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24th IEEE International Conference on Computer Supported Cooperative Work in Design (IEEE CSCWD)

作者： Lei, Shiqi Shen, Weiming Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan Peoples R China

ISBN: (纸本)9781728165974

It is not easy to provide a thermal environment satisfying all occupants in a shared space owing to individual differences in thermal comfort. Existing research efforts focusing on resolving thermal conflicts in offices with multi-occupants rely on consensus-based temperature setpoints optimization, which causes unfairness among occupants. To cope with this drawback, we propose a method to assign occupants to cubicles where every occupant can enjoy their preferred thermal environment by utilizing the uneven temperature distribution in a shared space with air conditioners. The proposed method accounts for personal thermal comfort differences and uneven temperature distribution in an open office space, and maximizes the aggregate thermal comfort of occupants, by proposing a differential evolution algorithm for the cubicle assignment problem. An application of the proposed method under a space with 30 cubicles is analyzed by assignment simulation of 15 occupants to 30 cubicles. Results show that the proposed method can find every occupant a cubicle matching with their thermal preference among the available cubicles and generate an assignment solution that maximizes the sum of the thermal comfort probabilities of all the occupants. Our investigations demonstrate that cubicle assignment considering personal thermal preferences can discover the potential of current thermal environment for providing personalized thermal conditions for multi-occupants.

关键词： open space cubicle assignment thermal comfort optimization differential evolution algorithm

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Research on Maintenance Efficiency Optimization for the Catenary System of Electrified Railways

Research on Maintenance Efficiency Optimization for the Cate...

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IEEE IAS Conference on Industrial and Commercial Power System Asia (IEEE I and CPS Asia)

作者： Lin, Sheng Li, Nan Sun, Xiaojun Feng, Ding Southwest Jiaotong Univ Sch Elect Engn Chengdu Peoples R China

ISBN: (纸本)9781665434980

Traditional preventive maintenance schemes for catenary systems of electrified railways are mainly formulated by on-site managers with reference to previous maintenance records and experience. With the increase of the maintenance workload of catenary systems, traditional maintenance schemes have been unable to meet the highly efficient requirements for on-site maintenance strategies. In view of this, a maintenance efficiency optimization method is proposed. According to the sequence of maintenance work of catenary systems, the workflow model of catenary maintenance work is established. Then, by taking the maintenance resources as constraints and the shortest completion time of maintenance tasks as the optimization objective, the optimal allocation model of catenary system maintenance resources is established. Finally, the differential evolution algorithm is used to obtain the optimal maintenance scheme. Based on the field data of a railway bureau in China, the maintenance scheme of the catenary systems is optimized. The results show that this method can greatly improve the maintenance efficiency of the catenary systems compared with the on-site maintenance scheme, and can provide decision support for the formulation of the catenary system maintenance scheme.

关键词： Catenary systems skill matrix allocation optimization differential evolution algorithm

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DEA-tuning of Reduced-order Extended Luenberger Sliding Mode Observers(ELSMO) for Sensorless Control of High-speed SPMSM

DEA-tuning of Reduced-order Extended Luenberger Sliding Mode...

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IEEE International Electric Machines and Drives Conference (IEMDC)

作者： Chen, Zihang Chen, Feiyu Huang, Xiaoyan Li, Zhaokai Wu, Min Zhejiang Univ Coll Elect Engn Hangzhou Peoples R China

ISBN: (纸本)9781665405102

Aiming at the phenomenon of integral drift in the rotor position observed by the Luenberger Observer, a sliding mode term is added to the original Luenberger term to enhance the robustness of the system. Meanwhile, in order to simplify the complexity of the observer, this paper reduces the order of the original state equation. The differential evolution algorithm (DEA) is used to optimize the observer gain coefficient globally, which reduces the contingency and randomness of manual tuning.

关键词： differential evolution algorithm Reduced-order Extended Luenberger Sliding Mode Observers

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An Universal Control Strategy for Planar 2-DoF Underactuated Manipulator with One Passive Joint 40

An Universal Control Strategy for Planar 2-DoF Underactuated...

