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32nd Chinese Control And Decision Conference (CCDC)

作者： Qi, Zhiyang Huang, Xiaosong Shen, Yu Shi, Jiyun Beijing Inst Technol Sch Comp Sci Beijing 100081 Peoples R China

ISBN: (纸本)9781728158556

Connect6 is an intuitive and fair game with no first-hand advantage. Because of the large search tree, the search depth is often lower, to sacrifice strength of chess to improve search efficiency. In this case, this paper proposes an optimization algorithm for pruning Connect6 search tree based on the principal variation search and transposition tables algorithms. The optimization algorithm obtained PV node through searching, narrowed the pruning interval, and stored the key value of the situation into the transposition table through searching, and then directly returned the evaluation value when the same chess game was searched again, which greatly improved the search efficiency. Through a large number of repeated experiments, the effectiveness of the algorithm can be proved.

关键词： Connect6 PVS Transposition tables optimization algorithm

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Investigation on parallel auxiliary adjusting machine of spatial filter lens for a high-power laser facility

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OPTICS AND LASER TECHNOLOGY 2022年 147卷

作者： Zhang, Donghui Dong, Ziming Zhang, Chao Liu, Zhigang Zheng, Liunian Pang, Xiangyang Zhu, Jianqiang Chinese Acad Sci Shanghai Inst Opt & Fine Mech Natl Lab High Power Laser & Phys Shanghai 201800 Peoples R China Chinese Acad Sci China Acad Engn Phys Natl Lab High Power Laser & Phys Shanghai 201800 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

As a key part in high-power laser facility, the spatial filter is used to determine the optical axis of the entire laser system, which consists of two conjugate lenses at both ends and filter hole in the middle. The lenses usually require precise adjustment, and the adjustment mechanism is integrated to both ends of the filter currently. To this end, a novel parallel adjusting machine for the filter lenses was proposed as an auxiliary tool in the spatial filter process. The machine was designed to realize the five-dimensional adjustment functions of the filter lenses with X-Y-Z axial translation, pitch, and yaw motion. The first-order ghost point of the filter lens was used as the feedback reference for the parallel machine to adjust Z-position of the lens. A more comprehensive optimizationoriented framework was established to improve the sensitivity of the lens to the posture error and to optimize the positioning speed based on the steepest descent method (SDM). The experimental results verified the superiority of the proposed adjustment machine and feedback reference point.

关键词： Spatial filter Parallel machine Ghost reference point optimization algorithm

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Genetic algorithm-Optimized Extreme Learning Machine Model for Estimating Daily Reference Evapotranspiration in Southwest China

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ATMOSPHERE 2022年第6期13卷

作者： Liu, Quanshan Wu, Zongjun Cui, Ningbo Zhang, Wenjiang Wang, Yaosheng Hu, Xiaotao Gong, Daozhi Zheng, Shunsheng Sichuan Univ Coll Water Resource & Hydropower State Key Lab Hydraul & Mt River Engn Chengdu 610065 Sichuan Peoples R China Chinese Acad Agr Sci Inst Environm & Sustainable Dev Agr Beijing 100081 Peoples R China Northwest A&F Univ Key Lab Agr Soil & Water Engn Arid & Semiarid Are Minist Educ Yangling 712100 Xianyang Peoples R China

