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A Deep Reinforcement Learning Based real-time Solution Policy for the Traveling Salesman Problem

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2023年第6期24卷 5871-5882页

作者： Ling, Zhengxuan Zhang, Yu Chen, Xi Zhejiang Univ Coll Control Sci & Engn Hangzhou 310027 Peoples R China Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China

The rapid development of logistics and navigation has led to increasing demand for solving route optimization problems in real-time. The traveling salesman problem (TSP) tends to require fast and reliable online solutions, which may not be met by traditional iterative optimization algorithms. In this work, a real-time solution policy is proposed for TSP. The idea is to build a mapping between city information and optimal solutions using deep neural networks. Therefore, when given a new set of city coordinates, the optimal route can be directly and quickly calculated without iteration. Considering the recent advancement in computer vision with deep convolutional neural networks (DCNNs), an image representation is proposed to convert TSP to a computer vision problem. A problem decomposition method is introduced to reduce the mapping complexity. Taking advantage of the powerful fitting capabilities of DCNN, a deep reinforcement learning method is designed without any labeling requirement. The proposed method is superior for real-time applications compared with other algorithms.

关键词： Urban areas real-time systems Heuristic algorithms Reinforcement learning Neural networks Training Image representation Machine learning deep reinforcement learning real-time algorithm deep convolutional neural network traveling salesman

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Fast parallel blur detection on GPU

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JOURNAL OF real-time IMAGE PROCESSING 2020年第4期17卷 903-913页

作者： Giang Son Tran Thi Phuong Nghiem Burie, Jean-Christophe Univ Sci & Technol Hanoi Vietnam Acad Sci & Technol ICTLab 18 Hoang Quoc Viet Hanoi Vietnam Sorbonne Univ IRD UMMISCO Unite Modelisat Math & Informat Syst Complexes F-93143 Bondy France Univ La Rochelle L3i Lab Av M Crepeau F-17042 La Rochelle 1 France

Blur detection, a task to determine whether an image is blurred or not, is very helpful in various applications of image processing and computer vision. In this paper, we propose a novel method to accelerate blur detection algorithms based on Haar wavelet transform. The method decouples data dependency to gain fast 3-level Haar wavelet transform. With the obtained independence, the blur detection steps can be performed in parallel using native GPU thread blocks. We evaluated our proposed method on embedded devices, desktop and server. Our experiments show that on desktop and server, the proposed method obtains a huge performance speedup. On embedded devices, our GPU-based 3-level Haar wavelet transform is up to 4.9 times better performance and 4.3 times better power efficiency than CPU-based blur detection algorithms.

关键词： Image blur detection Haar wavelet transform GPU parallelism real-time algorithm Embedded device

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real-time Residential-Side Joint Energy Storage Management and Load Scheduling With Renewable Integration

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IEEE TRANSACTIONS ON SMART GRID 2018年第1期9卷 283-298页

作者： Li, Tianyi Dong, Min Univ Ontario Inst Technol Dept Elect Comp & Software Engn Oshawa ON L1H 7K4 Canada

We consider joint energy storage management and load scheduling at a residential site with integrated renewable generation. Assuming unknown arbitrary dynamics of renewable source, loads, and electricity price, we aim at optimizing the load scheduling and energy storage control simultaneously in order to minimize the overall system cost within a finite time period. Besides incorporating battery operational constraints and costs, we model each individual load task by its requested power intensity and service durations, as well as the maximum and average delay requirements. To tackle this finite time horizon stochastic problem, we propose a real-time scheduling and storage control solution by applying a sequence of modification and transformation to employ Lyapunov optimization that otherwise is not directly applicable. With our proposed algorithm, we show that the joint load scheduling and energy storage control can in fact be separated and sequentially determined. Furthermore, both scheduling and energy control decisions have closed-form solutions for simple implementation. Through analysis, we show that our proposed real-time algorithm has a bounded performance guarantee from the optimal T-slot look-ahead solution, and is asymptotically equivalent to it as the battery capacity and time period goes to infinity. The effectiveness of joint load scheduling and energy storage control by our proposed algorithm is demonstrated through simulation as compared with alternative algorithms.

