve a better trade-off between service quality and system energy consumption. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Energy efficiency

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Traffic Pattern Classification in Smart Cities Using Deep Recurrent Neural Network

arXiv

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arXiv 2024年

作者： Ismaeel, Ayad Ghany Krishnadas, J. Manishankar, S. Natarajan, Yuvaraj Mahmood, Sarmad Nozad Alani, Sameer Shather, Akram H. Computer Technology Engineering College of Engineering Technology Al-Kitab University Kirkuk36001 Iraq Department of Computer Science and Engineering Sahrdaya College of Engineering and Technology Thrissur Kodakara680684 India Department of Computer Science and Engineering Sri Shakthi Institute of Engineering and Technology Coimbatore641062 India Electronic and Control Engineering Techniques Technical Engineering College Northern Technical University Kirkuk36001 Iraq Computer Center University of Anbar Ramadi55431 Iraq Department of Computer Engineering Technology Al-Kitab University Altun Kopru Kirkuk36001 Iraq

This paper examines the use of deep recurrent neural networks to classify traffic patterns in smart cities. We propose a novel approach to traffic pattern classification based on deep recurrent neural networks, which can effectively capture traffic patterns' dynamic and sequential features. The proposed model combines convolutional and recurrent layers to extract features from traffic pattern data and a SoftMax layer to classify traffic patterns. Experimental results show that the proposed model outperforms existing methods regarding accuracy, precision, recall, and F1 score. Furthermore, we provide an in-depth analysis of the results and discuss the implications of the proposed model for smart cities. The results show that the proposed model can accurately classify traffic patterns in smart cities with a precision of as high as 95%. The proposed model is evaluated on a real-world traffic pattern dataset and compared with existing classification methods. © 2024, CC BY-NC-ND.

关键词： Classification (of information)

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Disturbance-Rejection Guaranteed Mpc Design for Mimo systems with Application to a 2-Dof Helicopter

SSRN

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SSRN 2024年

作者： Zhao, Jingyu Liu, Shaojie Xue, Wenchao Ding, Yanjun Li, Donghai State Key Laboratory of Power Systems Department of Energy and Power Engineering Tsinghua University Beijing100084 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

This paper presents a hierarchical control strategy for a broad class of multi-input multi-output (MIMO) uncertain systems without a nominal identified model. The core idea is to utilize Active Disturbance Rejection control (ADRC) to construct an equivalent desired dynamic model, which avoids the complex model identification for MIMO systems and improves the uncertainty rejection capability of the predictive controller. At the foundational layer, the extended state observer is constructed to timely estimate the uncertainties in the coupling of subsystems, enforcing these into an equivalent desired plant through dynamic compensation linearization. The modified input-output pair models depend solely on compensation law parameter and can directly serve as the prediction model for multi-step prediction and centralized receding optimization, ensuring optimal control of the MIMO system. The strategy is validated on typical MIMO systems of various sizes (2×2, 3×3, 8×8), including minimum phase, unstable, higher-order, and time-delay subsystems. Monte Carlo simulations quantitatively assess the enhanced robustness. Additionally, a 2-DOF helicopter experiment system, characterized by nonlinear time-varying coupling between attitude angles is used to evaluate the servo-regulatory performance of the proposed strategy. Results demonstrate the effectiveness of our controller in both nominal and mismatch model scenarios. © 2024, The Authors. All rights reserved.

关键词： Disturbance rejection

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Analyzing α-divergence in Gaussian Rate-Distortion-Perception Theory

Analyzing α-divergence in Gaussian Rate-Distortion-Percepti...

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IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Martha V. Sourla Giuseppe Serra Photios A. Stavrou Marios Kountouris School of Electrical & Computer Engineering Technical University of Crete Chania Greece Communication Systems Department EURECOM France Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada Spain

ISBN: (数字)9798350393187

ISBN: (纸本)9798350393194

The problem of the estimation of the information rate-distortion-perception function (RDPF), which is a relevant information-theoretic quantity in goal-oriented lossy compression and semantic information reconstruction, is investigated here. Specifically, we study the RDPF tradeoff for Gaussian sources subject to a mean-squared error (MSE) distortion and a perception measure that belongs to the family of α-divergences. Assuming a jointly Gaussian RDPF, which forms a convex optimization problem, we characterize an upper bound for which we find a parametric solution. We show that evaluating the optimal parameters of this parametric solution is equivalent to finding the roots of a reduced exponential polynomial of degree α. Additionally, we determine which disjoint sets contain each root, which enables us to evaluate them numerically using the well-known bisection method. Finally, we validate our analytical findings with numerical results and establish connections with existing results.

