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第28届中国过程控制会议（CPCC 2017）暨纪念中国过程控制会议30周年

作者： Yan Yu Jiandong Wang Peking University Shandong University of Science and Technology

This paper proposes a new algorithm,named as the improved bottom-up algorithm,to approximate time series in a linear *** algorithm starts by the finest possible approximation of time series,so that n-1 segments are used to approximate the n-length time *** fitting errors of merging each pair of adjacent segments are *** algorithm iteratively merges the minimal fitting error pair until the number of segments meets a given value *** main novelty of the proposed algorithm is to devise a decision function to determine an optimal choice of *** decision function is composed of two parts,namely,the weighted fitness and trend similarity between the time series and its corresponding *** effectiveness of the proposed algorithm is illustrated via numerical and industrial examples.

关键词： Piecewise linear representation time series bottom-up algorithm

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Reductions in binary search trees

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THEORETICAL COMPUTER SCIENCE 2006年第3期355卷 327-353页

作者： Sánchez-Couso, JR Fernández-Camacho, MI Univ Complutense Dept Sistemas Informat & Programac Fac CC Matemat E-28040 Madrid Spain Univ Politecn Madrid Dept Lenguajes Proyectos & Sistemas Informat Esc Univ Informat Madrid 28031 Spain

We analyze two bottom-up reduction algorithms over binary trees that represent replaceable data within a certain system, assuming the binary search tree (BST) probabilistic model. These reductions are based on idempotent and nilpotent operators, respectively. In both cases, the average size of the reduced tree, as well as the cost to obtain it, is asymptotically linear with respect to the size of the original tree. Additionally, the limiting distributions of the size of the trees obtained by means of these reductions satisfy a central limit law of Gaussian type. (c) 2006 Elsevier B.V. All rights reserved.

关键词： bottom-up algorithm generating function analytic convergence singularity analysis complex asymptotics differential equation

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ProDomAs, protein domain assignment algorithm using center-based clustering and independent dominating set

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PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS 2014年第9期82卷 1937-1946页

作者： Ansari, Elnaz Saberi Eslahchi, Changiz Pezeshk, Hamid Sadeghi, Mehdi Univ Tehran Inst Biochem & Biophys Dept Bioinformat Tehran Iran Shahid Beheshti Univ Dept Comp Sci GC Tehran Iran Inst Res Fundamental Sci IPM Sch Biol Sci Tehran Iran Univ Tehran Sch Math Stat & Comp Sci Coll Sci Tehran Iran Natl Inst Genet Engn & Biotechnol Tehran Iran

Decomposition of structural domains is and essential task in classifying protein structures, predicting protein function, and many other proteomics problems. As the number of known protein structures in PDB grows exponentially, the need for accurate automatic domain decomposition methods becomes more essential. In this article, we introduce a bottom-up algorithm for assigning protein domains using a graph theoretical approach. This algorithm is based on a center-based clustering approach. For constructing initial clusters, members of an independent dominating set for the graph representation of a protein are considered as the centers. A distance matrix is then defined for these clusters. To obtain final domains, these clusters are merged using the compactness principle of domains and a method similar to the neighbor-joining algorithm considering some thresholds. the thresholds are computed using a training set consisting of 50 protein chains. The algorithm is implemented using C++ language and is named ProDomAs. To assess the performance of ProDomAs, its results are compared with seven automatic methods, against five publicly available benchmarks. The results show that ProDomAs outperforms other methods applied on the mentioned benchmarks. The performance of ProDomAs is also evaluated against 6342 chains obtained from ASTRAL SCOP 1.71 ProDomAs is freely available at http://***/software/prodomas.

关键词： domain boundary detection compactness principle of structural domains discontinuous domains bottom-up algorithm graph theoretical approach

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Parallel Iterative Reengineering Model of Legacy Systems

Parallel Iterative Reengineering Model of Legacy Systems

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IEEE International Conference on Systems, Man and Cybernetics

作者： Su, Xing Yang, Xiaohu Li, Juefeng Wu, Di Zhejiang Univ Coll Comp Sci Hangzhou 310027 Peoples R China State St Technol Zhejiang Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781424427932

Great improvements have been made in methodologies on reengineering of legacy systems to enhance the migration process. Unfortunately, taking into account the large scale of these systems, the duration of reengineering process can still be quite long which will make an impact on the business the systems supported. In this paper we propose a parallel iterative reengineering model to reduce the reengineering process duration. The model uses the method of Formal Concept Analysis to process the complex access relationship between legacy components and shared data. An algorithm named "bottom-up", which consists of two parts, is introduced to build the parallel schedule for the reengineering process. This model shortens the reengineering duration and has been proven to be successful in improving the transition system's performance in a comparative experiment.

关键词： Legacy System Reengineering Parallel Iterative Reengineering Model Formal Concept Analysis bottom-up algorithm Performance

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A New, Highly Efficient, and Easy To Implement Top-Down Join Enumeration algorithm

A New, Highly Efficient, and Easy To Implement Top-Down Join...