关键词： Load scheduling energy storage renewable generation real-time algorithm stochastic optimization finite time horizon

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The WQN algorithm for EEG Artifact Removal in the Absence of Scale Invariance

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2024年 72卷 2663-2676页

作者： Dora, Matteo Jaffard, Stephane Holcman, David Ecole Normale Super IBENS UMR8197 PSL F-75005 Paris France Univ Paris Est Creteil Univ Gustave Eiffel CNRS LAMA UMR8050 F-94010 Creteil France

Electroencephalogram (EEG) signals reflect brain activity across different brain states, characterized by distinct frequency distributions. Through multifractal analysis tools, we investigate the scaling behaviour of several classes of EEG signals and artifacts. We show that brain states associated to sleep and general anaesthesia are not in general characterized by scale invariance. The lack of scale invariance motivates the development of artifact removal algorithms capable of operating independently at each scale. We examine here the properties of the wavelet quantile normalization (WQN) algorithm, a recently introduced adaptive method for real-time correction of transient artifacts in EEG signals. We establish general results regarding the regularization properties of the WQN algorithm, showing how it can eliminate singularities introduced by artefacts, and we compare it to traditional thresholding algorithms. Furthermore, we provide evidence that the algorithm performance is independent of the wavelet basis. We finally examine its continuity and boundedness properties and illustrate its distinctive non-local action on the wavelet coefficients through pathological examples.

关键词： Art Electroencephalography time-frequency analysis Signal processing algorithms Transient analysis Transforms Task analysis Artifact replacement EEG real-time algorithm regularity property transport wavelet decomposition

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Wind turbine overspeed protection based on polytopic robustly invariant sets

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WIND ENERGY 2016年第9期19卷 1713-1731页

作者： Hure, Nikola Vasak, Mario Jelavic, Mate Peric, Nedjeljko Univ Zagreb Fac Elect Engn & Comp Dept Control & Comp Engn Lab Renewable Energy Syst Unska 3 HR-10000 Zagreb Croatia KONCAR Elect Engn Inst Inc Fallerovo Setaliste 22 HR-10000 Zagreb Croatia

Complex mechanical systems, such as wind turbines, often include safety constraints which should not be violated in order to avoid high risk of structural damage. Adherence to the safety constraints is ensured with a well-designed operating envelope protection. In this paper, we present an invariant set-based protection concept with the application to the wind turbine overspeed protection. The approach is model-based and operates without wind-preview measurements. Instead, it is based on the evolution model of the wind disturbance in the worst-case scenario manner. Accurate system estimation utilizing the blade root in-plane measurement is proposed, along with the efficient algorithm for the hard real-time operation of the protection system. The overspeed protection system is validated in extensive simulations on extreme turbulent wind, performed in GH Bladed. The results show the effectiveness of the proposed concept compared with the baseline controller performance. Copyright (C) 2015 John Wiley & Sons, Ltd.

关键词： wind turbine overspeed protection robustly controlled invariant set state estimation real-time algorithm damage equivalent loads analysis

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real-time agent-based control of plug-in electric vehicles for voltage and thermal management of LV networks: formulation and HIL validation

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第11期14卷 2169-2180页

作者： Veloso, Cesar Garcia Rauma, Kalle Orjuela, Julian Fernandez Rehtanz, Christian KTH Royal Inst Technol Stockholm Sweden Tech Univ Catalonia Barcelona Spain TU Dortmund Univ Inst Energy Syst Energy Efficiency & Energy Ie3 Dortmund Germany Univ Victoria Inst Integrated Energy Syst Victoria BC Canada

Ensuring a stable and reliable operation of current and future distribution networks represents a major challenge for system operators aggravated by the global proliferation of plug-in electric vehicles (PEVs). While the introduction of a controlled charging process would be advantageous to minimise the impacts PEVs cause in the system, a suitable, efficient and ready to be implemented solution is still missing. The present work addresses this issue by proposing a smart charging management solution capable to simultaneously combat the main network impacts derived from the energy needs of the vehicles. This is done by means of an agent-based hierarchical real-time algorithm which combines a local decentralised nodal voltage management with a centralised thermal control conceived to minimise the impact upon participating users. The effectiveness of the proposed system is tested both using a simulation environment considering multiple PEV penetration levels and employing commercially available charging stations and cars through hardware-in-the-loop simulations. The results reveal how all network violations are successfully attenuated by peak shaving the total aggregated charging demand and ensuring a correct system operation for all penetration scenarios while inflicting no impact on the participating users.