关键词： Wireless communication Upper bound Semantics Measurement uncertainty Estimation Distortion Polynomials Convex functions Distortion measurement Information theory

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Distributed Generalized Nash Equilibrium Seeking for Constrained N-Cluster Games with Second-Order Dynamics

Distributed Generalized Nash Equilibrium Seeking for Constra...

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IEEE Conference on Decision and control

作者： Yan Zhao Min Meng Xiuxian Li Jia Xu Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems and Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper studies N-cluster games with secondorder dynamics, wherein the players’ decisions are restricted by local set constraints and nonlinear coupled inequality constraints. The presence of second-order dynamics coupled with constraints leads to difficulties in the design and analysis of generalized Nash equilibrium (GNE) seeking algorithms, since it may be impossible to directly determine the decisions of players based on their control inputs. To facilitate the autonomous execution of N-cluster game tasks through secondorder players, by employing state feedback, projection, primaldual, dynamic average consensus, and passivity methods, a distributed algorithm is proposed to find the variational GNE of the studied games, under which the players’ decisions can satisfy the set constraints all the time. Additionally, the algorithm’s convergence is rigorously analyzed, and its efficacy is validated by a simulation example.

关键词： State feedback Heuristic algorithms Games Nash equilibrium Time factors Distributed algorithms Convergence

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A polynomial quantum computing algorithm for solving the dualization problem for positive boolean functions

A polynomial quantum computing algorithm for solving the dua...

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2023 International Workshop on AI for Quantum and Quantum for AI, AIQxQIA 2023

作者： Mezzini, Mauro Gomez, Fernando Cuartero Lopez Pelayo, Fernando Paulet Gonzalez, Jose Javier de la Cruz Calvo, Hernan Indibil Pascual, Vicente Department of Education Roma Tre University Rome00185 Italy Computing Systems Department Faculty of Computer Science Engineering University of Castilla-La Mancha Albacete02071 Spain Quantum Computing Department Qsimov Quantum Computing S.L Talavera de la Reina Toledo45600 Spain

Given two positive Boolean functions ∱ : {0, 1}n → {0, 1} and g : {0, 1}n → {0, 1} expressed in their positive irredundant DNF Boolean formulas, the dualization problem consists in determining if g is the dual of ∱, that is if ∱(x1, . . ., xn) = g(x1, . . . xn) for all (x1, . . . xn) ∈ {0, 1}n. In this paper we present a quantum computing algorithm that solves the dualization problem in polynomial time with respect to the dimensions of the DNF expressions. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Boolean Functions Computational complexity Dualization Quantum Algorithm

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Deceptive Hotel Review Detection: An Ensemble Learning Framework

Deceptive Hotel Review Detection: An Ensemble Learning Frame...

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Information Technology (OCIT), OITS International Conference on

作者： Siddharth Bhangale Pradeep Kumar Roy Department of Computer Science and Engineering Indian Institute of Information Technology (IIIT) Surat Gujarat India Decision Science and Information Systems Area Indian Institute of Management Nagpur India

ISBN: (数字)9798331510404

ISBN: (纸本)9798331510411

Electronic Word of Mouth (eWoM) becomes a key player for e-commerce platforms to upgrade or downgrade product or service value. Currently, reviews are one of the favorable sources for individuals to decide their opinions about products, hotels, places, transport services, food quality, and many others. The digital era yields positives and negatives; positive includes fast access to multiple people's opinions in terms of legitimate reviews, whereas negative includes the existence of deceptive reviews inside the total review. Deceptive reviews may be used to create a biased impact on humans about the brand or services. Therefore, detecting such biased reviews from online platforms is an urgent requirement. To address the issues, a weighted ensemble model was developed in this research, which was trained and tested on the gold standard dataset. The model's outcome achieved approx 5% higher accuracy for detecting deceptive reviews than baseline models.

关键词： Accuracy Reviews Oral communication Feature extraction Ensemble learning Electronic commerce Information technology

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Effective Intrusion Detection and Classification using Fuzzy Rule based Classifier in Cloud Environment 1

Effective Intrusion Detection and Classification using Fuzzy...