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40th Chinese Control Conference (CCC)

作者： Huang, Zixin Zhou, Yaosheng Chen, Zhen Wang, Wei Wang, Lejun Wuhan Inst Technol Sch Elect & Informat Engn Wuhan 430205 Peoples R China Wuhan Text Univ Hubei Key Lab Digital Text Equipment Wuhan 430074 Peoples R China Wuhan Inst Technol Sch Innovat & Entrepreneurship Wuhan 430205 Peoples R China Zhongnan Univ Econ & Law Sch Informat & Safety Engn Wuhan 430073 Peoples R China Hubei Key Lab Adv Control & Intelligent Automat C Wuhan 430074 Peoples R China Minist Educ Engn Res Ctr Intelligent Technol Geoexplorat Wuhan 430074 Peoples R China

ISBN: (纸本)9789881563804

This paper presents an unified control strategy based on the trajectory planning and tracking control for the planar 2-DoF underactuated manipulator. The trajectory of the active link is composed of two parts. The first part trajectories are designed according to the initial and target angles of the active link. The second part trajectories are designed based on the constraints between the underactuated link and the active link. Meanwhile, the parameters of the trajectories are optimized by the differential evolution algorithm (DEA) to ensure all links eventually reach to their target values by tracking the designed trajectories. Then, the sliding mode variable structure controller are designed to make the active link track their trajectories. The effectiveness of such strategy is demonstrated through simulation results.

关键词： Planar 2-DoF underactuated manipulator Trajectory planning Tracking control differential evolution algorithm

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Long-term joint scheduling of hydropower station group in the upper reaches of the Yangtze River using partition parameter adaptation differential evolution

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2019年 81卷 1-13页

作者： He, Zhongzheng Zhou, Jianzhong Qin, Hui Jia, Benjun Lu, Chengwei Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Hubei Peoples R China Hubei Key Lab Digital Valley Sci & Technol Wuhan 430074 Hubei Peoples R China

Hydropower as renewable, clean and cheap energy occupies a considerable share in power energy production. With more and more hydropower stations being established and involved in joint operation, long-term joint scheduling of hydropower station group (LJSHSG) has become a challenging constrained optimization problem, because of its characteristics of high dimension, nonlinearity and coupling. In order to deal with this problem effectively, the partition parameter adaptation differential evolution (PPADE) is put forward based on success-history based adaptive differential evolution (SHADE). PPADE uses a new mutation strategy "current-to-pbest/U-Ip", which is improved with relaxing the index restrained condition and linearly decreased region of control parameter p with large initial value based on "current-to-pbest/1" to prevent premature convergence. In addition, the partition parameter adaptation divides the population in descending order according to fitness and entry set into C partition so that each population partition corresponds to a partition of entry set for enhancing exploitation by faster and better boot parameter update in PPADE. Then numerical experiments of 10 benchmark functions in high dimension and low dimension have been done, it shows that PPADE with above improvement has stable convergence and high efficiency. With the PPADE compared with other improved DE algorithms in the LJSHSG problem of four completed hydropower stations, Xiluodu, Xiangjiaba, Three Gorges and Gezhouba, in the upper reaches of the Yangtze River, PPADE increases the power production compared to SHADE, EPSDE, CoDE and LSHADE in average best benefit by 9.06, 17.09, 35.69, 69.67 x 10(8) kWh in wet year. It demonstrates that PPADE has stable and efficient convergence to be a useful and reliable tool for LJSHSG problem. Then two hydropower stations under construction, Wudongde and Baihetan, are add into consideration to analysis compensation benefit of hydropower station group (HSG)

关键词： Long-term scheduling Hydropower station groups differential evolution algorithm Joint operation Parameter adaptation

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An improved Fuzzy based GWO algorithm for predicting the potential host receptor of COVID-19 infection

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COMPUTERS IN BIOLOGY AND MEDICINE 2022年第Pt A期151卷 106050-106050页