关键词： distribution networks distributed power generation electric vehicles hardware-in-the loop simulation real-time systems temperature control plug-in electric vehicles thermal management LV networks distribution networks global proliferation controlled charging process smart charging management real-time algorithm local decentralised nodal voltage management centralised thermal control multiple PEV penetration levels charging stations aggregated charging demand real-time agent-based control hardware-in-the-loop simulations

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Flexible Scenario for Background Suppression in Heavy Element Research

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PHYSICS OF ATOMIC NUCLEI 2022年第12期85卷 1981-1987页

作者： Ibadullayev, D. Tsyganov, Yu. S. Polyakov, A. N. Voinov, A. A. Shumeiko, M. V. Joint Inst Nucl Res Flerov Lab Nucl React Dubna 141980 Russia Inst Nucl Phys Alma Ata 050032 Kazakhstan Eurasian Natl Univ Astana 010000 Kazakhstan

New algorithms to operate with new analog spectrometer of the DGFRS-2 installed at DC-280 cyclotron setup are presented. The main goal of application of these algorithms is to search an optimal time correlation recoil-alpha parameter directly during the acquisition C++ code execution. A new real-time flexible algorithm is presented in addition to the conventional ER-alpha one which is in use for a few years at the DGFRS-1 setup installed at the U-400 FLNR cyclotron. Note that the spectrometer operates together with the 48 x 128 strip DSSD (Double Side Strip Detector;48 x 226 mm(2)) detector and low pressure pentane-filled gaseous detector (1.2 Torr;80 x 230 mm(2)) are presented schematically. First beam test results in Ca-48 induced nuclear reactions are presented too.

关键词： alpha decay real-time algorithm detection system cyclotron heavy ion C plus plus gaseous detector silicon radiation detector

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real-time System Identification of a Nonlinear Four-Story Steel Frame Structure-Application to Structural Health Monitoring

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IEEE SENSORS JOURNAL 2009年第11期9卷 1339-1346页

作者： Hann, Christopher E. Singh-Levett, Ishan Deam, Bruce L. Mander, John B. Chase, J. Geoffrey Univ Canterbury Dept Mech Engn Christchurch 8140 New Zealand Univ Canterbury Dept Civil Engn Christchurch 8140 New Zealand Texas A&M Univ Zachry Dept Civil Engn College Stn TX 77843 USA HGL Dynam Ltd Godalming GU7 1HZ Surrey England

Structural health monitoring (SHM) is a means of identifying damage from structural response to environmental loads. real-time SHM is of particular use for rapid assessment of structural safety by owners and civil defense authorities. This paper presents an algorithm for real-time SHM during earthquake events using only acceleration measurements and infrequently measured displacement motivated by global positioning system. The algorithm identifies a nonlinear baseline model including hysteretic dynamics and permanent deformation using convex integral-based fitting methods and piecewise linear least squares fitting. The methodology identifies pre and postyield stiffness, elastic and plastic components of displacement, and final residual displacement. It thus identifies key measures of damage affecting the immediate safety or use of the structure and the long-term cost of repair and retrofit. The algorithm is tested with simulated response data using the El-Centro earthquake record and with measured response data. Both data sets are based on a four-story nonlinear steel frame structure using the El-Centro ground motion record. Overall, the algorithm is shown to provide accurate indications of the existence, location, and magnitude of structural damage for nonlinear shear-type buildings. Additionally, the identified permanent displacement is a particularly useful damage measure for the construction of probabilistic fragility functions.

