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Burden Distribution Decision for Blast Furnace Based on Multiple Condition State

Burden Distribution Decision for Blast Furnace Based on Mult...

引用

第37届中国控制会议

作者： Huicong Chen Jianqi An School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

The relationship of state parameters and burden distribution is uncertain in blast furnaces. In the present industry,burden operation mainly relies on the experiences of the workers. So it is difficult to control burden operation. To solve these problems, this paper presents a model to adjust the burden distribution using fuzzy C-means（FCM） and wavelet analysis. First,multiple condition states of blast furnaces are analysed through data processing, the state parameters are clustered based on the similarity, and then this paper searches for the corresponding burden parameters from the history data. Finally, for different state clusters, best burden parameters are selected to adjust the conditions. Simulation results show that the burden distribution adjustments based on the state parameters clustering are efficient.

关键词： Multiple Condition Burden Distribution Fuzzy C-Means Blast Furnace

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Multi-robot distributed cooperative monitoring of mobile targets 3rd

Multi-robot distributed cooperative monitoring of mobile tar...

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3rd International Conference on Intelligence Science, ICIS 2018

作者： Jiang, J.Q. Xin, B. Dou, L.H. Ding, Y.L. School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9783030013127

Cooperative monitoring targets of mobile robots is of great importance in military, civil, and medical applications. In order to achieve multi-robot coordinated monitoring, this paper proposes a new distributed path planning algorithm. In this algorithm, a method of dynamic sequential decision making is used firstly to determine which robots should be moved to the neighbourhoods of the target path. A distributed cooperative path planning algorithm is then proposed in which the robots can only utilize their local information to make the joint monitoring areas of robots cover the target path. To reduce the chance of detection and ensure enough time to implement monitoring handover, our distributed algorithm can guarantee enough overlapped monitoring areas between adjacent robots. The effectiveness of the algorithm was verified by simulation experiments and a comparison experiment in typical scenarios. © IFIP International Federation for Information Processing 2018.

关键词： Monitoring

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Stochastic stability of evolutionary prisoner's dilemma

Stochastic stability of evolutionary prisoner's dilemma

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2018 Australian and New Zealand control Conference, ANZCC 2018

作者： Liang, Haili Zhou, Zhao Zhang, Fan Peng, Chen Wang, Yu-Long Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Mathematics Southeast University Nanjing China

ISBN: (纸本)9781538666173

In this paper, we study two-player evolutionary prisoner's dilemma on regular graphs and identify the stochastically stable equilibria for infinite populations. We consider four different update rules: Birth-death(BD), death-birth(DB), imitation(IM) and pairwise comparison(PC). With the same values of cost and benefit of cooperation, we show that there is a unique stochastically stable equilibrium for evolutionary prisoner's dilemma on regular graphs. If the benefit-to-cost ratio is larger than k + 2 (k is the degree of a regular graph), the networked game has a higher fraction of cooperators than that for a well-mixed population. Under certain conditions, the lower graph connectivity can lead to the emergence of more cooperators. Besides theoretical analysis, we demonstrate our results through numerical computations and simulations as well. © 2018 IEEE.

关键词： Stochastic systems

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Bifurcation and stability analysis of a delayed fractional-order gene regulation networks with uncertain order 8

Bifurcation and stability analysis of a delayed fractional-o...

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8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Applications, ISCIIA and ITCA 2018

作者： Liu, Feng Dong, Ting Sun, Fenglan Ling, Guang School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Research Center of System Theory and Application Chongqing University of Posts and Telecommunications Chongqing400065 China School of Science Wuhan University of Technology Wuhan430070 China

Bifurcation and stability analysis for a fractional-order gene regulatory networks with time delay is researched. Firstly, taking time delay as the bifurcation parameter, the Hopf bifurcation and stability conditions are established. Finally, a numerical example verifies the theoretical conclusion. It is showed that time delay can heavily effect the dynamics of the system and each order has a major influence on the creation of bifurcation simultaneously. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Time delay

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Ultrasonic Signal Denoising Based on a New Wavelet Thresholding Function

Ultrasonic Signal Denoising Based on a New Wavelet Threshold...

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第37届中国控制会议

作者： Yan Luo Wei Xue Yunyun Yu School of Autonation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systemsy

In the ultrasonic nondestructive testing, the echo signal is polluted by noise and the signal-to-noise ratio is low. To solve the problem, a new wavelet thresholding function is introduced in this paper based on soft and hard thresholding functions. Compared with the existing improved thresholding functions, the new thresholding function is simple in computation and continuous and easy to adjust, it is suitable for some kinds of mathematical disposals. The simulation results show that the new thresholding function can suppress the noise effectively, it is better than soft and hard thresholding functions and the existing improved thresholding functions and has high practical value.

关键词： Wavelet Threshold Denoising Ultrasonic Detection Signal to Noise Ratio Signal Processing

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Deep Forest-Based Classification of Hyperspectral Images

Deep Forest-Based Classification of Hyperspectral Images

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第37届中国控制会议

作者： Xu Yin Ruilin Wang Xiaobo Liu Yaoming Cai School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Computer Science China University of Geosciences

The classification of hyperspectral images(HSIs) is a hot topic in the field of remote sensing technology. In recent years, convolutional neural network(CNN) has achieved great success for HSI classification. However, CNN has to do a great effort in parameters tuning which is time-consuming. Furthermore, a large number of samples are required to train CNN,nevertheless, it is expensive to obtain enough training samples from HSIs. In this paper, we propose a novel classification approach based on deep forest. To reduce the dimension of hyperspectral data, principal component analysis(PCA) is performed during the pre-processing. In contrast to the CNN, our method has fewer hyper-parameters and faster training speed. To the best of our knowledge, this is among the first deep forest-based hyperspectral spectral information classification. Extensive experiments are conducted on two real-world HSI datasets to show the proposed method is significantly superior to the state-ofthe-art methods.

