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第35届中国控制与决策会议

作者： Liyao Yang Hongyan Ma Yingda Zhang Shengyan Li School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture School of Electrical and Information Engineering Institute of Distributed Energy Storage Safety Big DataBeijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture

An improved support vector machine model for energy consumption prediction is proposed to achieve efficient energy saving in *** this paper,firstly,a gray correlation analysis model is used to measure the correlation between temperature,humidity,sunlight and other factors and building energy ***,the sparrow search algorithm(SSA) is introduced to optimize the penalty coefficient c and kernel function parameter g of the support vector machine,and then the SSA-SVM energy consumption prediction model is ***,the experimental results are analyzed by comparing with the data derived from the support vector machine prediction(SVM) model and BP neural network energy consumption *** experimental results show that compared with SVM and BP neural network,the prediction results of SSA-SVM model perform better in error index,indicating that the energy consumption prediction of SSA-SVM model has higher prediction accuracy;the maximum relative error of SSA-SVM prediction model is 0.0514,and the maximum relative errors of the other two models are greater than 0.55,indicating that SSA-SVM model has a higher degree of reliability.

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A Study on Application of Artificial Intelligence in College English Teaching Management and Evaluation 3

A Study on Application of Artificial Intelligence in College...

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3rd International Conference on Electronic InformationTechnology and Smart Agriculture, ICEITSA 2023

作者： Feng, Tao Deng, Jianjie Liu, Yiwen Gao, Yanxia Peng, Ling Fu, Jinrong School of Foreign Languages Huaihua University Hunan Huaihua418000 China School of Computer and Artificial Intelligence Huaihua University Hunan Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China School of Computing Science University of Glasgow GlasgowG12 8QQ United Kingdom

ISBN: (纸本)9798400716775

With the rapid development of artificial intelligence, AI technology has been widely applied in various industries, including education. In English teaching, AI technology provides teachers with objective and instructive feedback, offers students a more personalized learning experience, helping them improve their English language skills, etc., and brings new development opportunities and challenges to English teaching as well. However, there are still some problems that need to be solved in college English teaching in our university. For this reason, based on the application of AI technology in college English teaching, this paper mainly explores the impact and application countermeasures of AI on college English teaching from the following four aspects: individuals with differences, teaching management, classroom teaching and teaching evaluation. In addition, the profound integration of college English education and AI will foster the advancement and transformation of college English instruction, ultimately serving as a catalyst for its reform. © 2023 ACM.

关键词： Artificial intelligence

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A Pruning Method Based on the Dissimilarity of Angle Among Channels and Filters

A Pruning Method Based on the Dissimilarity of Angle Among C...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Jiayi Yao Ping Li Xiatao Kang Yuzhe Wang Changsha University of Science and Technology China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transp China

Convolutional Neural Network (CNN) is more and more widely used in various fileds, and its computation and memory-demand are also increasing significantly. In order to make it applicable to limited conditions such as embedded application, network compression comes out. Among them, researchers pay more attention to network pruning. In this paper, we encode the convolution network to obtain the similarity of different encoding nodes, and evaluate the connectivity-power among convolutional kernels on the basis of the similarity. Then impose different level of penalty according to different connectivity-power. Meanwhile, we propose Channel Pruning base on the Dissimilarity of Angle (DACP). Firstly, we train a sparse model by GL penalty, and impose an angle dissimilarity (AD) constraint on the channels and filters of convolutional network to obtain a more sparse structure. Eventually, the effectiveness of our method is demonstrated in the section of experiment. On CIFAR-10, we reduce 66.86% FLOPs on VGG-16 with 93.31% accuracy after pruning, where FLOPs represents the number of floating-point operations per second of the model. Moreover, on ResNet-32, we reduce FLOPs by 58.46%, which makes the accuracy after pruning reach 91.76%.