关键词： Model-based parameter identification permanent displacement real-time algorithm structural health monitoring (SHM)

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Methodology for time-domain estimation of storm time geoelectric fields using the 3-D magnetotelluric response tensors

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SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS 2017年第7期15卷 874-894页

作者： Kelbert, Anna Balch, Christopher C. Pulkkinen, Antti Egbert, Gary D. Love, Jeffrey J. Rigler, E. Joshua Fujii, Ikuko US Geol Survey Geomagnetism Program Box 25046 Denver CO 80225 USA Oregon State Univ Coll Earth Ocean & Atmospher Sci Corvallis OR 97331 USA NOAA Space Weather Predict Ctr Boulder CO USA NASA Goddard Space Flight Ctr Greenbelt MD USA Meteorol Coll Kashiwa Chiba Japan

Geoelectric fields at the Earth's surface caused by magnetic storms constitute a hazard to the operation of electric power grids and related infrastructure. The ability to estimate these geoelectric fields in close to real time and provide local predictions would better equip the industry to mitigate negative impacts on their operations. Here we report progress toward this goal: development of robust algorithms that convolve a magnetic storm time series with a frequency domain impedance for a realistic three-dimensional (3-D) Earth, to estimate the local, storm time geoelectric field. Both frequency domain and time domain approaches are presented and validated against storm time geoelectric field data measured in Japan. The methods are then compared in the context of a real-time application. Plain Language Summary Magnetic storms can pose significant risks to critical technology infrastructure such as the electric power grids. real-time estimation of geoelectric fields can give the grid operators an opportunity for prompt intervention that would mitigate the long-term consequences. We develop and validate a method to efficiently and accurately (to within 85-90%) "nowcast" storm time geoelectric fields in close to real time in places where both geomagnetic field data are collected or estimated, and a magnetotelluric impedance has been previously measured. This method can be applied in all regions where magnetotelluric data have been collected, including in the United States, where USArray magnetotelluric data survey is ongoing and by 2018 will cover about two thirds of the country. In this work, we focus on the algorithm development only.

关键词： geoelectric fields geomagnetically induced currents magnetotelluric impedance space weather hazards real-time algorithm discrete time impulse response

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Predicting missing values in a home care database using an adaptive uncertainty rule method

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METHODS OF INFORMATION IN MEDICINE 2005年第5期44卷 639-646页

作者： Konias, S Gogou, G Bamidis, PD Vlahavas, I Maglaveras, N Aristotle Univ Thessaloniki Sch Med Lab Med Informat Thessaloniki 54124 Greece Aristotle Univ Thessaloniki Dept Informat Thessaloniki Greece

Objectives. Contemporary literature illustrates an abundance of adaptive algorithms for mining association rules. However, most literature is unable to deal with the peculiarities, such as missing values and dynamic data creation, that are frequently encountered in fields like medicine. This paper proposes an uncertainty rule method that uses an adaptive threshold for filling missing values in newly added records. A new approach for mining uncertainty rules and filling missing values is proposed, which is in turn particularly suitable for dynamic databases, like the ones used in home care systems. Methods. in this study, a new data mining method named FiMV (Filling Missing Values) is illustrated based on the mined uncertainty rules. Uncertainty rules have quite a similar structure to association rules and are extracted by an algorithm proposed in previous work, namely AURG (Adaptive Uncertainty Rule Generation). The main target was to implement an appropriate method for recovering missing values in a dynamic database, where new records are continuously added, without needing to specify any kind of thresholds beforehand. Results: The method was applied to a home care monitoring system database. Randomly, multiple missing values for each record's attributes (rate 5-20% by 5% increments) were introduced in the initial dataset. FiMV demonstrated 100% completion rates with over 90% success in each case, while usual approaches, where all records with missing values are ignored or thresholds are required, experienced significantly reduced completion and success rates. Conclusions: It is concluded that the proposed method is appropriate for the data-cleaning step of the Knowledge Discovery process in databases. The latter, containing much significance for the output efficiency of any data mining technique, can improve the quality of the mined information.

关键词： data mining missing values adaptive thresholds real-time algorithm certainty factor

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