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4th Workshop on the Frontiers of Evolutionary algorithms

作者： Liu, JQ Shimohara, K ATR Human Informat Sci Labs Seika Kyoto 6190288 Japan Cent S Univ Coll Informat Sci & Engn Changsha 410083 Hunan Peoples R China

In this paper, we propose a molecular computing method based on the signaling pathways of cells. The kernel of the corresponding computing mechanism is the interaction of signaling pathways for phosphorylation-dephosphorylation regulated by kinases and phosphatases. The materials for its potential biological implementation are the signaling pathways of Rho family GTPases of in situ cells that have been simulated by us in a coarse-grained way. An instance of the 3-SAT benchmark problem is used to test the performance of signaling-pathway-based algorithms applied in NP problem solving. The theoretical result that we achieved is that both control-space complexity and time complexity is linear. In addition to this, the merits derived from the method mentioned above include scalability, robustness, programmability, controllability and autonomy. The simulation has shown that molecular computing schemes using signaling pathways are programmable for different computing units and controllable for temporal signals of pathways with ample efficiency for computing processes. (C) 2003 Elsevier Inc. All rights reserved.

关键词： molecular computing 3-SAT problem parallel algorithm

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A Highly parallelizable Newton-type Method for Nonlinear Model Predictive Control

A Highly Parallelizable Newton-type Method for Nonlinear Mod...

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6th International-Federation-of-Automatic-Control (IFAC) Conference on Nonlinear-Model-Predictive-Control (NMPC)

作者： Deng, Haoyang Ohtsuka, Toshiyuki Kyoto Univ Grad Sch Informat Dept Syst Sci Kyoto Japan

We propose a highly parallelizable Newton-type method for nonlinear model predictive control by exploiting the particular structure of the associated Karush-Kuhn-Tucker conditions. These equations are approximately decoupled into single step subproblems along the prediction horizon for parallelization. The coupling variable of each subproblem is approximated toward its optimal value by a simple but effective method in every iteration. The proposed algorithm is applied to control a quadrotor. The numerical simulation results show that the proposed algorithm is highly parallelizable and converges with only a few iterations even to a high accuracy. The proposed method is also shown to be faster compared with several state-of-the-art algorithms. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Nonlinear model predictive control parallel algorithm real-time algorithm

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Distributed energy-efficient solutions for area coverage problems in wireless sensor networks

Distributed energy-efficient solutions for area coverage pro...

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作者： Vu, Chinh Trung Georgia State University

学位级别：Ph.D.

Wireless sensor networks (WSNs) have recently attracted a great deal of attention due to their numerous attractive applications in many different fields. Sensors and WSNs possess a number of special characteristics that make them very promising in a wide range of applications, but they also put on them lots of constraints that make issues in sensor network particularly challenging. These issues may include topology control, routing, coverage, security, data management and many others. Among them, coverage problem is one of the most fundamental ones for which a WSN has to watch over the environment such as a forest (area coverage) or set of subjects such as collection of precious renaissance paintings (target of point coverage) in order for the network to be able to collect environment parameters, and maybe further monitor the environment. In this dissertation, we highly focus on the area coverage problem. With no assumption of sensors’ locations (i.e., the sensor network is randomly deployed), we only consider distributed and parallel scheduling methods with the ultimate objective of maximizing network lifetime. Additionally, the proposed solutions (including algorithms, a scheme, and a framework) have to be energy-efficient. Generally, we investigate numerous generalizations and variants of the basic coverage problem. Those problems of interest include k-coverage, composite event detection, partial coverage, and coverage for adjustable sensing range network. Various proposed algorithms. In addition, a scheme and a framework are also suggested to solve those problems. The scheme, which is designed for emergency alarming applications, specifies the guidelines for data and communication patterns that significantly reduce the energy consumption and guarantee very low notification delay. For partial coverage problem, we propose a universal framework (consisting of four strategies) which can take almost any complete-coverage algorithm as an input to generate an algorithm

关键词： k-Coverage Energy-efficiency Wireless Sensor Network Adjustable Sensing Range WSN Coverage Problem Localized and Distributed algorithm Connectivity parallel algorithm Fault-Tolerance Partial Coverage Composite Event Detection Robustness

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Information Technologies in Models for Assessing the Reliability of Electric Power Systems in Managing their Development 9

Information Technologies in Models for Assessing the Reliabi...

