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A Barzilai-Borwein Gradient algorithm for Spatio-Temporal Internet Traffic Data Completion via Tensor Triple Decomposition

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JOURNAL OF SCIENTIFIC COMPUTING 2021年第3期88卷 65-65页

作者： Chen, Yannan Zhang, Xinzhen Qi, Liqun Xu, Yanwei South China Normal Univ Sch Math Sci Guangzhou Peoples R China Tianjin Univ Sch Math Tianjin 300354 Peoples R China Huawei Technol Investment Co Ltd Labs 2012 Future Network Theory Lab Shatin Hong Kong Peoples R China Hangzhou Dianzi Univ Dept Math Sch Sci Hangzhou 310018 Peoples R China Hong Kong Polytech Univ Dept Appl Math Hung Hom Kowloon Hong Kong Peoples R China Huawei Theory Res Lab Kowloon Hong Kong Peoples R China

With the coming of high-speed network and 5G era, internet traffic data is crucial for various network tasks such as traffic engineering, capacity planning and anomaly detection. To explore the natural spatio-temporal structure of network flow, we use the novel triple decomposition of tensors to establish an optimization model with the spatio-temporal regularization for completing the internet traffic data. A Barzilai-Borwein gradient algorithm is designed for solving the spatio-temporal internet traffic tensor completion problem. We prove the convergence of this algorithm and analyze its convergence rate with the tool of the Kurdyka-Lojasiewicz property. Numerical experiments on Abilene and GeANT datasets report that the proposed tensor completion method is effective.

关键词： Internet traffic tensor Tensor completion Triple tensor decomposition optimization algorithm

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Simulation of Chlorophyll a Concentration in Donghu Lake Assisted by Environmental Factors Based on Optimized SVM and Data Assimilation

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WATER 2022年第15期14卷 2353-2353页

作者： Tang, Xiaodong Huang, Mutao Huazhong Univ Sci & Technol Sch Civil & Hydraul Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Elect & Elect Engn Wuhan 430074 Peoples R China

Lake eutrophication is a global water environmental problem and has become a research focus nowadays. Chlorophyll a concentration is an important index in terms of evaluating lake eutrophication. The aim of this study was to build an effective and universal empirical model for simulation of chlorophyll a concentration in Donghu Lake. On the basis of the relationship between chlorophyll a concentration and dissolved oxygen (DO), water temperature (T), total nitrogen (TN), and total phosphorus (TP), models for simulating chlorophyll a concentration were built by using simulated annealing (SA), genetic algorithm (GA), artificial bee colony (ABC), and particle swarm optimization (PSO) to optimize parameters of support vector machine (SVM). Moreover, a collaborative mode (Col-SVM model) was built by introducing data assimilation, and meanwhile, accuracy and universality of the model were studied. Modeling results showed that the application of optimization algorithms and data assimilation improved the performance of modeling based on SVM. Model simulation results demonstrated that the Col-SVM model has high accuracy, decent stability, and good simulation effect;the root mean square error (RMSE), mean absolute percentage error (MAPE), Nash-Sutcliffe efficiency coefficient (NSE), bias, and mean relative error (MRE) between simulated values and observed values were 10.07 mu g/L, 0.31, 0.96, -0.050, and 0.15, respectively. In addition, model universality analysis results revealed that the Col-SVM model has good universality and can be used to simulate the chlorophyll a concentration of Donghu Lake at different times. Overall, we have built an effective and universal simulation model of chlorophyll a concentration that provides a new idea and method for chlorophyll a concentration modeling.

