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Application of neural network in modeling of activated sludge wastewater treatment process 36

Application of neural network in modeling of activated sludg...

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第36届中国控制会议

作者： Li Jun Zhang Neng Li Jing Jing Zhang Xi Yong Tian School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

This paper present a prediction model for three different objection(the airflow rate,the carbonaceous biochemical oxygen demand(CBOD) of the effluent,and the total suspend solids(TSS) of the *** model is built by the MLP neural *** accurancy of the prediction result of MLP neural network is compared with the accurancy of the result of trational stational autoregressive model(AR).The conclution is that the percentage error prediction model of the MLP neural network(PE),the fractional deviation(FB),normalized mean square error(NMSE),the mean absolute error(MAE) and mean square error(MSE) prediction model of evaluation index is better than the AR *** other words,the prediction model based on MLP neural network provides a reliable basis for reducing the energy consumption in the activated sludge process of industrial waste water treatment and further improving its effect on the treatment of industrial waste water.

关键词： Industrial waste water treatment Activated sludge process MLP neural network Data mining

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Speaker-independent Speech Emotion Recognition Based on Random Forest Feature Selection Algorithm 36

Speaker-independent Speech Emotion Recognition Based on Rand...

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第36届中国控制会议

作者： Wei-Hua Cao Jian-Ping Xu Zhen-Tao Liu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Feature selection is a crucial step in the development of a system for identifying emotions in *** to select high correlation features is an open *** paper focuses on feature selection method which aims to extract the most effective acoustic features to improve the performance of emotion *** feature selection of speakerindependent speech based on Random Forest is proposed,which can remove the redundant features that have high correlations with each *** on the speech emotion recognition based on Support Vector Machines(SVM) is performed,where the speaker-independent features selected by the proposal and Spearman correlation analysis are used for emotion recognition,*** results show that the proposal achieves 78.6%recognition rate on average,which is 2.2%higher than using Spearman.

关键词： Emotion Recognition Speech Speaker-independent Feature Selection Random Forest

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Experimental Study on Decentralized Concurrent Learning for Multi-Agent System with complex Dynamics 36

Experimental Study on Decentralized Concurrent Learning for ...

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第36届中国控制会议

作者： Ting Fei Xin Chen Min Wu Chi Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

A cooperative multi-agent system entitles some independent agents to complete complex tasks through coordination and *** the dynamics of physical agents are so complex that the environment of learning is indeed stochastic,the paper introduces the decentralized multi-agent reinforcement learning（MARL） algorithm,named as Decentralized Concurrent Learning with Cooperative Policy Exploration（DCL-CPE）,in order to solve cooperative learning within stochastic *** investigate its feasibility in practical multi-agent systems,the box-pushing test with DCL-CPE is designed with a group of two-wheel driven robots acting as learning *** to physical properties,such as nonholonomic dynamics,rolling and sliding frictions,unreliable sense,rigid body collision,etc.,the cooperative learning is a high stochastic learning *** simulation test in Webots shows that DCL-CPE is good at exploring best cooperative policy in a decentralized way,even as state transition and rewards are all stochastic.

关键词： Multi-agent system Decentralized cooperative learning Stochastic environment Webots

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Adaptive Generalized Projective Synchronization of a New Fractional Chaotic System with uncertain parameters

Adaptive Generalized Projective Synchronization of a New Fra...

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第30届中国控制与决策会议

作者： Jiaoru Huang Kun Zhong Fucai Qian The International Joint Research Center of Autonomous Systems and Intelligent Control Xi'an Technological University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

This paper investigates the generalized projective synchronization scheme of a new fractional chaotic system, which can display a four-wing chaotic attractor when the order of system is in the range of 0.82 and ***, considering the situation with unknown parameters, an adaptive nonlinear controller is obtained for synchronization and parameters identification based on fractional-order Lyapunov stability theorem. The fractional-order adaptation law, which can update parameters estimation errors online, is derived to ensure the stability of synchronization error system. Numerical simulations are used to verify the results.

关键词： Four-wing chaotic attractors uncertain parameter generalized projective synchronization parameter identification

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ICB-MOEA/D: An interactive classification-based multi-objective optimization algorithm

ICB-MOEA/D: An interactive classification-based multi-object...

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第37届中国控制会议

作者： Bin Xin Hepeng Li Ling Wang School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Department of Automation Tsinghua University

Interactive multi-objective optimization algorithms have developed rapidly in recent years. In this paper, we propose a new classification-based interactive multi-objective optimization algorithm named ICB-MOEA/D to solve the formulated multiobjective optimization problem. ICB-MOEA/D provides several solutions for the decision maker to choose. The decision maker chooses his/her most preferred solution from these solutions and the historical solutions which have been chosen as the current most preferred solution. ICB-MOEA/D records this solution and classifies the objectives according to the updated preference information into four categories: 1) objectives which are expected to be improved;2) objectives which can be sacrificed;3) objectives which are expected to remain basically unchanged;4) objectives which do not matter currently. Accoding to the number of the objectives in the first category, a new single-objective opitimization model or multi-objective optimization model will be built. The single-objective optimization model will be optimized by a classic variant of differential evolution DE/rand/1/bin, and the multi-objective optimization model will be optimized by a popular docomposition-based multi-objective optimizer MOEA/*** the classifications are done automatically by the algorithm, reducing the burden of the decision maker. ICB-MOEA/D was tested on the two-objective instance ZDT1, and the experiment results show the effectiveness of ICB-MOEA/D.

关键词： interactive multi-objective optimization decomposition classification virtual decision maker

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A Multi-model Estimation of Distribution Algorithm for Agent Routing Problem in Multi-point Dynamic Task

A Multi-model Estimation of Distribution Algorithm for Agent...