Reference evapotranspiration (ET0) is an essential component in hydrological and ecological processes. The Penman-Monteith (PM) model of Food and Agriculture Organization of the United Nations (FAO) model requires a number of meteorological parameters;it is urgent to develop high-precision and computationally efficient ET0 models with fewer parameter inputs. This study proposed the genetic algorithm (GA) to optimize extreme learning machine (ELM), and evaluated the performances of ELM, GA-ELM, and empirical models for estimating daily ET0 in Southwest China. Daily meteorological data including maximum temperature (T-max), minimum temperature (T-min), wind speed (u(2)), relative humidity (RH), net radiation (R-n), and global solar radiation (R-s) during 1992-2016 from meteorological stations were used for model training and testing. The results from the FAO-56 Penman-Monteith formula were used as a control group. The results showed that GA-ELM models (with R-2 ranging 0.71-0.99, RMSE ranging 0.036-0.77 mm center dot d(-1)) outperformed the standalone ELM models (with R-2 ranging 0.716-0.99, RMSE ranging 0.08-0.77 mm center dot d(-1)) during training and testing, both of which were superior to empirical models (with R-2 ranging 0.36-0.91, RMSE ranging 0.69-2.64 mm center dot d(-1)). ET0 prediction accuracy varies with different input combination models. The machine learning models using T-max, T-min, u(2), RH, and R-n/R-s (GA-ELM5/GA-ELM4 and ELM5/ELM4) obtained the best ET0 estimates, with R-2 ranging 0.98-0.99, RMSE ranging 0.03-0.21 mm center dot d(-1), followed by models with T-max, T-min, and R-n/R-s (GA-ELM3/GA-ELM2 and ELM3/ELM2) as inputs. The machine learning models involved with R-n outperformed those with R-s when the quantity of input parameters was the same. Overall, GA-ELM5 (T-max, T-min, u(2), RH and R-n as inputs) outperformed the other models during training and testing, and was thus recommended for daily ET0 estimation. With the estimation accuracy,

关键词： reference evapotranspiration extreme learning machine optimization algorithm empirical model solar radiation

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Carbon price forecasting system based on error correction and divide-conquer strategies

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APPLIED SOFT COMPUTING 2022年第0期118卷 107935-107935页

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

Carbon price forecasting is an important component of a sound carbon price market mechanism. The accurate prediction of carbon prices is an active topic of research. However, many previous studies have focused on the application of a single model, ignoring the application of combination strategies. In this study, a hybrid forecasting system that includes error correction strategy and divide-conquer strategy is designed to predict the carbon price series accurately. Specifically, the main framework of this article comprises four modules. Data preprocessing module of the divide and conquer strategy is proposed. Next, the optimization module uses a multi-objective grasshopper optimization algorithm to enhance the performance of the prediction module. Then, the error correction module predicts the error sequence and corrects the model results. To verify the performance of the established hybrid forecasting system, experiments were performed using two real carbon price series from China and European Union emissions trading schemes, and the results showed that the mean absolute percentage errors of the system were 2.7793% and 0.6720%, respectively, which are better than the other benchmark methods considered. Moreover, it was proved that the designed forecasting system provides a new, effective, and feasible solution for carbon price forecasting. (c) 2021 Elsevier B.V. All rights reserved.

关键词： Artificial intelligence Carbon price forecasting Data preprocessing optimization algorithm Error correction

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Automated technique for EEG signal processing to detect seizure with optimized Variable Gaussian Filter and Fuzzy RBFELM classifier

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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2022年 74卷

作者： Harishvijey, A. Raja, J. Benadict Anna Univ Chennai Tamilnadu India PSNA Coll Engn & Technol Dindigul Tamilnadu India

Epileptic seizure in patients is detected from EEG signals with the use of automatic signal classification tech-niques. The accurate detection of epilepsy is essential to reduce the risk of seizure related complications. However the available automatic signal detection techniques give poor sensitivity and accuracy. In this work, an automatic signal classification method for detecting seizure from EEG signal is presented for obtaining good classification results. The proposed work improves the performance of detection using Variable Gaussian filter (VGF) with social spider algorithm (SSA) (SSA-VGF), Empirical Wavelet Transform (EWT) feature extraction method, K-Principal component analysis (K-PCA) based feature reduction and Fuzzy logic embedded RBF kernel based ELM algorithm (FRBFELM). The SSA-VGF method is used for removing noise artifacts from the given EEG signals. EWT is employed for feature extraction and the size of extracted features is reduced using K-PCA method. Finally the signals are classified as normal signals and epileptic signals using FRBFELM classifier. The perfor-mance of the proposed method is evaluated by measuring the metrics;PSNR, accuracy, sensitivity, and speci-ficity. The value of performance metrics obtained for the proposed work is 98.48%, 98.44% and 98.51%.