关键词： chlorophyll a concentration support vector machine optimization algorithm data assimilation Donghu Lake

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A Low-Complexity Channel Estimation in Internet of Vehicles in Intelligent Transportation Systems for 5G Communication

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JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING 2023年第1期35卷 1页

作者： Yan, Lichao Zhengzhou Univ Aeronaut Sch Intelligent Engn Zhengzhou Peoples R China

The objective of utilizing mmWave/subTHz bands in next-generation wireless communications is to be achieved. Despite this, since reconfigurable intelligent surface (RIS)-assisted systems depend on the transmission channel configuration, the system architecture design, and the methods used to derive channel state information (CSI) on a base station (BS) and RIS, channel estimation continues to be the main problem with these systems. This research proposes an innovative RIS-based and compressed sensing-based channel estimation technique for the internet of vehicles. To obtain the best phase shift matrix, the communication model must first be constructed, and the angle-of-arrival and departure are utilized. Channel estimation is then performed based on the perception matrix. The training overhead and complexity of the channel estimation are reduced by considering the position information of the vehicles in the optimal phase shift matrix. Simulation results show that the proposed algorithm exhibits better channel estimation and low complexity performance compared with existing algorithms.

关键词： 5G Networks Channel Estimation Complexity Intelligent Compressed Sensing Intelligent Reflecting Surface optimization algorithm Transportation System Vehicular Communication

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Effects of PM2.5 on health and economic loss: Evidence from Beijing-Tianjin-Hebei region of China

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JOURNAL OF CLEANER PRODUCTION 2020年 257卷 120605-120605页

作者： Wang, Jianzhou Zhang, Lifang Niu, Xinsong Liu, Zhenkun Dongbei Univ Finance & Econ Sch Stat Dalian 116025 Peoples R China

Rapid industrialization and urbanization have triggered severe PM(2.5 )pollution and induced serious health hazards and economic losses in densely populated regions. A substantial number of health-related economic loss assessment methods, which quantify economic losses caused by diverse health endpoints, have been applied. However, traditional models neglect pollutant distribution and optimization of distribution parameters, which may lead to poor estimation accuracy. In this study, a health-related economic loss evaluation system is proposed, which deals with PM2.5 distribution, optimization of distribution parameters, and evaluation of health-related economic losses. This assessment system efficiently simulated the characteristic of PM2.5 concentrations in three cities of the Beijing-Tianjin-Hebei region and addressed economic losses estimation problems. The results indicate that the system not only provides a novel perspective on health-related economic loss assessment, but also assists policymakers in its practical application. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： PM2.5 distributions optimization algorithm BTH region Economic loss assessment

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An Effective Spectral Processing Method for Low-Cost Fiber Loop Ring-Down Systems

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ADVANCED THEORY AND SIMULATIONS 2023年第5期6卷

作者： Cha, Guozhi Wang, Ruoyu Ma, Jiangtao Shao, Guifang Liu, Tundong Xiamen Univ Sch Aerosp Engn Xiamen 361102 Peoples R China Dali Univ Sch Engn Dali 671003 Peoples R China Xiamen Univ Xiamen Key Lab Big Data Intelligent Anal & Decis Xiamen 361102 Peoples R China

Fiber loop ring-down spectroscopy (FLRDS) is a highly sensitive spectroscopic technology. Here, a spectral processing method is proposed for low-cost fiber loop ring-down systems. In the proposed method, the amplitude modulation theory is used to establish a new ring-down spectral model, and the particle swarm optimization algorithm is introduced into FLRDS. The experimental results demonstrate that the proposed method can effectively process the ring-down spectral signals acquired from the low-cost fiber loop ring-down system. Moreover, this method demonstrates higher accuracy and stronger adaptability than the current widely used method. Owing to its excellent performance, the proposed method has considerable potential to be applied in low-cost fiber loop ring-down systems.