关键词： Convolution Encoding Convolutional neural networks Kernel Artificial intelligence

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Edge-Dependent Efficient Grasp Rectangle Search in robotic Grasp Detection

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2021年第6期26卷 2922-2931页

作者： Chen, Lu Huang, Panfeng Li, Yuanhao Meng, Zhongjie Shanxi Univ Inst Big Data Sci & Ind Taiyuan 030006 Peoples R China Northwestern Polytech Univ Natl Key Lab Aerosp Flight Dynam Xian 710072 Peoples R China Northwestern Polytech Univ Res Ctr Intelligent Robot Sch Astronaut Xian 710072 Peoples R China

Grasping unseen objects has become one of the most critical abilities of robots, where identifying the feasible grasp locations is the key technique. Previously proposed methods generally rely on grid search strategy, which evaluates grasp candidates at regular interval, or directly adopt the deep convolutional network, which requires large datasets and powerful computational ability. In this article, we propose an edge-based grasp detection strategy, which combines low-level features and a lightweight convolutional neural network (CNN). Specifically, two grip criteria are first introduced to select feasible point pairs and determine the corresponding grasp candidates. Then, a lightweight CNN model is rapidly trained with limited number of samples in order to recognize feasible grasps. Our method does not require additional sensor information and can work well with only RGB image. Comparative experiments on public dataset verify the effectiveness of our efficient grasp search, which is superior to existing grasp search strategies in accuracy and efficiency. Meanwhile, it achieves competitive results with traditional CNN-based methods using less training time. In addition, we also test the proposed approach under real-world robotic grasping scenario.

关键词： Grasping Image edge detection robots Torque Friction Search problems Feature extraction Deep neural network efficient search grasp detection grip criteria robotic grasping

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Semi-supervised Deep Closest Point Method for Point Cloud Registration

Semi-supervised Deep Closest Point Method for Point Cloud Re...

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2021 International Conference on robotics Automation and intelligent Control, ICRAIC 2021

作者： Wu, Yong Shen, Lingfeng Li, Ping Jiangsu Power Transmission and Transformation Co. Ltd. Nanjing211106 China College of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing210023 China

Point cloud registration is one of the key issues in fields that need 3D scenes with global vision, including 3D scene reconstruction in robot technology, high-accuracy 3D map reconstruction in automatic driving, 3D reconstruction of real-time monitoring underground tunnel. Recently, point cloud registration methods based on deep neural networks have made great progress by learning from a large amount of well-aligned point cloud pairs. However, these large-scale labelled samples are usually difficult to obtain in the real-world applications such as visual simultaneous location and mapping of mobile robots which obtains unlabelled scene images in real time. To solve this problem, we propose a deep point cloud registration method based on the semi-supervised learning. Specifically, for the problem of less supervised data, we use Iterative Closest Point (ICP) algorithm to generate pseudo labels for the point cloud samples with unknown rigid transformations, effectively increasing the number of supervised data;in order to amend the pseudo labels, we design an alternating optimization algorithm to jointly learn the pseudo labels and deep point cloud registration model. The deep point cloud registration model and ICP are used alternately to continuously improve the precision of pseudo labels and the performance of the deep model. Experimental results show that this method can still obtain a reliable point cloud registration model even when just observing a small amount of point cloud samples with ground truth labels. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Surface measurement

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A Hybrid Prediction Method Based on MODWT-EMD for Time Series in Wireless Sensor Networks 16

A Hybrid Prediction Method Based on MODWT-EMD for Time Serie...

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16th IEEE International Conference on intelligent Systems and Knowledge Engineering, ISKE 2021

作者： Wang, Zhongmin Jia, Jingwen Gao, Cong Chen, Yanping Xia, Hong Xi'an University of Posts and Telecommunications Xi'an Key Laboratory of Big Data and Intelligent Computing Xi'an China Xi'an University of Posts and Telecommunications School of Computer Science Technology Xi'an China Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an China

ISBN: (纸本)9781665405539

Time series is the main form of sensor data. Time series prediction is conducive to reduce the energy consumption of sensor nodes and increase the service life. As time cost and computation cost of the existing hybrid prediction methods for time series are not good, this paper proposes a hybrid prediction method based on MODWT-EMD for time series. Firstly, the original time series is decomposed into multiple frequency components by Maximal Overlapping Discrete Wavelet Transform (MODWT). Secondly, the multiple frequency components are decomposed successively by Empirical Mode Decomposition (EMD) to obtain IMF components and residuals. IMFs and residuals contain the feature information of time series. Then, the importance of the extracted feature information is scored and sorted by random forest. We select feature information with a higher score. Finally, the selected feature information is input into Bi-GRU for training. We predicted the original time series by the trained Bi-GRU and obtained the prediction results. The experimental results show that the method proposed in this paper can predict the time series effectively. © 2021 IEEE.

关键词： Empirical mode decomposition

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Application of Computer Software Simulation in Building Fire Evacuation Engineering:A Case Study of a University Library in Beijing

Application of Computer Software Simulation in Building Fire...

