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Association rules mining algorithm using sharing mechanism niche leaping ant colony based on apriori algorithm

Journal of Computational and Theoretical Nanoscience 2015年第10期12卷 3223-3231页

作者： Wang, Yang Xu, Yakun Li, Gang Wang, Hongliang MicroNano System Research Center College of Information Engineering Taiyuan University of Technology Taiyuan Shanxi China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of Technology Taiyuan Shanxi China Ministry of Education North University of China Taiyuan China

Based on the alarm data in the information communication network under the context of big data, the paper discusses the classic association mining algorithms of Apriori and FP-Growth with living examples, elaborates the ant colony algorithm and the niche technology, combines the Apriori algorithm thought and the Travelling Salesman Problem (TSP) of the ant colony algorithm, and proposes association rules mining algorithm using Sharing mechanism Niche Leaping Ant Colony based on Apriori algorithm (SN-APLAC algorithm). The algorithm achieves the thought of "leaping ants" by accelerating support calculation through a sparse linked list and setting the route point of non frequent item sets as "stimulation point" and retains the local optimal solution to further improve the quality of association rules mining utilizing the technique of sharing mechanism niche. Copyright © 2015 American Scientific Publishers.

关键词： Association rules

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Human tracking method based on multi-template color-texture mean-shift algorithm

Human tracking method based on multi-template color-texture ...

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IEEE International Conference on Mechatronics and Automation

作者： Linfeng Wen Songmin Jia Lijia Wang 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

Human tracking is a hot topic and a challenging task during the past few decades. This paper present a multi templates based strategy for human detecting and tracking with a mobile robot. This method first determines the coarse location by using adaptive template matching algorithm (ATM) based on head-shoulder. Then, a multi-templates based method is presented to locate the person precisely. Multi templates considering the pose changes are obtained to represent the person. For each template, the mean-shift is proceeded. Then, the accurate position is obtained by fusing the results of the Mean-shift from all the templates. After detecting the person, the templates are updated by considering the likelihood of the tracking results and the old templates. Finally, the method is evaluated on a mobile robot in complex environment. The experiment result shows that our method performs well when there are unclear disparity image and pose variations.

关键词： Image color analysis Histograms Target tracking Mathematical model Cameras Mobile robots Robot vision systems

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Development of a control algorithm to improve fuel economy for PHEV considering driver tendency

Development of a control algorithm to improve fuel economy f...

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International Conference on Ecological Vehicles and Renewable Energies (EVER)

作者： Seulgi Lee Jingyu Choi Sunyoung Park Jaemyoung Pi Heejin Shin Hyunsoo Kim Kiyun Jeong School of Mechanical Engineering Sungkyunkwan University Suwon-si Republic of Korea Intelligent Control System R&D center Korea Automotive Technology Institute Cheonan-si Republic of Korea

In this study, an engine on/off and engine operation control algorithm to improve the fuel economy was proposed for a PHEV(plug-in hybrid electric vehicle) considering driver tendency. To identify the driver tendency, a driver model was developed using VIDE (virtual integrated development environment). The target vehicle model was developed based on MATLAB/Simulink and validation of the vehicle model was performed by experiments. Using the VIDE, real drivers who have different tendency drive the PHEV in virtual environment and driving data were accumulated. Using the driving data, the driver model which can reflect the driver tendency was developed. To describe the driver tendency, degree of driver aggression (DDA) was proposed, which was determined by fuzzy logic. The DDA was applied to the PHEV control algorithm to improve the fuel economy. This algorithm controls the engine on/off and engine operation, which provides the improved fuel economy.

关键词： Vehicles Engines MATLAB Batteries Analytical models Data models system-on-chip

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Corrigendum to “A Novel Improved Probability-Guided RANSAC Algorithm for Robot 3D Map Building”

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Journal of Sensors 2016年第1期2016卷

作者： Songmin Jia Ke Wang Xiuzhi Li Tao Xu College of Electronic and Control Engineering Beijing University of Technology Beijing 100124 *** Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124 *** Engineering Research Center of Digital Community Ministry of Education Beijing 100124 *** School of Mechanical and Electrical Engineering Henan Institute of Science and Technology Xinxiang 453003 ***

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Environment exploration and recognition for mobile robot using immune algorithm and objectness measure

Environment exploration and recognition for mobile robot usi...