关键词： amplitude modulation fiber optics optimization algorithm spectroscopy

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A water quality prediction model based on variational mode decomposition and the least squares support vector machine optimized by the sparrow search algorithm (VMD-SSA-LSSVM) of the Yangtze River, China

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2021年第6期193卷 363-363页

作者： Song, Chenguang Yao, Leihua Hua, Chengya Ni, Qihang China Univ Geosci Beijing Sch Engn & Technol Beijing 100083 Peoples R China

Accurate and reliable water quality forecasting is of great significance for water resource optimization and management. This study focuses on the prediction of water quality parameters such as the dissolved oxygen (DO) in a river system. The accuracy of traditional water quality prediction methods is generally low, and the prediction results have serious autocorrelation. To overcome nonstationarity, randomness, and nonlinearity of the water quality parameter data, an improved least squares support vector machine (LSSVM) model was proposed to improve the model's performance at two gaging stations, namely Panzhihua and Jiujiang, in the Yangtze River, China. In addition, a hybrid model that recruits variational mode decomposition (VMD) to denoise the input data was adopted. A novel metaheuristic optimization algorithm, the sparrow search algorithm (SSA) was also implemented to compute the optimal parameter values for the LSSVM model. To validate the proposed hybrid model, standalone LSSVM, SSA-LSSVM, VMD-LSSVM, support vector regression (SVR), as well as back propagation neural network (BPNN) were considered as the benchmark models. The results indicated that the VMD-SSA-LSSVM model exhibited the best forecasting performance among all the peer models at Panzhihua station. Furthermore, the model forecasting results applied at Jiujiang were consistent with those at Panzhihua station. This result further verified the accuracy and stability of the VMD-SSA-LSSVM model. Thus, the proposed hybrid model was effective method for forecasting nonstationary and nonlinear water quality parameter series and can be recommended as a promising model for water quality parameter forecasting.

关键词： VMD SSA LSSVM Water quality prediction optimization algorithm Hybrid model

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Optimized Bezier-curve-based command generation and robust inverse optimal control for attitude tracking of spacecraft

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AEROSPACE SCIENCE AND TECHNOLOGY 2022年第0期121卷 107183-107183页

作者： Wang, Peng Zhang, Xiaobing Nanjing Univ Sci & Technol Sch Energy & Power Engn Nanjing Peoples R China

In this paper we address the optimized attitude command generation and robust inverse optimal control design for the spacecraft attitude tracking with large angle slews. Firstly, with the reference attitude command described in a Bezier curve through the spherical linear interpolation, an optimized reference command is generated to meet the principles of small energy consumption and short turning time. The applied optimization combines the particle swarm optimization algorithm and genetic algorithm based on information entropy to guarantee the diversity of the population and improve the global search capabilities. Next, a robust inverse optimal control is developed for the attitude tracking of the obtained optimized reference attitude command, consisting of an inverse optimal Lyapunov approach for performance guarantee and an arctangent-based integral sliding mode control for the disturbance attenuation. A stronger generality of the control Lyapunov function is obtained for the inverse optimality. Furthermore, the developed control efforts are of smaller amplitudes due to introducing the auxiliary angular velocity for the smooth transition to the reference attitude command. Finally, simulation results are included to show the performance of the proposed scheme. (c) 2021 Elsevier Masson SAS. All rights reserved.

关键词： Attitude control Inverse optimal control optimization algorithm Bezier curve Arctangent-based sliding mode control

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Aggregated Use of Energy Flexibility in Office Buildings

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ENERGIES 2023年第2期16卷 961页

作者： Patricio, Joao Tabanez Lopes, Rui Amaral Majdalani, Naim Aelenei, Daniel Martins, Joao NOVA Sch Sci & Technol P-2829516 Caparica Portugal Ctr Technol & Syst CTS UNINOVA P-2829516 Caparica Portugal Univ Lisbon IST IN Tecn Lisboa P-1049001 Lisbon Portugal

Due to climate change consequences, all Member States of the European Union signed an agreement with the goal of becoming the first society and economy with a neutral impact on the planet by 2050. The building sector is one of the highest energy consumers, using 33% of global energy production. Given the global increase for energy demand, implementing energy flexibility strategies is crucial for a better integration of renewable energy sources and a reduction of consumption peaks arising from the electrification of energy demand. The work described in this paper aims to develop an optimization algorithm to use the existing aggregated energy flexibility in office buildings to reduce both the electric energy costs of each office, considering the tariffs applied at each moment and the total power peak, aiming to reduce the entire building's cost of the contracted power, considering the Portuguese context. The obtained results conclude that it is possible to reduce both the costs associated with electric energy consumption and contracted power. Nevertheless, since the cost of contracted power has a lower impact on the overall energy bill, it is more beneficial to focus only on the reduction of costs associated with electric energy consumption in the considered case study.