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第35届中国控制与决策会议

作者： Shun Wang Hongyan Ma Shengyan Li Wei He School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture School of Electrical and Information Engineering Institute of Distributed Energy Storage Safety Big DataBeijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture

University library is an important building for teaching and *** atrium library has the characteristics of good lighting and flexible use,and the atrium structure was extensively ***,the fire in the atrium library will cause more serious *** this paper,we build a fire and evacuation model of a university atrium library and conduct a simulation *** with BIM technology,we restored the physical information of a university library and establish a fire *** was used to simulate the fire somke diffusion,and the smoke factors were analyzed to derive the available safe evacuation time(ASET).Pathfinder was used to simulate personnel evacuation,which determines the required safe evacuation time(REST).The simulation results show that the visibility of the smoke is the most important factor affecting personnel evacuation,and the personnel needs 108 s to evacuate the fire area and 291 s to enter the stairwell to *** the personnel in the library by area can shorten the evacuation time by about 74 *** study is expected to provide support for the fire simulation and personnel evacuation in atrium building.

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Projection methods with linesearch technique for pseudomonotone equilibrium problems and fixed point problems

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2021年第1期83卷 3-14页

作者： Zhu, Li-Jun Yao, Yonghong Postolache, Mihai The Key Laboratory of Intelligent Information and Big Data Processing of NingXia Province North Minzu University Yinchuan750021 China Health Big Data Research Institute of North Minzu University Yinchuan750021 China The Key Laboratory of Intelligent Information and Big Data Processing of NingXia Province North Minzu University Yinchuan750021 China Health Big Data Research Institute of North Minzu University Yinchuan750021 China School of Mathematical Sciences Tiangong Uni-versity Tianjin300387 China Center for General Education China Medical University Taichung40402 Taiwan Department of Interior Design Asia University Taichung Taiwan Romanian Academy Gh. Mihoc-C. Iacob Institute of Mathematical Statistics and Applied Mathematics Bucharest050711 Romania University "Politehnica" of Bucharest Department of Mathematics and Informatics Bucharest060042 Romania

In this paper, we discuss pseudomonotone equilibrium problems and fixed point problems in real Hilbert spaces. With the help of linesearch technique, we propose a projection algorithm without any Lipschitz-type condition for solving equilibrium problems and fixed point problems. We show that the constructed algorithm converges strongly to a common element of the investigated problems. © 2021, Politechnica University of Bucharest. All rights reserved.

关键词： Computers

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A pruning method based on the dissimilarity of angle among channels and filters

arXiv

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arXiv 2022年

作者： Yao, Jiayi Li, Ping Kang, Xiatao Wang, Yuzhe Changsha University of Science and Technology China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transp China

关键词： Convolution

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Visualization Study on the Dynamic Behavior of Shear Thinning Droplets Impacting Superhydrophobic Spheres

SSRN

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SSRN 2024年

作者： Qian, Lijuan Xu, Liujun Sun, Chengbin Lv, Li College of Mechanical and Electrical Engineering China Jiliang University Hangzhou310018 China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China jiliang University Hangzhou310018 China

The surface characteristics and droplet characteristics significantly affect the dynamic behavior of droplet impact on solid surfaces. A visualization platform is utilized in this work to experimentally study the dynamic behavior of shear thinning fluid droplets impacting superhydrophobic spheres. By calculating the diffusion arc angle and diffusion coefficient corresponding to the two-dimensional wetting arc in the maximum diffusion state, the effects of different concentrations, We numbers, particle size ratios on droplets impact are studied. The results show that on the superhydrophobic sphere, as the shear thinning droplet concentration increases, the diffusion diameter increases, and the contact time decreases. Under the same curvature, the contact time between the droplet and the sphere decreases with the increase of We number. After the We number reaches a specific value, the contact time remains unchanged with the increase of We number. Then under different curvature conditions, the contact time increases with the increase of curvature. When the diameter ratio of the sphere to the droplet is D*≥6, the maximum diffusion coefficient remains almost unchanged. However, when D*＜6, the maximum diffusion dimensionless diameter significantly increases as the particle size ratio decreases. Importantly, a theoretical model considering gravity effect is established to predict the maximum dimensionless diameter of shear thinning droplets on superhydrophobic spheres on the basis of energy conservation. The deviation between the maximum dimensionless diameter obtained by this theoretical model and the experimental results is within ± 10%. © 2024, The Authors. All rights reserved.

关键词： Shear thinning

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