关键词： EEG signals Signal classification Noise removal Filter algorithm Feature extraction Feature reduction optimization algorithm

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Determination of relative permeability curve under combined effect of polymer and surfactant

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2022年 215卷

作者： Zhang, Wenlong Hou, Jian Liu, Yongge Zhou, Kang Li, Zhenquan Du, Qingjun China Univ Petr East China Key Lab Unconvent Oil & Gas Dev Minist Educ Qingdao 266580 Peoples R China Qingdao Natl Lab Marine Sci & Technol Lab Marine Mineral Resources Qingdao 266237 Peoples R China China Univ Petr East China Sch Petr Engn Qingdao 266580 Peoples R China Shandong Univ Sci & Technol Coll Energy & Min Engn Qingdao 266580 Peoples R China SINOPEC Shengli Oilfield Branch Co Dongying 257015 Peoples R China

Relative permeability of surfactant-polymer (SP) flooding is determined by an inversion method based on numerical simulation and unsteady-state coreflooding experiment. Compared with the common methods, this method is more time-saving and simpler than steady-state method, and considers more physicochemical properties (adsorption and diffusion) of SP than unsteady-state method based on Buckley-Leverett theory. It is also more applicable to reservoir engineering than pore-scale simulation. After the reliability is confirmed, the superiority of the method is strongly proved by studying the influence of adsorption and diffusion of SP on relative permeability. Comparing relative permeability with and without effect of adsorption and diffusion of SP, the findings show adsorption and diffusion of SP significantly reduce the average inversion error of relative permeability curve from 11.9 to 3.7 for oil and from 10.7 to 1.8 for water. On this basis, the variations of SP flooding relative permeability under the effect of polymer and surfactant are discussed in turn. In the existing researches, the quantitative characterization of variation of SP-flooding relative permeability curves is limited by curve crossing and endpoint saturation changes. In this work, normalized relative permeability is introduced to eliminate the adverse effect caused by curve crossing and endpoint saturation changes. The findings show that although the rise of aqueous-phase viscosity reduces water relative permeability, it has little effect on normalized water relative permeability. Normalized oil and water relative permeability increase in logistic functions with the decrease of IFT in semi-logarithmic plot. Water relative permeability at residual oil endpoint decreases linearly as aqueous-phase viscosity increases, and increases exponentially as IFT decreases in semi-logarithmic plot. Ultimately, the functional models based on normalized relative permeability and cubic B-spline are built through mu

关键词： Surfactant-polymer flooding Relative permeability Numerical simulation Interfacial tension optimization algorithm

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Prior information-based optimization for electrical tomographic imaging 39

Prior information-based optimization for electrical tomograp...

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39th Chinese Control Conference (CCC)

作者： Lu, Jian Yue, Shihong Ma, Haitao Yem, Sidolla Wang, Huaxiang Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China

ISBN: (数字)9789881563903

ISBN: (纸本)9789881563903

Electrical tomographic imaging (ETI) is an advanced technique that has been widely applied in many fields. But it's application is greatly limited by its low spatial resolution which mainly caused by two inherent problems: ill-posed solution and "soft field" effect. Even many optimizing methods have been applied to overcome these problems and have made some contributions to increase the ETI spatial resolution. Meanwhile, the 'prior information' method has been demonstrated to be efficient and feasible. In this paper, we introduced the 'prior information' method for the optimization of the spatial resolution of ET! process. To do this, we first recovered rich types of the prior information in an ETI process, and then introduced them to the ETI process. Based on the Tikhonov regularization and a traditional optimization method, this assessable prior information can greatly increase spatial resolution for typical flow patterns. Moreover, the reconstructed ETI optimal solution is more robust than the solutions achieved by other existing methods. Both theoretical analysis and experimental results strongly confirmed the priority of this new method. It also laid an important foundation for further wide usage of the prior information to improve the spatial resolution in other applications.

关键词： Electrical impedance imaging optimization algorithm Image reconstruction

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Path Planning and optimization of Unmanned Ground Vehicles (UGVs) in the Field 3

Path Planning and Optimization of Unmanned Ground Vehicles (...