关键词： energy flexibility energy management energy consumption modeling EnergyPlus optimization algorithm

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Analyzing the Societal Cost of Electric Roads Compared to Batteries and Oil for All Forms of Road Transport

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ENERGIES 2022年第5期15卷 1925页

作者： Coban, Hasan Huseyin Rehman, Aysha Mohamed, Abdullah Ardahan Univ Dept Elect Engn TR-75002 Ardahan Turkey Univ Gujrat Dept Math Gujrat 50700 Pakistan Future Univ Egypt Univ Res Ctr New Cairo 11745 Egypt

This article is designed to demonstrate that electric roads are an affordable way to electrify all forms of road transport-not only cars, but also buses and trucks. Electric roads represent a way to power electric vehicles without relying solely on batteries. The idea is that when an electric vehicle reaches an electric road, it stops using power from the battery and instead uses power directly from the road itself. The primary challenge for electric vehicles is still the perception of a compromised quality of life in owning an electric vehicle due to a limited range compared with petrol and diesel cars, today. This paper introduces a new technology, currently experiencing rapid development, that can not only overcome range anxiety but make electric vehicles better, in terms of range, than petrol and diesel cars today. Furthermore, not only can this research help to arrange this, but it can also help, for the first time, to cost-effectively electrify heavy-duty transport, such as trucks and buses, which would be a huge breakthrough in terms of sustainability, as it is very important to start supplying electricity to heavy-duty vehicles. The case study provides a very hypothetical example of a trip with and without an electric road, covering a total of 26,011 km of highways and main roads. The results indicate that building electric roads is cheaper than many other alternatives. If a large battery is replaced with a smaller battery for each new vehicle sold, after 3 years, enough savings will be made to electrify all highways and main roads in Turkey. This paper can help transport operators and policymakers develop strategies to accelerate the adoption of electric vehicles by appropriately implementing electric road infrastructure.

关键词： electric road system battery-electric car electric vehicle sustainable transport profitability charging infrastructure optimization algorithm

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Optimal membership function based fuzzy proportional-integral controller for power control of molten salt breeder reactor core

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PROGRESS IN NUCLEAR ENERGY 2023年第1期161卷

作者： Acharya, Debasis Das, Dushmanta Kumar Natl Inst Technol Nagaland Dept Elect & Elect Engn Dimapur India

The aim of this paper is to design an optimal membership function (MF)-based fuzzy PI (proportional integral) controller to control the core power of a nuclear reactor. The molten salt breeder reactor (MSBR) is extensively utilized for studying primary power management of nuclear reactors. Many challenges are associated with such systems, including mathematical modelling errors, parametric uncertainties, and external disturbances. Moreover, the liquid fuel used in MSBR systems makes it more challenging to design a suitable controller for the core relative power control of such systems. The conventional PI controller may not perform efficiently under such uncertainties in the MSBR system. Different types of perturbations can be handled by a fuzzy controller, if the coordination among fuzzy rules and membership functions of fuzzy variables is done accurately. The idea of this work is to optimize the settings (range and scale) of fuzzy MFs in a fuzzy base controller. The fuzzy controller will not be used directly in the system;rather, it will be used to tune a PI controller for the system where proper expert knowledge may not be available. A nonlinear dynamic acceleration coefficients -based class topper optimization (NDAC-CTO) algorithm is also developed to optimize the fuzzy membership functions. For load tracking with step disruption, the power control of the MSBR core is investigated. With the proposed controller, a significant improvement of 70 to 80 % in the settling time of the power profile of the MSBR system is achieved in comparison with the existing results.

关键词： Molten salt breeder reactor Proportional-integral control Fuzzy controller optimization algorithm

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