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IEEE 27th International Conference on Data Engineering (ICDE 2011)

作者： Fender, Pit Moerkotte, Guido Univ Mannheim Database Res Grp D-68131 Mannheim Germany

ISBN: (纸本)9781424489589

Finding an optimal execution order of join operations is a crucial task in every cost-based query optimizer. Since there are many possible join trees for a given query, the overhead of the join (tree) enumeration algorithm per valid join tree should be minimal. In the case of a clique-shaped query graph, the best known top-down algorithm has a complexity of Theta(n(2)) per join tree, where n is the number of relations. In this paper, we present an algorithm that has an according O(1) complexity in this case. We show experimentally that this more theoretical result has indeed a high impact on the performance in other non-clique settings. This is especially true for cyclic query graphs. Further, we evaluate the performance of our new algorithm and compare it with the best top-down and bottom-up algorithms described in the literature.

关键词： algorithm design and analysis Complexity theory Data structures Heuristic algorithms Niobium Optimization Partitioning algorithms bottom-up algorithm clique shaped query graph computational complexity computational complexity cost based query optimizer cyclic query graph graph theory join tree optimal execution order query processing top-down join enumeration algorithm tree data structures trees (mathematics)

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IMPROVEMENT ON DYNAMIC TILED TERRAIN RENDERING algorithm IN LIBMINI

IMPROVEMENT ON DYNAMIC TILED TERRAIN RENDERING ALGORITHM IN ...

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22nd European Modeling and Simulation Symposium (EMSS)

作者： Liao Mingxue Xu Fanjang He Xiaoxin Chinese Acad Sci Inst Software Beijing Peoples R China

ISBN: (纸本)9782952474788

As an open source library for large-scale terrain rendering in a continuous LOD high field, libMini takes a top-down method for static terrain rendering and achieves good perfounance. However, it uses the same top-down method to render elevation and texture for dynamic terrain. The method consumes a few seconds to update dynamic terrain and thus does not meet real-time requirements for rendering and leads to possible holes and gaps between adjacent terrain tiles. A millisecond-level real-time bottom-up libMini-based algorithm is proposed to render dynamic terrain while a method is presented to blend holes and gaps produced during the process of rendering dynamic tiled terrain.

关键词： bottom-up algorithm dynamic terrain libMini tiled terrain

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Steady-State Interval Detection and Nonlinear Modeling for Automatic Generation Control Systems

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IEEE ACCESS 2019年 7卷 139592-139600页

作者： Cao, Pengfei Wang, Jiandong Zhang, Chao Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Shandong Peoples R China

Automatic generation control systems are designed to adjust electric power outputs of multiple generators simultaneously in accordance with the current load. However, the control instruction and the main steam pressure have significant impacts on the resulting active power generation of a conventional thermal generator, and the impacts may be associated with nonlinear characteristics. As a result, the control instruction requires an accurate modeling of the relationship between these three variables for a satisfactory control performance. This paper proposes a method to build a piecewise linear model for the nonlinear relationship from steady-state data hidden in historical data samples. The proposed method is composed by two main steps of steady-state interval detection and steady-state data segmentation. Historical data samples are grouped using the k-means clustering algorithm, and the time domains of each cluster are merged in a specific way to obtain the steady-state intervals. The steady-state data are taken as the samples means of data in the steady-state intervals. A bottom-up algorithm is utilized to partition the steady-state data into numbers of sets iteratively, and the parameters of the piecewise linear model for each data set are estimated by the least squares algorithm. The effectiveness of the proposed method is illustrated via industrial applications to two thermal power generation units.

关键词： Automatic generation control system piecewise linear model steady-state interval detection k-means clustering algorithm bottom-up algorithm

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Optimal Hierarchical Partition for k-Anonymity

Optimal Hierarchical Partition for k-Anonymity

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The 5th International Conference on Computer Science & Education(第五届国际计算机新技术与教育学术研讨会 ICCSE'10)

作者： Qingming Tang Yingjie Wu Xiaodong Wang Dept. of Computer Science FuZhou University FuZhou FuJianChina350108

k-Anonymity is a famous and widely used privacy principle for protecting private information. It requires that each tuple of a public released data table must be indistinguishable from at least other k -1 tuples. Given a table, finding an optimal k-anonymous version is NP-hard in most previous recoding "model". Thus, designing an efficient algorithm to find high-quality k-anonymous version is still challenge, though k-anonymity is well-researched. In recent years, hierarchical partition is proposed and widely accepted. Viewing the given table as a multidimensional space, each hierarchical partition of the space is a multidimensional recoding under some special constraints. Previous works need huge computation to find optimal hierarchical partition, and efficient algorithms just find a reasonable hierarchical partition. In this paper, we show that optimal hierarchical partition for k-anonymity can be obtained within polynomial time when a fixed quasi-identifier is given. We then design a bottom-up algorithm using dynamic approach. Through theoretical analysis and experiments, we show that our algorithm finds better results than related works, and our algorithm runs significantly fast comparing with other optimal algorithms for hierarchical partition.

关键词： Privacy:k-Anonymity:Hierarchical Partition bottom-up algorithm

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