检索结果-内蒙古大学图书馆

International Joint Conference on Neural Networks (IJCNN)

作者： Wen-Tao Fu Jun-Fei Qiao Gai-Tang Han Meng College of Electronic Information and Control Engineering Beijing University of Technology Beijing CN College of Electronic Information and Control Engineering Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

In this paper, a novel kind of the dissolved oxygen (DO) concentration control system was proposed based on the T-S fuzzy neural network. The proposed T-S fuzzy neural network controller was used to control the DO concentration in the Benchmark Simulation Model No.1 (BSM1) wastewater treatment platform. The parameters of the neural network were adjusted online through the error back propagation algorithm to get the minimum error. By adjusting the learning rate online, the convergence speed of the system was accelerated, and then the DO concentration in the wastewater treatment system was controlled fast and efficiently in real-time. Compared with BP and PID controllers through the digital simulation, the results showed that the control effect of the DO concentration based on T-S fuzzy neural network control system was better. Besides, the test results under three kinds of weather condition showed that better adaptability and robustness were also gained in this control system.

关键词： Fuzzy control Benchmark testing Artificial neural networks Recycling Neurons

来源：评论

学校读者我要写书评

暂无评论

Spatially distributed sequential array stimulation of tibial anterior muscle for foot drop correction

Spatially distributed sequential array stimulation of tibial...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Hui Zhou Yingying Wang Wanzhen Chen Nanxin Zhang Ludovic Krundel Guanglin Li Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences Shenzhen Guangdong China Shenzhen Key Laboratory of Electromagnetic Control Shenzhen University Shenzhen Guangdong China School of Electronic Loughborough University UK

ISBN: (纸本)9781424492695

Electrode arrays for the ease of electrode placement in the correction of foot drop with surface electrical stimulation have been developed in recent years. However, the configuration and identification of optimal stimulation sites with regard to time efficiency, stimulation comfort, and fatigue resistance is yet to be solved. In this study, the candidate stimulation sites were ranked and selected according to the motor thresholds induced by 1 Hz stimulation trains. Then based on the selected sites, a new stimulation configuration method termed spatially distributed sequential stimulation was tested and compared with traditional single electrode stimulation for foot drop correction in two normal subjects. The preliminary results demonstrated that the motor threshold of spatially distributed sequential stimulation was equal or less than motor thresholds of each stimulus sites. Besides, with the same stimulation parameters, the spatially distributed sequential stimulation induced larger dorsiflexion motion compared with traditional single electrode stimulation. These findings suggest that spatially distributed sequential stimulation on the selected sites might be an effective electrode array configuration method for correcting foot drop with electrical stimulation.

关键词： Electrodes Arrays Muscles Foot Goniometers Fatigue Electrical stimulation

来源：评论

学校读者我要写书评

暂无评论

Bat algorithm with oscillation element

引用

International Journal of Innovative Computing and Applications 2015年第3-4期6卷 171-180页

作者： Cai, Xingjuan Li, Wuzhao Kang, Qi Wang, Lei Wu, Qidi Department of Control Science and Engineering Tongji University Shanghai201804 China Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology 030024 China Shanghai Key Laboratory of Financial Information Technology Shanghai200433 China

Bat algorithm is a novel swarm intelligent algorithm inspired by the echolocation behaviour of bats. However, the exploration capability is not well for some multi-model problems. In this paper, the control theory is applied to analyse the exploration behaviour for each bat, theoretical result shows the update manner in the standard version of bat algorithm can be viewed as a special case of oscillation element. Therefore, a new variant of bat algorithm, called bat algorithm with oscillation element, is designed. Different from the standard version, frequency is set to negative in this new variant. Furthermore, a new parameter, inertia weight is employed to provide a balance between exploitation and exploration. To test the performance, the CEC2013 shifted and rotated benchmark problems are used to compare, simulation results show our method is validity. Copyright © 2015 Inderscience Enterprises Ltd.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

引用

arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

来源：评论

学校读者我要写书评

暂无评论

Adaptive bat algorithm for coverage of wireless sensor network

引用

International Journal of Wireless and Mobile Computing 2015年第3期8卷 271-276页

作者： Cai, Xingjuan Wang, Lei Kang, Qi Wu, Qidi Department of Control Science and Engineering Tongji University Shanghai201804 China Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Taiyuan030024 China Shanghai Key Laboratory of Financial Information Technology Shanghai200433 China

Bat algorithm is a novel swarm intelligent algorithm inspired by the echolocation behaviour of bats. Pulse rate of emission is one important parameter, which is adjusted in an exponential manner in the standard version, however, this manner provides a fast convergent behaviour in the first several generations. With this manner, the exploitation capability is limited. In this paper, a new linear adjusted manner is employed to enhance the local search capability. To test the performance, it is applied to solve the optimal coverage problem of Wireless Sensor Network (WSN). Simulation results show it is effective when compared with the standard version of bat algorithm. Copyright © 2015 Inderscience Enterprises Ltd.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Chiller gradual fault detection based on Independent Component Analysis

Chiller gradual fault detection based on Independent Compone...