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IEEE International Conference on Mechatronics and Automation

作者： Wenbin Qu Songmin Jia Xue Zhao College of Electronic Information & Control Engineering Beijing University of Technology Beijing China Engineering Research Center of Digital Community Ministry of Education Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9781479970995

In order to complete a service task more efficiently, robot needs to create a map quickly and recognize objects during this process. In this paper, a novel mapping method is proposed to address this problem. Firstly, Admissible Space Tree is generated to acquire possible node. Then, immune algorithm is applied for its advantages such as diversity, dynamic, parallel management and self-adaptation. And antibody affinity is constructed to select optimal path. Meanwhile, robot recognizes key objects on its way to get the semantic information. To achieve this purpose, normed gradients feature has been extracted to describe the object windows. It is based on just a few training images and also has the ability to learn incrementally. Subsequently, three support vector machines are respectively used for objectness estimation and object types detection. Experimental results demonstrate that the presented method can build a semantic map more efficient, which verifies the feasibility of proposed algorithm.

关键词： Immune system Support vector machines Semantics Robot sensing systems Algorithm design and analysis Object recognition

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Trajectory prediction and alerting for aircraft mode and energy state awareness

Trajectory prediction and alerting for aircraft mode and ene...

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AIAA Infotech @ Aerospace 2015

作者： Shish, Kimberlee Kaneshige, John Acosta, Diana Schuet, Stefan Lombaerts, Thomas Martin, Lynne Madavan, Avinash N. Intelligent Systems Division Millennium Engineering and Integration Company NASA Ames Research Center Mail Stop 269-1 Moffett FieldCA94035 United States Intelligent Systems Division NASA Ames Research Center Mail Stop 269-1 Moffett FieldCA94035 United States Institute of System Dynamics and Control German Aerospace Center DLR Münchner Straße 20 Weßling82234 Germany Human Systems Integration Division San Jose State University NASA Ames Research Center Mail Stop 262-4 Moffett FieldCA94035 United States Intelligent Systems Division Universities Space Research Association NASA Ames Research Center Mail Stop 269-1 Moffett FieldCA94035 United States

ISBN: (数字)9781624103384

ISBN: (纸本)9781624103384

This paper describes the implementation and evaluation of technologies that predict and assess the future aircraft energy state and autoflight configuration, and provide appropriate alerting to better inform pilots of the effect of problematic autoflight inputs or conditions. Prediction algorithms are used to extrapolate the current state of the aircraft based on flight management, autopilot and autothrottle system control laws and knowledge of mode transition logic. The resulting predicted trajectory represents the future four-dimensional flight path of the aircraft if the current course of action is continued. Probabilistic methods are used to estimate the trim envelope through high-fidelity model-based computation of attainable equilibrium sets. The corresponding maneuverability limitations of the aircraft are determined through a robust reachability analysis (relative to the trim envelope) through an optimal control formulation. The combination of prediction and assessment technologies are used to trigger timely alerts to avoid loss of control situations. The maneuvering envelope limits are also indicated on the primary flight display, and the predicted trajectory is displayed on navigation and vertical situation displays. The display features and alerts were evaluated in the Advanced Concepts Flight Simulator at NASA Ames Research center, where commercial airline crews flew multiple problematic approach and landings scenarios to investigate the impact on current and future aircraft energy state awareness. Results show that the display features and alerts have the potential to improve situational awareness of what the automation is doing now and what it will do in the future. © 2015, American Institute of Aeronautics and Astronautics Inc. All rights received.

关键词： Forecasting

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A Fallback control Study of Networked control systems for Cybersecurity

A Fallback Control Study of Networked Control Systems for Cy...

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Asian control Conference

作者： Kenji Sawada Tsubasa Sasaki Seiichi Shin Shu Hosokawa Dept. of Mechanical Engineering and Intelligent Systems The University of Electro-Communications Control System Security Center

ISBN: (纸本)9781479978632

Recent control systems of critical infrastructures are networked systems, which are exposed to the infection of the computer malwares. This paper considers a cybersecurity technology of networked control systems in terms of availability. Architecture of fallback control is proposed, which consists of the remote controller and the local controller. The former achieves the high control performance and the latter guarantees the minimum required control performance. If the malicious behavior of the remote controller is detected by the local controller, the local controller breaks the network communication between the plant and the remote controller and takes over the plant control. This framework aims to prevent the spread of the damage caused by the infection of the computer malwares. As a first step of the research, a prototype fallback control system is applied to a simple automation system simulating the defective discriminator.

