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检索条件"任意字段=6th International Conference on the Art, Science, and Engineering of Programming, Programming 2022"

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GA-PID controller for position control of inverted pendulum

GA-PID controller for position control of inverted pendulum

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international conference on Adaptive science & Technology (ICAST)

作者： Lukman A. Yusuf Nuraddeen Magaji Department of Electrical Engineering Bayero University Kano Nigeria

Stability is very necessary in control system and it becomes more difficult to achieve for a nonlinear system which inverted pendulum is an example. Most of the controllers available suffer from problems such as difficult in tuning process, sluggishness in response time, quick and global convergence etc. this paper considered Proportional-Integra-Derivative optimized with Genetic Algorithm (GA-PID) Controller on Inverted pendulum for the control of the angle position. Conventional PID controller was used to validate the proposed controller. A MATLAB script for genetic algorithm was written with the aim of obtaining optimum PID parameters that would keep the pendulum angle at equilibrium (i.e. returns the pendulum to a desire point as quick as possible) by minimizing an objective function (Integral time absolute error ITAE). On the other hand, a convention PID controller was designed using MATLAB/Simulink environment; the PID's gains were manually tuned until an optimum response is achieved. the results obtained in both schemes shows that GA-PID showed superiority in all the performance indices used in evaluating the two controller schemes and therefore can serves as a valuable controller for the system.

关键词： Mathematical model Control systems Genetic algorithms Linear programming Tuning Sociology Statistics

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Parameter Estimation Algorithm for Storm Intensity Model with Single Return Period Based on Multicellular Gene Expression programming

Parameter Estimation Algorithm for Storm Intensity Model wit...

引用

the 6th international conference on Computer Research and Development

作者： Yuzhong Peng Jie Li Chang'an Yuan Baoqin Hu College of Computer and Information Engineering Guangxi Teachers Education University Department of Mathematics and computer science Guangxi Liuzhou Teachers college Key Lab of Beibu Gulf Environment Change and Resource Use of ministry of Education Guangxi Teachers Education University

To resolve the difficulty of parameter estimation of Storm rainfall intensity formulation, a new multicellular GEP parameter estimation algorithm, named MCEPPO, with a novel individual coding scheme based on Gene Expression programming algorithm is proposed in this paper. MCEPPO is used for solving the parameter estimation problem of the single return period of rainfall intensity forecast model using historical rainfall statistical data as a learning example. And its effectiveness in real compute instance has been evaluated. the compared experiment result shows that the proposed method exploring for parameter estimation of Storm rainfall intensity formulation is feasible and precise.

关键词： Multicellular Gene Expression programming Multi-parameter optimization Storm rainfall intensity parameter estimation

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Analyses on Performance of Gromacs in Hybrid MPI+OpenMP+CUDA Cluster

Analyses on Performance of Gromacs in Hybrid MPI+OpenMP+CUDA...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Ce Li Wenbo Chen Yang Zhang Qifeng Bai School of Information Science & Engineering Lanzhou University Lanzhou China

ISBN: (纸本)9781479961245

the Tri-Level parallel programming pattern of MPI+OpenMP+CUDA, which enables better speedup for applications on popular multi-core architecture cluster, is increasingly admired by research institutions and companies. the interaction of particles of molecular dynamics simulation needs extensive calculation, which will also increases with the extension of system. therefore higher performance for the computing capability and storage ability of current high performance computer is required. As one of main softwares of molecular dynamics simulation, GROMACS can be used for the simulation of hundreds of or even millions of atoms. Based on this kind of hybrid parallel programming pattern, the latest version of GROMACS has higher operation efficiency and shorter simulation time. In this paper, we take advantage of two different sizes of protein simulation system as the data of GROMACS for the molecular simulation of different parallel granularity on mixed cluster which is based on Intel Xeon5650 and NVIDIA C2050. By the result of experiment, we have obtained the best mechanism of hybird CPU-GPU cluster and analyzed the advantage of MPI+OpenMP+CUDA hybrid parallel programming pattern. In the end, we compared GROMACS4.6 with GROMACS4.5. the results of the test also provide a reference for scientists who work on building large-scale molecular dynamics simulation platform and observe the molecular dynamics simulation.

关键词： Graphics processing units Computational modeling Parallel programming Proteins Parallel processing Biological system modeling Acceleration

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R2Time: a framework to analyse OpenTSDB time-series data in HBase

R2Time: a framework to analyse OpenTSDB time-series data in ...

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IEEE international conference on Cloud Computing Technology and science

作者： Bikash Agrawal Antorweep Chakravorty Chunming Rong Tomasz Wiktor Wlodarczyk Department of Computer and Electrical Engineering University of Stavanger

ISBN: (纸本)9781479940929

In recent years, the amount of time series data generated in different domains have grown consistently. Analyzing large time-series datasets coming from sensor networks, power grids, stock exchanges, social networks and cloud monitoring logs at a massive scale is one of the biggest challenges that data scientists are facing. Big data storage and processing frameworks provides an environment to handle the volume, velocity and frequency attributes associated with time-series data. We propose an efficient and distributed computing framework - R2Time for processing such data in the Hadoop environment. It integrates R with a distributed time-series database (OpenTSDB) using a MapReduce programming framework (RHIPE). R2Time allows analysts to work on huge datasets from within a popular, well supported, and powerful analysis environment.