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9th International Scientific Symposium on Electrical Power Engineering (ELEKTROENERGETIKA)

作者： Chukreyev, Iurii Chukreyev, Mikhail RAS Fed State Budgetary Sci Inst Inst Socioecon & Energy Problems North Komi Sci CtrUral Branch Syktyvkar Russia

ISBN: (纸本)9788055331959

The determination of reliability criteria is an essential part of the work to establish the future power reserves in territorial areas of the United Power System of Russia. This task has been thoroughly studied. In this article, the main features of long term planning are discussed, and methods and models for the determination of reliability criteria are proposed.

关键词： UPS of Russia reliability criteria power system adequacy parameter parallel algorithm

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Alarm Fuzzy Association Rules parallel Mining in Multi-domain Distributed Communication Network

Alarm Fuzzy Association Rules Parallel Mining in Multi-domai...

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2012 IEEE 14th International Conference on Communication Technology

作者： Xiaojie Leng Xingming Li School of Communication and Information Engineering University of Electronic Science and Technology of China

ISBN: (纸本)9781467321006

Network is divided into different management domains in large-scale communication system,each management domain has its own Local Management *** distributed characteristics of network determine the Global Management Site with several Local Management Sites to meet a distributed *** paper proposes a new algorithm called PFAARM (parallel fuzzy alarm association rules mining algorithm),which can be used for alarm fuzzy association rules parallel mining in multi-domain distributed communication *** correlation analysis ban be executed in parallel both in Global Management Site and Local Management *** association rules can be achieved within inner-and inter-domain *** the basis of alarm correlation analysis in single management domain,the introduction of inter-domain alarm fuzzy association rules,which are based on inter-domain communication relationship,gives another essential clue for fault ***,it’s of great significance for quick and efficient fault *** simulation results illustrated its feasibility and efficiency.

关键词： Fault Diagnosis Fuzzy Logic Fuzzy Association Rule parallel algorithm Multi-domain Distributed Network

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Efficient nonlinear optimization with rigorous models for large scale industrial chemical processes

Efficient nonlinear optimization with rigorous models for la...

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作者： Zhu, Yu Texas A&M University

学位级别：Ph.D.

Large scale nonlinear programming (NLP) has proven to be an effective framework for obtaining profit gains through optimal process design and operations in chemical engineering. While the classical SQP and Interior Point methods have been successfully applied to solve many optimization problems, the focus of both academia and industry on larger and more complicated problems requires further development of numerical algorithms which can provide improved computational efficiency. The primary purpose of this dissertation is to develop effective problem formulations and an advanced numerical algorithms for efficient solution of these challenging problems. As problem sizes increase, there is a need for tailored algorithms that can exploit problem specific structure. Furthermore, computer chip manufacturers are no longer focusing on increased clock-speeds, but rather on hyperthreading and multi-core architectures. Therefore, to see continued performance improvement, we must focus on algorithms that can exploit emerging parallel computing architectures. In this dissertation, we develop an advanced parallel solution strategy for nonlinear programming problems with block-angular structure. The effectiveness of this and modern off-the-shelf tools are demonstrated on a wide range of problem classes. Here, we treat optimal design, optimal operation, dynamic optimization, and parameter estimation. Two case studies (air separation units and heat-integrated columns) are investigated to deal with design under uncertainty with rigorous models. For optimal operation, this dissertation takes cryogenic air separation units as a primary case study and focuses on formulations for handling uncertain product demands, contractual constraints on customer satisfaction levels, and variable power pricing. Multiperiod formulations provide operating plans that consider inventory to meet customer demands and improve profits. In the area of dynamic optimization, optimal reference trajectories are d

关键词： nonlinear optimization air separation design under uncertainty parallel algorithm water network rigorous model Thesis

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Maximum Flow on Highly Dynamic Graphs

Maximum Flow on Highly Dynamic Graphs

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Luo, Juntong Sallinen, Scott Ripeanu, Matei The University of British Columbia Vancouver Canada

