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Solving the information accumulation problem in mesh structured agent system

IEEE TRANSACTIONS ON POWER SYSTEMS 2007年第1期22卷 493-495页

作者： Huang, K. Srivastava, S. K. Cartes, D. A. Florida State Univ Ctr Adv Power Syst Tallahassee FL 32310 USA

In this letter, the authors propose a spanning tree-based algorithm for an agent system, which breaks the mesh-structured agent system into a single tree-structured agent system. Then an algorithm for recalculating the information flow among agents without redundant information accumulationis presented. Finally, the proposed methodology is illustrated through a simple mesh structured agent system.

关键词： distributed system multiagent system (MAS) redundant information accumulation (RIA) spanning tree algorithm

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Cost Effective Dynamic Multi-Microgrid Formulation Method Using Deep Reinforcement Learning

Cost Effective Dynamic Multi-Microgrid Formulation Method Us...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Jung, YoonGun Chang, Minhyeok Kang, Sungwoo Jang, Gilsoo Lee, Hojun Yoon, Minhan Song, Sungyoon Han, Changhee Korea Univ Dept Elect Engn Seoul South Korea Kwangwoon Univ Dept Elect Engn Seoul South Korea Korea Electrotechnol Res Inst Adv Power Grid Div Uiwang South Korea Univ Calif San Diego Qualcomm Inst San Diego CA USA

ISBN: (纸本)9781665464413

This paper proposes an online Dynamic Multi-Microgrid Formulation (DIVIMF) method using Deep Reinforcement Learning. It aims to reconfigure the microgrid into several self-supplied islands and minimize total operation cost at the same time. spanning tree algorithm is used to reduce the total number of microgrid formulation. Proximal -Policy Optimization is implemented to train the agent which determines the status of sectionalizing switches in microgrid in real-time. To show the effectiveness of the proposed DMMF method, a case study was conducted in the modified cigre-14 bus test network. The results demonstrated that the proposed DMMF method reduced the total operation cost compared to the operation cost derive from original Cigre 14 bus formulation.

关键词： Microgrid (MG) Reconfiguration Dynamic Multi-Microgrid Formulation Distributed generation (DG) spanning tree algorithm Deep Reinforcement Learning (DRL)

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Determination of Safe Landing Zones for an Autonomous UAS using Elevation and Population Density Data

Determination of Safe Landing Zones for an Autonomous UAS us...

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AIAA Science and Technology (SciTech) Forum and Exposition

作者： Carney, Edward Castano, Lina Xu, Huan Univ Maryland Dept Aerosp Engn College Pk MD 20740 USA Univ Maryland Aerosp Engn College Pk MD 20740 USA Univ Maryland Aerosp Engn Inst Syst Res College Pk MD 20740 USA

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

This work determines a safe emergency landing zone for an autonomous UAS by utilizing ground elevation, terrain ruggedness, land coverage, and population density data. The proposed system uses openly available high-fidelity Light Detection and Ranging (LIDAR) datasets and surface reflectance data from the Landsat land remote sensing project to determine potential landing zones based on current UAS position and calculated data provided by these datasets. The elevation data is represented as a set of coordinates and an elevation, with the bounding latitudes and longitudes for the dataset included in the dataset metadata. Threshold values for these data set a minimum required topographic quality for an area to be considered valid for landing. A weighting algorithm is used to determine the optimal landing zone for a given UAV situation and position. A constrained bidirectional rapidly exploring random tree algorithm is used with onetime pruning to generate a path to the chosen landing zone that obeys aircraft heading and motion constraints. We show that the optimal landing zone and corresponding path plan update based on the specified topographic quality threshold values and weighting configuration.

关键词： Dataset flight strip Caste determination Sex Determination Processes cage set Lidar DATA DENSITY setting coordination Coordinates LIght Detection and Ranging Population density calculation data Valid spanning tree algorithm

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A GRAPH algorithmIC FRAMEWORK FOR THE ASSEMBLY OF SHREDDED DOCUMENTS

A GRAPH ALGORITHMIC FRAMEWORK FOR THE ASSEMBLY OF SHREDDED D...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Richter, Fabian Ries, Christian X. Lienhart, Rainer Univ Augsburg D-8900 Augsburg Germany

ISBN: (纸本)9781612843490

In this paper we propose a framework to address the reassembly of shredded documents. Inspired by the way humans approach this problem we introduce a novel algorithm that iteratively determines groups of fragments that fit together well. We identify such groups by evaluating a set of constraints that takes into account shape- and content-based information of each fragment. Accordingly, we choose the best matching groups of fragments during each iteration and implicitly determine a maximum spanning tree of a graph that represents alignments between the individual fragments. After each iteration we update the graph with respect to additional contextual knowledge. We evaluate the effectiveness of our approach on a dataset of 1 6 fragmented pages with strongly varying content. The robustness of the proposed algorithm is finally shown in situations in which material is lost.