关键词： Fallback control Cybersecurity Networked control system Availability

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Spinning reserve optimization using reliability constrained unit commitment

Spinning reserve optimization using reliability constrained ...

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IEEE Region 10 International Conference TENCON

作者： M. Q. Wang P. P. Yang Q. Zhang Y. Wang Key Laboratory of Power System Intelligent Dispatch and Control Shandong University linan Shandong Province China Shandong Electric Power Engineering Consulting Institute Limited Co. linan Shandong Province China Shandong Electric Power Dispatching and Control Center Jinan Shandong Province China

ISBN: (纸本)9781479986422

Maintaining an appropriate amount of spinning reserve (SR) is a necessary condition to keep the reliable operation of power systems. In this paper, a probabilistic method is proposed to determine the optimal SR amount where the reliability levels are well kept. The SR amount is optimized through a reliability constrained unit commitment (RCUC). In the RCUC model the reliability indexes must be smaller than their upper limits are involved as the constraints. The introduction of the reliability indexes makes the optimization computation intensive. In this paper, a multi-step method is proposed to solve the problem efficiently. The reliability indices such as the expected energy not supplied and loss of load probability are analytically approximated in terms of piecewise linear formulations. The approximation error is gradually eliminated as the step progresses. The superiority of proposed technique is illustrated by the IEEE reliability test system. efficiency and validity of the proposed method is verified using the.

关键词： Reliability Indexes Spinning Probabilistic logic Computational modeling Computational efficiency

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Consistency analysis of SCADA data from field power systems

Consistency analysis of SCADA data from field power systems

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10th International Conference on Advances in Power system control, Operation & Management (APSCOM 2015)

作者： Yaping Zhang Hengxu Zhang Liang Wang Guangsong Hou Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education School of Electrical Engineering Shandong University Jinan China Dispatch and Control Center of Shandong Electric Power Corporation Jinan China Heze Power Supply Company of State Grid Shandong Electric Power Corporation China

ISBN: (纸本)9781510830059

SCADA (Supervisory control And Data Acquisition) system is a basic infrastructure of modern power systems. SCADA data are widely used in applications such as state estimation, power flow calculation, and on-line security assessment. The accuracy of the SCADA data directly affects the implementation of power system automatic control. In practice, the error of the SCADA data may deviate from its factory precision due to the influence of the equipment aging, data transmission and so on. To quantitatively evaluate the validity of the SCADA data, a consistency index is defined in this paper. Some SCADA data from several substations of a power gird is checked with the consistency index to reveal its reliability.

关键词： consistency power systems SCADA error analysis

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A new hybrid tracking strategy based on Pulse Coupled Neural Network

A new hybrid tracking strategy based on Pulse Coupled Neural...

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International Conference on Information and Automation (ICIA)

作者： Songmin Jia Tao Xu Zhengyin Dong Xiuzhi Li Peng Zhang College of Electronic and Control Engineering Beijing University of Technology Beijing China Engineering Research Center of Digital Community Ministry of Education Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China School of Mechanical and Electrical Engineering Henan Institute of Science and Technology Xinxiang China

ISBN: (纸本)9781467391054

Visual object tracking is a fundamental research topic in computer vision. In this paper, we proposed a novel hybrid tracking method based on Pulse Coupled Neural Network (PCNN) and Multiple Instance Learning (MIL). Most modern trackers may be inaccurate when the training samples are imprecise which causes drift. To resolve these problems, MIL method is introduced into the tracking task, which can alleviate drift to some extent. However, the MIL tracker may detect the positive sample that is less important. PCNN is different from traditional artificial neural networks, which can be applied in many image processing fields, such as image segmentation. So, the PCNN was employed as sample detector which can know the most important sample when training the classifier. Then, a more robust and much faster tracker is proposed to approximately maximize the bag likelihood function. Empirical results on a large set of sequences demonstrate the superior performance of the proposed approach in robustness, stability and efficiency to state-of-the-art methods in the literature.

关键词： Target tracking Neurons Visualization Object tracking Image segmentation Computer vision Computational modeling

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