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第37届中国控制会议

作者： Sai Lu Bin Xin Lihua Dou Ling Wang School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Department of Automation Tsinghua University

The agent routing problem in multi-point dynamic task（ARP-MPDT） is a multi-task routing problem of a mobile agent. In this problem, there are multiple tasks to be carried out in different locations. As time goes on, the state of each task will change nonlinearly. The agent must go to the task points in turn to perform the tasks, and the execution time of each task is related to the state of the task point when the agent arrives at the point. ARP-MPDT is a typical NP-hard optimization problem. In this paper, we establish the nonlinear ARP-MPDT model. A multi-model estimation of distribution algorithm（EDA） employing node histogram models（NHM） and edge histogram models（EHM） in probability modeling is used to solve the ARP-MPDT. The selection ratio of NHM and EHM probability models is adjusted adaptively. Finally, performance of the algorithm for solving the ARP-MPDT problem is verified by the computational experiments.

关键词： Estimation of distribution algorithm Multi-model Routing Multi-point dynamic task

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Bat Algorithm Optimizer for Drilling Trajectory designing under Wellbore Stability Constraints

Bat Algorithm Optimizer for Drilling Trajectory Designing un...

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第37届中国控制会议

作者： Jiafeng Xu Xin Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

In the process of deep geological resources exploration, there are often some complex stratigraphic situations. A threedimension drilling trajectory is designed by using the geological environment data. The trajectory should be sure that the target position is reachable. And it can avoid the area prone to be in an accident. In order to solve this problem, this paper discusses a three-dimensional wellbore trajectory design optimization model suitable for shale gas horizontal mining. Considering the wellbore stability and dogleg severity as constraints, the minimum drilling length is taken as the objective function. Depending on the Mohr-Coulomb criterion, the range of azimuth angle and inclination angle of safety trajectory can be determined. It can be seen as a constraint on the wellbore derrick segment. As for the optimization algorithm, bat algorithm（BA） optimizer combined with a penalty function method is applied to this optimization model. Finally, the case study shows that the BA performs well in the wellbore optimization design. It obtains the trade-off result between the safe and efficient drilling demands. And, it provides a basic model idea for the real-time trajectory optimization while drilling.

关键词： Drilling Trajectory designing Wellbore Stability Bat Algorithm

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Multi-Convolution Neural Networks-Based Deep Learning Model for Emotion Understanding

Multi-Convolution Neural Networks-Based Deep Learning Model ...

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第37届中国控制会议

作者： Luefeng Chen Min Wu Wanjuan Su Kaoru Hirota School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Tokyo Institute of Technology

Multi-convolution neural networks-based deep learning model in combination with multimodal data for emotion understanding is proposed, in which facial expression and body gesture are used to achieve emotional states recognition for emotion understanding. It aims to understand coexistence multimodal information in human-robot interaction by using multi-convolution neural networks, where multilayer convolutions are connected in series and multiple networks are executed in parallel. Moreover,when optimizing the weights of deep neural network by traditional method, it is easy to fall into poor local optimal. To address this problem, a hybrid genetic algorithm with stochastic gradient descent is developed, which has the capacity of inherent implicit parallelism and better global optimization of genetic algorithm so that it can adaptively find the better weights of the *** in order to speed up the convergence of the proposal, the weights optimized by stochastic gradient descent will be taken as a chromosome of genetic algorithms initial population, and it also can be used as a priori knowledge. To verify the effectiveness of the proposal, experiments on benchmark database of spontaneous emotion expressions are developed, and experimental results show that the proposal outperforms the state-of-the-art methods. Meanwhile, the preliminary application experiments are also carried out and the results indicate that the proposal can be extended to human-robot interaction.

关键词： Deep learning emotion understanding convolution neural network facial expression body gesture

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A Detection System of Tool Parameter Using Machine Vision

A Detection System of Tool Parameter Using Machine Vision

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第37届中国控制会议

作者： Hantao Wang Hong Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

This paper suggests a novel technique for the tool parameter measurement based on machine vision. Tool images are captured by using a machine vision system and the outer contour image of the cutter is obtained by using the machine vision technology. The HALCON image processing library is used as the development platform to build the tool parameters test system. Several algorithms including image segmentation, edge extraction and fitting ellipse determination is used for image *** tool parameters such as external diameter and contour angle of tool edge can be obtained after rebuilding the contour of tool *** proposed scheme is shown to be reliable and effective for the automated tool parameter measurement.

关键词： Machine vision image processing tool parameter

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A calculation method of braking torque for eddy current dynamometer using least square method based on assumption of cylindrical ring 29

A calculation method of braking torque for eddy current dyna...

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第29届中国控制与决策会议

作者： Li Duo-yang Wang Jun-zheng Shen Wei Chen Ying-hui Zhao Jiang-bo Chen Guang-rong Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

ISBN: (纸本)9781509046584

For engineering applications,the existing method of calculating the braking torque is more ***,the calculation method depends on the internal structure parameters which are often difficult to ***,the calculational method of braking torque using least square method based on assumption of cylindrical ring(CR-LS) is proposed in this *** to calculation methods of eddy current braking devices,The CR-LS assumes that the eddy current is distributed as a cylindrical ring with the same width as the tooth tip of the *** current values are worked out by conversion *** the employ of LS,unknown internal structure parameters of dynamometer in formula are *** makes the formula use in industrial control with *** experimental verification,the formula obtained by CR-LS was simple and available,and calculation results had minor errors in contrast with output values of actual *** CR-LS can be applied in actual engineering calculations of dynamometer.

关键词： Dynamometer Braking Torque Cylindrical Ring CR-LS

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