引用

第27届中国控制与决策会议

作者： Pu Wang Jiaojiao Xin Xuejin Gao Yachao Zhang College of Electronic and Control Engineering Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing Laboratory for Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781479970186

Aiming at the chiller process variables cannot be strictly obey the Gauss distribution,and the large number of variables between the serious correlation,this paper describes a fault detection method to detect the faults of *** Component Analysis(ICA) approach is used to extract the correlation of variables of chiller and reduce the dimension of measured data.A ICA-based method model is built to determine the thresholds of statistics and calculate statistics I2 and SPE,which are used to check if a fault occurs in *** method is validated using the laboratory data from ASHRAE RP-1043 and compared with Principle Component Analysis(PCA).Results show that the ICA-based method has better fault detection performance of *** has very good sensitivity for early fault and can effectively reduce the false alarm rate.

关键词： Fault Detection,ICA,PCA,Chiller

来源：评论

学校读者我要写书评

暂无评论

The Evaluation Method of PID controller Parameter Tuning Based on Fluent

The Evaluation Method of PID Controller Parameter Tuning Bas...

引用

第27届中国控制与决策会议

作者： Xuejin Gao Siyu Wang Pu Wang College of Electronic and Control Engineering Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing Laboratory For Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781479970186

For the problem that it is difficult to evaluate overall control effects when tuning PID controller parameter,this paper propose an evaluation method tuning PID controller parameter which is based on Fluent and computer aided *** method uses Fluent to emulate controlled object,and Fluent UDF to conduct the unsteady closed-loop control,achieving evaluation for PID controller parameter *** northern platform in one of the station of the Line 5 in Beijing for example,the results show that the method can be effectively evaluate the control effects in different control parameters.

关键词： Fluent PID User-Defined Function subway station

来源：评论

学校读者我要写书评

暂无评论

Natural scene recognition based on Convolutional Neural Networks and Deep Boltzmannn machines

Natural scene recognition based on Convolutional Neural Netw...

引用

IEEE International Conference on Mechatronics and Automation

作者： Jingyu Gao Jinfu Yang Jizhao Zhang Mingai Li Department of Control & Engineering Beijing University of Technology Beijing P.R. China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing P.R. China

ISBN: (纸本)9781479970995

Scene recognition is a significant topic in computer vision, and Deep Boltzmann machines (DBM) is a state-of-the-art deep learning model which has been widely applied in object and hand written digit recognition. However, when the DBM is used in scene recognition, it is difficult to handle large images due to its computational complexity. In this paper, we present a deep learning method based on Convolutional Neural Networks (CNN) and DBM for scene image recognition. First, in order to categorize large images, the CNN is utilized to preprocess images for dimensional reduction. Then, regarding the preprocessed images as the input of the visible layer, the DBM model is trained using Contrastive Divergence (CD) algorithm. Finally, after extracting features by the DBM, the softmax regression is employed to perform scene recognition tasks. Since the CNN can reduce effectively image size, the proposed method can improve the computational efficiency and becomes more suitable for large image recognition. Experimental evaluations using SIFT Flow dataset and fifteen-scene dataset demonstrate that the proposed method can obtain promising results.

关键词： Convolution Feature extraction Sensitivity Computational modeling Training Mathematical model Kernel

来源：评论

学校读者我要写书评

暂无评论

On study of a wheel-track transformation robot

On study of a wheel-track transformation robot

引用

IEEE International Conference on Robotics and Biomimetics

作者： Jianbing Hu Ansi Peng Yongsheng Ou Guolai Jiang Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen China Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781467396769

Wheeled robots usually move fast in relatively even surfaces while losing their major mobility on rough terrains. However, the tracked robots are superior to the wheel-types when they are to move on irregular terrains in spite of lower speed. In this paper, a Wheel-Track Transformation robot which combines the advantages of both mobile types by turning into wheel mode or track mode is designed. The robot consists of a robot platform equipped with an extra support mechanism, two wheels with transformation units and an universal wheel. Each transformation unit is composed of a rotating board and a double two-bar linkage mechanism. Three key mechanical components and several locomotion strategies on rough terrains are presented. Meanwhile, a detailed quasi-dynamic analysis is conducted to obtain proper torque capabilities of motors. Three prototypes of the proposed mechanism were manufactured and their fundamental mobility was evaluated by experiments.

关键词： Mobile robots Wheels Couplings Force Torque Tracking

来源：评论

学校读者我要写书评

暂无评论

A new motion control method for omnidirectional intelligent wheelchair based on improved Fuzzy Support Vector machine

A new motion control method for omnidirectional intelligent ...

引用

IEEE International Conference on Mechatronics and Automation

作者： Wentao Guo Songmin Jia Tao Xu Xiuzhi Li College of Electronic and Control Engineering Beijing University of Technology Beijing China Ministry of Education Engineering Research Center of Digital Community Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9781479970995

This paper proposed the FSVM (Fuzzy Support Vector machine) based on affinity to achieve the intelligent wheelchair motion control. The gravity center, which can be computed by calculating the weights of four force sensors under the wheelchair seat, is the key factor to determine the intention of movement of the user. The improved fuzzy membership function of FSVM can reduce the effect of clustering gravity center caused by abnormal clustering gravity center data generated from malfunction. Comparing with the traditional SVM (Support Vector machine), the improved FSVM algorithm has lower error rate. This paper further validates the practical feasibility and validity of the proposed control algorithm. The experiment results show that the proposed algorithm can improve the precision of omnidirectional intelligent wheelchair motion control.

关键词： Wheelchairs Gravity Support vector machines Clustering algorithms Training Force sensors Noise

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：