作者： Achom, Amika Das, Ranjita Pakray, Partha Natl Inst Technol Dept Comp Sci & Engn Aizwal 796001 Mizoram India Natl Inst Technol Dept Comp Sci & Engn Silchar 788003 Assam India

Coronavirus disease (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and has infected millions worldwide. SARS-CoV-2 spike protein uses Angiotensin-converting enzyme 2 (ACE2) and Transmembrane serine protease 2 (TMPRSS2) for entering and fusing the host cell membrane. However, interaction with spike protein receptors and protease processing are not the only factors determining coronaviruses' entry. Several proteases mediate the entry of SARS-CoV-2 virus into the host cell. Identifying receptor factors helps understand tropism, transmission, and pathogenesis of COVID-19 infection in humans. The paper aims to identify novel viral receptor or membrane proteins that are transcriptionally and biologically similar to ACE2 and TMPRSS2 through a fuzzy clustering technique that employs the Grey wolf optimizer (GWO) algorithm for finding the optimal cluster center. The exploratory and exploitation capability of GWO algorithm is improved by hybridizing mutation and crossover operators of the evolutionary algorithm. Also, the genetic diversity of the grey wolf population is enhanced by eliminating weak individuals from the population. The proposed clustering algorithm's effectiveness is shown by detecting novel viral receptors and membrane proteins associated with the pathogenesis of SARS-CoV-2 infection. The expression profiles of ACE2 protein and its co-receptor factor are analyzed and compared with single-cell transcriptomics profiling using the Seurat R toolkit, mass spectrometry (MS), and immunohistochemistry (IHC). Our advanced clustering method infers that cell that expresses high ACE2 level are more affected by SARS-CoV-infection. So, SARS-CoV-2 virus affects lung, intestine, testis, heart, kidney, and liver more severely than brain, bone marrow, skin, spleen, *** have identified 58 novel viral receptors and 816 membrane proteins, and their role in the pathogenicity mechanism of SARS-CoV-2 infection has been studied. Besides, our s

关键词： Single cell RNA sequencing data Clustering COVID-19 SARS-CoV-2 ACE2 TMPRSS2 Fuzzy clustering Grey wolf optimizer differential evolution algorithm evolution population dynamics

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Using a Grey model optimized by differential evolution algorithm to forecast the per capita annual net income of rural households in China

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2012年第5期40卷 525-532页

作者： Zhao, Ze Wang, Jianzhou Zhao, Jing Su, Zhongyue Lanzhou Univ Sch Math & Stat Lanzhou 730000 Gansu Peoples R China

China is a major developing country where farmers account for over 57% of the population. Thus, promoting a rural economy is crucial if the Chinese government is to improve the quality of life of the nation as a whole. To frame scientific and effective rural policy or economic plans, it is useful and necessary for the government to predict the income of rural households. However, making such a prediction is challenging because rural households income is influenced by many factors, such as natural disasters. Based on the Grey Theory and the differential evolution (DE) algorithm, this study first developed a high-precision hybrid model, DE-GM(1,1) to forecast the per capita annual net income of rural households in China. By applying the DE algorithm to the optimization of the parameter lambda. which was generally set equal to 0.5 in GM( 1.1), we obtained more accurate forecasting results. Furthermore, the DE-Rolling-GM(1,1) was constructed by introducing the Rolling Mechanism. By analyzing the historical data of per capita annual net income of rural households in China from 1991 to 2008, we found that DE-Rolling-GM(1,1) can significantly improve the prediction precision when compared to traditional models. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： GM(1,1) Parameter optimization differential evolution algorithm Rolling Mechanism

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Fast characterization for UXO-like targets with a portable transient electromagnetic system

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MEASUREMENT 2022年 189卷

作者： Wang, Lijie Zhang, Shuang Chen, Shudong Jiang, Hejun Jilin Univ Coll Elect Sci & Engn Changchun 130012 Peoples R China Sci & Technol Near Surface Detect Lab Wuxi 214035 Jiangsu Peoples R China