ISBN: (纸本)9798350324457

Recent advances in dynamic graph processing have enabled the analysis of highly dynamic graphs with change at rates as high as millions of edge changes per second. Solutions in this domain, however, have been demonstrated only for relatively simple algorithms like PageRank, breadth-first search, and connected components. Expanding beyond this, we explore the maximum flow problem, a fundamental, yet more complex problem, in graph analytics. We propose a novel, distributed algorithm for max-flow on dynamic graphs, and implement it on top of an asynchronous vertex-centric abstraction. We show that our algorithm can process both additions and deletions of vertices and edges efficiently at scale on fast-evolving graphs, and provide a comprehensive analysis by evaluating, in addition to throughput, two criteria that are important when applied to real-world problems: result latency and solution stability. © 2023 IEEE.

关键词： asynchronous algorithm dynamic graph processing graph streaming maximum flow parallel algorithm

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parallelism of association rules mining and its application in insurance operations

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4th International Conference on Computational Science (ICCS 2004)

作者： Tian, JL Zhu, L Zhang, SQ Huang, G Tsing Hua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)3540221298

Association rules mining is a basic method in data mining. This paper first introduces the basic concepts of association rules mining and Apriori algorithm. It also provides a parallel association rules model scheme for improving the mining efficiency when treating large numbers of data sets as well as the analyse of the scheme effect. In conclusion we discuss how to apply association rules mining to insurance data sets, find out the knowledge hidden behind the data sets, and provide powerful decision-making support for people.

关键词： data mining association rules mining parallel algorithm insurance

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RESEARCH OF parallel PROCESS MANAGEMENT MODEL BASED ON PARITY DICHOTOMY METHOD TO SLOVE TRIGANGULAR SYSTEM

RESEARCH OF PARALLEL PROCESS MANAGEMENT MODEL BASED ON PARIT...

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2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

作者： CHUN-FENG LIU AI-MIN YANG YA-MIAN PENG School of Management Hebei University of Technology Tianjin 300130 China College of Science Hebe College of Science Hebei Ploytechnic University Tangshan 063009 China

With the object of realizing the direct solution to the triangular system, and in accordance with the associated chain for first order parallel linear recurrence method, this paper derives the associated chain for 8 order triangular system, then constructs the relative associated chain for common system of equations based on the parity dichotomy method and designs the correlative parallel algorithm. In regards to the designed parallel algorithm, it is analyzed in two aspects, which are the theoretical derivation of the parallel speed-up ratio and efficiency for the algorithm and then the verification for it through the number experiment By the analysis, we can see the algorithm has the characters of less communication time and better calculating efficiency, which testifies that the parallel algorithm is practically effective in solving the triangular system.

关键词： Associated chain Parity dichotomy method parallel algorithm Speed-up ratio Efficiency

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On a parallel spark workflow for frequent itemset mining based on array prefix-tree

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2022年第14期34卷 e6313-e6313页

作者： Niu, Xinzheng Wu, Peng Wu, Chase Q. Hou, Aiqin Qian, Mideng Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu 611731 Sichuan Peoples R China New Jersey Inst Technol Dept Comp Sci Newark NJ 07102 USA Northwest Univ Sch Informat Sci & Technol Xian Peoples R China

Extracting frequent itemsets from datasets is an important problem in data mining, for which several mining methods including FP-Growth have been proposed. FP-Growth is a classical frequent itemset mining method, which generates pattern databases without candidates. Many improvements have been made in the literature due to the high time complexity and memory usage of FP-Growth. However, most of them still suffer from performance issues on large datasets. In this paper, we design an auxiliary structure, Array Prefix-Tree (AP-Tree), and propose a new algorithm, Array Prefix-Tree Growth (APT-Growth), which is further parallelized as a Spark workflow, referred to as PAPT-Growth. Based on a density threshold, we incorporate an adaptive algorithm selection process into PAPT-Growth to ensure its running time performance. We conduct extensive experiments on different thresholds and multiple datasets, and experimental results show the performance superiority of PAPT-Growth in comparison with several state-of-the-art methods such as PFP, YAFIM, and DFPS. The analysis on density reveals a changing point, which justifies the necessity and validity of adaptive algorithm selection.

关键词： adaptive algorithm array prefix‐ tree frequent itemsets mining parallel algorithm Spark workflow

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