关键词： Deep Forest Hyperspectral Image（HSI） Deep Neural Network（DNN） Principal Component Analysis（PCA）

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Empirical Research on a Fuzzy Model of Music Emotion Classification based on Pleasure-Arousal Model

Empirical Research on a Fuzzy Model of Music Emotion Classif...

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第37届中国控制会议

作者： Siqi Huang Li Zhou Zhentao Liu Shan Ni Jingxian He School of Arts and Communication China University of Geosciences School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Affective computing plays a key role in music artificial intelligence, in which a music emotion classification model is indispensable. Both discrete classification model and continuous dimensional model are commonly used for music emotion classification. However, these models are not designed in views of composers, which is insufficient for the perception of music emotion. In this paper, a fuzzy music emotion classification model is proposed by extracting the music expression marks considering the composers emotion. Experiments on subjective evaluation in the feeling of pleasure and arousal according to the change of three selected features（i.e., tempo, register, and dynamic） are conducted by listeners from different subjects. The experimental results show that the correlation between the proposal fuzzy model and the the results from questionnaires reaches 80% on average, which demonstrate the validity of the proposed fuzzy music emotion classification model. The proposal could be applied to music emotion generation conveyed from either composers or players, and to emotion recognition of music as for audiences.

关键词： Music emotion Classification Affective computing Pleasure-Arousal model Fuzzy logic

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Simulation and Experimental Study on Piezoelectric Geophone Core Based on PMN-PT

Simulation and Experimental Study on Piezoelectric Geophone ...

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第37届中国控制会议

作者： JunLei Song YanXia Huang ZhiHeng Yang MeiJuan Chen Yong Yang WenQin Mo KaiFeng Dong Fang Jin School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mathmatics and Physics China University of Geosciences

Piezoelectric geophones are vibration detectors that convert vibration acceleration signals into electrical signals. High performance piezoelectric materials can improve the sensitivity of piezoelectric geophone and meet the need of high-resolution seismic data acquisition. The comprehensive performance of relaxor piezoelectric single crystal PMN-PT is more superior than PZT, and it is potential to be applied to high sensitivity and small volume geophones. In this paper, the central compressed geophone core model based on PMN-PT was established and theoretically analyzed. Then, a multiphysics simulation model was set up in COMSOL for simulation calculation. Finally, experimental verification was carried out. The results show that using PMN-PT in geophone core design can improve the sensitivity of the model by more than 120% compared with the traditional PZT material. The PMN-PT has the potential to be applied to high sensitivity and small volume geophones.

关键词： PMN-PT PZT Piezoelectric geophone Seismic exploration Accelerometer

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To Improve Drilling Efficiency by Multi-objective Optimization of Operational Drilling Parameters in the complex Geological Drilling Process

To Improve Drilling Efficiency by Multi-objective Optimizati...

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第37届中国控制会议

作者： Chao Gan Weihua Cao Kangzhi Liu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Electronic Engineering Chiba University

Operational drilling parameters optimization is necessary for increase drilling efficiency in complex geological drilling process. There are four key objectives to evaluate the drilling efficiency, including drilling cost, rate of penetration（ROP）, drill bit life, and drill bit’s specific energy. In this paper, we proposed a multi-objective optimization method to improve drilling efficiency in the complex geological drilling process considering all the four key objectives. Firstly, the characteristics of complex geological drilling process and optimization problems are analyzed to find the vital process parameters and problems for drilling efficiency optimization. Then, a multi-objective optimization model which combines the four key objectives is ***, an improved nondominated sorting genetic algorithm（improved NSGA-II） is used to optimize the operational drilling parameters include weight on bit（WOB） and rotational speed（RS） to make drilling efficiency improved. The real case results demonstrate that our method increases the drilling efficiency in four key objectives and saves the simulation time. The proposed method provides the foundation for intelligent optimization control in complex geological drilling process.

关键词： Operational Drilling Parameters Multi-objective Optimization complex Geological Drilling Process Drilling Efficiency Improved NSGA-II

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Application of pseudo random correlation identification method based on LabViewin electromagnetic prospecting

Application of pseudo random correlation identification meth...

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Chinese control Conference (CCC)

作者： Fan Li ZhiHua Li Hongwei Li Zikun Yang Pei Gao Wenqi Zhou School of Automation china University of Geosciences Wuhan Hubei Key Laboratory of Advanced Contol and Intelligent Automation for Complex Systems Wuhan

Electromagnetic exploration plays an important role in the development of mineral, oil and gas resources and other minerals. With the improvement of exploration depth and longitudinal resolution, as well as the increasing humanistic interference in modern society, the electromagnetic exploration method put forward higher requirements. Improving the signal to noise ratio is the key to the development of electromagnetic exploration. Since the pseudo-random sequence is proposed as an artificial field source in the exploration of electromagnetic field, the pseudo-random technique based on correlation identification is also applied to the exploration of electromagnetic method in view of the good correlation characteristics and anti -jamming ability of pseudo-random sequence. In this paper, the principle of correlation identification is introduced, and the realization of correlation spectrum analysis in Lab View is studied. The 2 n sequence pseudorandom signal is used as system excitation signal to verify the anti-jamming performance of correlation identification method in electromagnetic prospecting. It has great application prospect.

关键词： Correlation Interference Electromagnetics Spectral analysis Signal to noise ratio White noise Fourier transforms

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