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1st IEEE International Conference on Automation, Computing and Renewable systems, ICACRS 2022

作者： Veena, C. Ramalakshmi, S. Bhoopathy, V. Bhosale, Minakshi Dattatraya Magadum, C.G. Abirami, S.K. Ghatkesar Telangana Hyderabad India Puducherry Karaikal India Department of Computer Science and Engineering Malla Reddy College of Engineering Telangana Secunderabad India Faculty of MCA Yashoda Technical Campus Maharashtra Satara India Smt. Kasturbai Walchand College Maharashtra Sangli India Department of Computer Science and Business Systems Sri Eshwar College of Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9781665460842

Cloud computing (CC) is the demonstration of the technology that makes use of the substructure for computing in a proficient fashion. This sort of computing offers great quantity of consequences in augmenting the productivity that verifies the risk handling management and decreases the cost. Intrusion detection system (IDS) is widely applied for detecting malicious actions in its host and the communication network. IDS is a procedure of discovering activities that take place in a network and attempts to fulfill the confidentiality, network, or security accessibility to smear the trust procedure. This article introduces an Effective Intrusion Detection and Classification using Fuzzy Rule based Classifier (EIDC-FRC) model in Cloud Environment. The goal of the presented EIDC-FRC model is to determine the occurrence of intrusions and normal data traffic in the cloud environment. In order to achieve this, the presented EIDC-FRC model applies FRC for data classification process. The parameter tuning of the FRC model is performed using enhanced bird swarm algorithm (EBSA). The FRC is an effective model in pattern recognition that offers effective outcomes by the use of linguistic labels in the antecedents of the rules. The simulation analysis of the EIDC-FRC model ensured the enhancements of the presented approach compared to recent state of art approaches. © 2022 IEEE

关键词： Machine learning

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Van der Waals integration inch-scale 2D MoSe_(2) layers on Si for highly-sensitive broadband photodetection and imaging

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Nano Research 2023年第8期16卷 11422-11429页

作者： Yupiao Wu Shuo-En Wu Jinjin Hei Longhui Zeng Pei Lin Zhifeng Shi Qingming Chen Xinjian Li Xuechao Yu Di Wu School of Physics and Microelectronics and Key Laboratory of Material PhysicsZhengzhou UniversityZhengzhou 450052China Department of Electrical and Computer Engineering University of California San DiegoLa JollaCA 92093USA School of Microelectronics Science and Technology Sun Yat-Sen UniversityZhuhai 519082China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China

As one of the most promising materials for two-dimensional transition metal chalcogenides(2D TMDs),molybdenum diselenide(MoSe_(2))has great potential in photodetectors due to its excellent properties like tunable bandgap,high carrier mobility,and excellent air *** 2D MoSe_(2)-based photodetectors have been reported to exhibit admired performance,the large-area 2D MoSe_(2)layers are difficult to be achieved via conventional synthesis methods,which severely impedes its future ***,we present the controllable growth of large-area 2D MoSe_(2)layers over 3.5-inch with excellent homogeneity by a simple post-selenization ***,a high-quality n-MoSe_(2)/p-Si van der Waals(vdW)heterojunction device is in-situ fabricated by directly growing 2D n-MoSe_(2)layers on the patterned p-Si substrate,which shows a self-driven broadband photoresponse ranging from ultraviolet to mid-wave infrared with an impressive responsivity of 720.5 mA·W^(−1),a high specific detectivity of 10^(13) Jones,and a fast response time to follow nanosecond pulsed optical *** addition,thanks to the inch-level 2D MoSe_(2)layers,a 4×4 integrated heterojunction device array is achieved,which has demonstrated good uniformity and satisfying imaging *** large-area 2D MoSe_(2)layer and its heterojunction device array have great promise for high-performance photodetection and imaging applications in integrated optoelectronic systems.

关键词： molybdenum diselenide large-area synthesis broadband photodetector integrated device array van der Waals(vdW)heterojunction

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On the computation of the minimum set of reactions for optimal growth in constraint-based models

On the computation of the minimum set of reactions for optim...

引用

IEEE Conference on Decision and control

作者： Alexandru Oarga Jorge Júlvez Department of Computer Science and Systems Engineering University of Zaragoza Zaragoza Spain

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

Technical advances in sequencing have allowed the reconstruction of metabolic models of multiple microorganisms, which have proven useful in advancing metabolic engineering and drug discovery. Optimization methods have provided a way to accurately predict flux phenotypes of various unicellular organisms and their response to gene knockouts. Despite the broad application of these methods, the role that different biochemical reactions have in providing robustness and flexibility has not been studied extensively. In this work, a method is presented to identify those sets of reactions that are essential for growth and those that are redundant and therefore account for the robustness of metabolism. The problem of computing a minimum set of reactions that can produce optimum growth is formally stated. It is proven that such a problem is NP-complete and a technique to reduce the search space of the problem is proposed. The presented approach is experimentally applied in various genome-scale models. The contribution of this work is to provide insight into the roles that different reactions play in the production of growth and to propose methods that can be directly applied in model curation and analysis.

关键词： Sequential analysis Pathogens Microorganisms Computational modeling Redundancy Optimization methods Genomics

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