When detecting an underground target with a portable transient electromagnetic system, the system excites and records digitized data on a 5 x 5 or 7 x 7 grid above the target, and with the positioning system to accurately record the sensor positions, which makes the detection more complex and less efficient. To simplify the detection process, a novel three-position measurement method without positioning system is proposed to estimate the target characteristics. First, a new forward model based on the relative position is established, and the relative position is estimated by differential evolution algorithm at each measurement. Then, the proposed method is optimized to quickly and precisely characterize the target. Results show that the horizontal and depth errors are less than 5 and 9 cm, respectively. The proposed method takes about 28.4 s to characterize the target, only 11% of the traditional one, which substantially improves the detection efficiency and flexibility of the portable sensor.

关键词： Transient electromagnetic Unexploded ordnance differential evolution algorithm Target characterization

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Interval inversion based well log analysis assisted by petrophysical laboratory measurements for evaluating tight gas formations in Derecske through, Pannonian basin, east Hungary

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2022年第PartC期208卷 109607-109607页

作者： Szabo, N. P. Remeczki, F. Jobbik, A. Kiss, K. Dobroka, M. Univ Miskolc Dept Geophys H-3515 Miskolc Hungary Univ Miskolc MTA ME Geoengn Res Grp H-3515 Miskolc Hungary Univ Miskolc Res Inst Appl Earth Sci H-3515 Miskolc Hungary

The evaluation of Hungarian tight gas formations requires the use of innovative interpretation technologies because of diverse geological environment, heterogeneous dataset including several variables measured with different accuracies, and reservoirs under varying petrophysical conditions. Conventional well logging methods based on the use of limited number of wireline logs make only a quick-look interpretation, in which a limited number of unknowns is determined, and there is a non-negligible risk for occurrence of ambiguity. In order to increase the overdetermination (data-to-unknowns) ratio and the estimation accuracy and reliability, all suitable well logs are to be jointly processed in a more effective manner. To estimate the total organic carbon content together with porosity, water saturation, shale content and rock matrix volumes with higher accuracy, a new inversion methodology is introduced that is tested in tight gas reservoirs. A differential evolution algorithmbased interval inversion method is developed that is combined by nano-permeability and high precision porosity laboratory measurements for the detection and evaluation of Hungarian tight gas reservoirs. Spectral gamma-ray, neutron-porosity and electric resistivity logs are jointly analyzed using the interval inversion approach. By solving a highly overdetermined inverse problem, the effective porosity, water- and gas saturation, shale and sand content, as well as the kerogen volume are estimated in a reliable inversion procedure. The silt and clay content of Miocene tight gas formations are separated and both determined by inversion, while the total organic carbon content is derived from the inversion results. The permeability log is directly derived from the inverted porosity values using the local porosity versus permeability relation established by multi-well core analysis. The combination of in situ wireline log data analysis and porosity and nano-permeability laboratory measurements is shown

关键词： Interval inversion differential evolution algorithm Well logging Total organic carbon content Permeability

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Electricity Market Price Prediction Based on differential evolutionary algorithm and Neural Network 3

Electricity Market Price Prediction Based on Differential Ev...

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3rd Asia Energy and Electrical Engineering Symposium (AEEES)

作者： Fu, Yuetong Zhang, Zheng Li, Tianran Nanjing Normal Univ Sch Elect Power & Automat Engn Nanjing Peoples R China NARI Technol Dev Co Ltd Nanjing Peoples R China

ISBN: (纸本)9781665425513

In order to obtain a practical and high-precision prediction method of the clearing price in the spot market of electric power, this paper tries to apply the neural network optimized by differential evolutionary algorithm to the prediction of the clearing price in the spot market. Firstly, the weights and thresholds of BP neural network are optimized based on differential evolutionary algorithm, and then the BP neural network model is used to test on the basis of the PJM spot market data in the United States. The experiment shows that the prediction accuracy of the proposed method is improved obviously and the prediction effect is stable.

关键词： electricity market forecast electricity market price differential evolution algorithm artificial neural networks

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