关键词： Document assembly spanning tree algorithm Kruskal

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Network Decomposition and Maximum Independent Set Part Ⅱ: Application Research

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Journal of Southwest Jiaotong University(English Edition) 2004年第1期12卷 1-14页

作者：朱松年朱嫱 School of Traffic and Transportation Geac Computers Corporation

According to the researches on theoretic basis in part Ⅰ of the paper, the spanning tree algorithms solving the maximum independent set both in even network and in odd network have been developed in this part, part Ⅱ of the paper. The algorithms transform first the general network into the pair sets network, and then decompose the pair sets network into a series of pair subsets by use of the characteristic of maximum flow passing through the pair sets network. As for the even network, the algorithm requires only one time of transformation and decomposition, the maximum independent set can be gained without any iteration processes, and the time complexity of the algorithm is within the bound of O(V3). However, as for the odd network, the algorithm consists of two stages. In the first stage, the general odd network is transformed and decomposed into the pseudo-negative envelope graphs and generalized reverse pseudo-negative envelope graphs alternately distributed at first; then the algorithm turns to the second stage, searching for the negative envelope graphs within the pseudo-negative envelope graphs only. Each time as a negative envelope graph has been found, renew the pair sets network by iteration at once, and then turn back to the first stage. So both stages form a circulation process up to the optimum. Two available methods, the adjusting search and the picking-off search are specially developed to deal with the problems resulted from the odd network. Both of them link up with each other harmoniously and are embedded together in the algorithm. Analysis and study indicate that the time complexity of this algorithm is within the bound of O(V5).

关键词： Network transformation and decomposition Negative envelope graph Pseudo-negative envelope graph spanning tree algorithm Adjusting search Picking-off search Polynomial time bound.

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Latent tree approximation in linear model

Latent tree approximation in linear model

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Navid Tafaghodi Khajavi Dept. of Electrical Engineering University of Hawaii Honolulu 96822 United States of America

ISBN: (纸本)9781509041183

We consider the problem of learning underlying tree structure from noisy, mixed data obtained from a linear model. To achieve this, we use the expectation maximization algorithm combined with Chow-Liu minimum spanning tree algorithm. This algorithm is sub-optimal, but has low complexity and is applicable to model selection problems through any linear model.

关键词： tree Approximation EM algorithm expectation-maximisation algorithm linear models tree STRUCTURES model selection spanning tree algorithm approximation

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A ROBUST AND LIGHTWEIGHT FEATURE SYSTEM FOR VIDEO FINGERPRINTING

A ROBUST AND LIGHTWEIGHT FEATURE SYSTEM FOR VIDEO FINGERPRIN...

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European Signal Processing Conference

作者： Tzu-Jui Liu Hye Jung Han Xin Xin Zhu Li Aggelos K. Katsaggelos Dept. of EECS Northwestern University

ISBN: (纸本)9781467310680

In this paper, a new content-based feature identification method for video sequences is presented. It is robust to a number of image transformations and relatively lightweight compare to most state of the art methods. A scale and rotation invariant descriptor for a set of interest points in detected key frames is proposed based on modified minimal spanning tree algorithm. In addition, a predicative coding scheme is used to achieve minimal size of the descriptor for transmission. Furthermore, the pairwise distance between the frequency responses of the curvature vector from the descriptors is calculated and compared to efficiently match query with a large database. Experimental results demonstrate the effectiveness of our approach.

关键词： Robust video hashing Content-based fingerprinting Multimedia fingerprinting Video copy detection state of the art Descriptors frequency response Videotapes Video sequences spanning tree algorithm Feature extraction graph transformation

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Using Tarjan's Red Rule for Fast Dependency tree Construction 02

Using Tarjan's Red Rule for Fast Dependency Tree Constructio...

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Annual Conference on Neural Information Processing Systems

作者： Dan Pelleg Andrew Moore School of Computer Science Carnegie-Mellon University Pittsburgh PA 15213 USA

ISBN: (纸本)0262025507

We focus on the problem of efficient learning of dependency trees. It is well-known that given the pairwise mutual information coefficients, a minimum-weight spanning tree algorithm solves this problem exactly and in polynomial time. However, for large data-sets it is the construction of the correlation matrix that dominates the running time. We have developed a new spanning-tree algorithm which is capable of exploiting partial knowledge about edge weights. The partial knowledge we maintain is a probabilistic confidence interval on the coefficients, which we derive by examining just a small sample of the data. The algorithm is able to flag the need to shrink an interval, which translates to inspection of more data for the particular attribute pair. Experimental results show running time that is near-constant in the number of records, without significant loss in accuracy of the generated trees. Interestingly, our spanning-tree algorithm is based solely on Tarjan's red-edge rule, which is generally considered a guaranteed recipe for bad performance.

关键词： Runtime Data sampling spanning tree algorithm Rule DEPENDENCE

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Network Decomposition and Maximum Independent Set Part Ⅱ:Application Research

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Journal of Modern Transportation 2004年第1期000卷

关键词： Network transformation and decomposition Negative envelope graph Pseudo-negative envelope graph spanning tree algorithm Adjusting search Picking-off search Polynomial time bound

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