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3rd International Conference on Unmanned Systems (ICUS)

作者： Chen, Zhiwei Hu, Jinwen Zhao, Chunhui Hou, Xiaolei Pan, Quan Xu, Zhao Jia, Caijuan Sch Northwestern Polytech Univ Xian Peoples R China Xian ASN Technol Grp GO Ltd Xian Peoples R China

ISBN: (纸本)9781728180250

Unmanned Ground Vehicle (UGV) can be as a replacement of human beings during a dangerous mission. It can also be applied to military and performs repetitive mechanical transportation. For the UGVs in the conventional layout and structured urban environment, the research of environment perception and path planning technology has been relatively mature. Compared with the flat ground, the control of the UGV in the field is unknown and more complex. This article revolves autonomous control of the UGV in the field, putting forward a kind of path planning and optimizing technology for the UGV under complex environment. Research content includes: Conduct field environment modeling with environment information. First, the environment is detected by the fusion of lidar and IMU. Then a more accurate environment model is obtained by training the RBF neural network. Use the obtained environmental model to conduct path planning for the UGV in the field. The path planning trajectory is obtained by introducing the distance between the starting point and target point, the environmental height and environmental gradient constraints to construct the cost function. Then Analyze different characteristics of the paths that are generated by modifying the constraint function. Optimize the smoothness of the generated path for the field UGV. The path is optimized from broken lines into a curve by using a 5th order polynomial trajectory.

关键词： Unmanned Ground Vehicles Environment Perception Path Planning RBF Neural Network optimization algorithm

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Using Genetic algorithms for Safe Swarm Trajectory optimization

Using Genetic Algorithms for Safe Swarm Trajectory Optimizat...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Rughani, Rahul Barnhart, David A. Univ Southern Calif Informat Sci Inst ISI Astronaut Engn Dept Marina Del Rey CA 90292 USA Univ Southern Calif Space Engn Res Ctr SERC Marina Del Rey CA 90292 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Satellite swarms are groups of spacecraft that operate cooperatively to perform a common task or goal in orbit. Examples of this are in-space assembly or manufacturing of structures, cooperative sensing platforms, on-orbit servicing, asteroid mining, etc. Swarms would be operating in relative-motion orbits, working around a common point in space, within a few kilometers of each other. Such swarms would share information between each member of the swarm, allowing them to have a shared situational awareness of the entire mission. This paper describes a novel approach to optimize relative-motion orbital trajectories for a spacecraft swarm of arbitrary size and function, using genetic algorithms. The use of genetic algorithms allows convergence to an optimal set or family of trajectories for each member of the swarm regardless of the size of the swarm or mission functions required, should a solution exist. These trajectories will be such that each spacecraft can perform their required individual actions while minimizing the fuel required for maneuvering and also avoiding conjunctions, to a prescribed probability of collision, for a given amount of time. Genetic algorithms have been used previously for optimization of low thrust orbit transfers, drone delivery networks, and control of self-driving cars, among other applications.

关键词： Genetic algorithm Satellite Swarm Trajectory optimization Asteroid Mining Drone Spacecraft Structures Micro Gravity Environment optimization algorithm Distributed Computing Orbital Mechanics

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Assessing the Significance of Nesting Order in optimization Using Multiple Dominance Relations

Assessing the Significance of Nesting Order in Optimization ...

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AIAA Aviation Forum

作者： Phillips, Samuel T. Jarrett, Jerome P. Univ Cambridge Dept Engn Cambridge CB2 1PZ England

ISBN: (数字)9781624105982

ISBN: (纸本)9781624105982

A promising alternative to the traditional objectives-and-constraints formulation for optimization that uses multiple dominance relations has recently been developed. Optimal designs according to one dominance relation are sought within the set of designs that are optimal according to some other relation. This problem formulation allows the designer to express more accurately what it is they want from an optimization, resulting in more efficient use of computational resources by focussing the search on designs that are of interest. A key feature of this new formulation is the nesting of multiple dominance relations, and this work assesses whether the ordering of dominance relations within this hierarchical structure is significant. A two-dimensional transonic airfoil design problem is used for this purpose, with design parameters classified as being primary objectives, desirable features, or design requirements. These three classifications result in six possible nesting arrangements, each of which is applied to scenarios comprising one and two primary objectives. Results show that the ordering of dominance relations is significant, with a well chosen arrangement actively assisting the scheme by preventing it from wasting a substantial proportion of the available computational budget searching regions of design space that are of little interest to the designer.

关键词： Airfoil Pitching Moment Computational Fluid Dynamics Angle of Attack Skin Friction Coefficient optimization algorithm Computer algorithm Aerospace Designs

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