关键词： R OpenTSDB Hadoop HBase Time-series

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Task Migration for Energy Saving in Real-Time Multiprocessor Systems

Task Migration for Energy Saving in Real-Time Multiprocessor...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Gang Zeng Yutaka Matsubara Hiroyuki Tomiyama Hiroaki Takada Graduate School of Engineering Nagoya University Graduate School of Information Science Nagoya University Furo-cho Chikusa-ku Nagoya Japan College of Sciences and Engineering Ritsumeikan University Kusatsu Shiga Japan

A task migration method is proposed for energy savings in multiprocessor real-time systems. the method is based on the portioned scheduling technique which classifies each task into a fixed task or a migratable task. the energy-aware migration with specified parameters is formulated as a linear programming problem, and optimal solution is given. Furthermore, the method is extended to more general case with a complete migration algorithm. Simulation results showed significant energy savings over existing methods.

关键词： Silicon Educational institutions conferences Electronic mail Resource management Equations Mathematical model

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A Modified Particle Swarm Optimization Algorithm for Reliability Redundancy Optimization Problem

A Modified Particle Swarm Optimization Algorithm for Reliabi...

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the 6th international conference on Computer Research and Development

作者： Yubao Liu Guihe Qin College of Computer Science and Technology Jilin University College of Computer Science and Technology Changchun University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University

In this paper, a modified particle swarm optimization(MPSO) algorithm is proposed to solve the reliability redundancy optimization problem. this algorithm modifies the strategy of generating new position of particles. For each generation solution, the flight velocity of particles is removed. Whereas the new position of each particle is generated by using difference strategy. Moreover, an adaptive parameter is used to ensure diversity of feasible solutions. Experimental results on four benchmark problems demonstrate that the proposed MPSO has better robustness, effectiveness and efficiency than other algorithms reported in literatures for solving the reliability redundancy optimization problem.

关键词： nonlinear programming PSO reliability optimization redundancy allocation adaptive mechanism

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JolokiaC++: An Annotation Based Compiler Framework for GPGPUs

JolokiaC++: An Annotation Based Compiler Framework for GPGPU...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Vibha Patel Sanjeev Aggarwal Amey Karkare Department of Computer Science and Engineering India Institute of Technology Kanpur

We present JolokiaC++, an annotation based compiler framework which generates high quality CUDA (Compute Unified Device Architecture) code for GPUs. Our contributions include: (1) developing explicit and implicit annotations with illustrations of their use in C++, (2) showing the utility of these annotations by providing comparison code snippets, which demonstrates the ease of programming and performance gains, (3) evaluating their effectiveness on kernels like Blacks holes, Matrix-Vector multiplication, Matrix-Matrix multiplication, Jacobi 1D & 2D, Heat 2D, Vector Addition and Convolution.

关键词： Graphics processing units Arrays Kernel Vectors Semantics Optimization

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Power-Efficient and Predictable Data Centers with Sliding Scheduled Tenant Requests

Power-Efficient and Predictable Data Centers with Sliding Sc...

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IEEE international conference on Cloud Computing Technology and science (CloudCom)

作者： Aissan Dalvandi Mohan Gurusamy Kee Chaing Chua Department of Electrical and Computer Engineering National University of Singapore Singapore

Power efficiency and predictable performance have become major concerns for cloud service providers as they significantly affect cloud adoption and tenancy cost. Providing guaranteed resources for predictable performance in data centers drives the need for a request model which abstracts the traffic characteristics as well as the resource requirements of tenant applications. In this paper, we propose a novel Sliding Scheduled Tenant (SST) request model which enables tenants to request their resources for an estimated required time duration which can slide within a certain time-window. We investigate the power-efficient resource-guaranteed Virtual Machine (VM) -placement and routing problem for dynamically arriving SST requests. the problem requires provisioning of the specified resources in a data center for the required duration of requests by choosing an appropriate start- and end-time within their specified time-window, so as to maximize the number of accepted requests while consuming as low power as possible. We develop a mixed integer linear programming (MILP) optimization problem formulation based on the multi-component utilization-based power model. Since this problem which is a combination of VMplacement, scheduling and routing problems, is computationally rohibitive, we develop a fast and scalable heuristic algorithm. We demonstrate the effectiveness of the proposed algorithm and SST request model in terms of power saving and acceptance ratio through comprehensive simulation results.

关键词： Servers Bandwidth Routing Power demand Biological system modeling Data models Optimization

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Ruminative Reinforcement Learning: Improve Intelligent Inventory Control by Ruminating on the Past

Ruminative Reinforcement Learning: Improve Intelligent Inven...

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the 6th international conference on Computer Research and Development

作者： Tatpong Katanyukul Khon Kaen University/Computer Engineering

Reinforcement Learning(RL) can solve practical sequential decision problems, even when structures of the problems are less understood. However, some sequential decision problems intrinsically have structural parts that are easily to formulate and distinguish from less understood parts. Exploiting this knowledge may help improve performance of RL. this study proposed and investigated an approach to exploit the knowledge of structural parts of inventory management problems in the context of RL. the proposed method is motivated by human behavior of ruminating on what has happened and what would happen if alternative choices would have been taken. Our investigation provides an insight into RL mechanism and our experimental results show viability of the approach.

关键词： Temporal difference learning ruminative behavior markov decision problem artificial intelligence reinforcement learning inventory control approximate dynamic programming

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A Hybrid TS-DE Algorithm for Reliability Redundancy Optimization Problem

A Hybrid TS-DE Algorithm for Reliability Redundancy Optimiza...

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the 6th international conference on Computer Research and Development

作者： Yubao Liu Guihe Qin College of Computer Science and Technology Jilin UniversityChangchunChina College of Computer Science and TechnologyChangchun University College of Computer Science and Technology Jilin UniversityChangchunChina Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin University

In this paper, a hybrid TS-DE algorithm based on Tabu search and differential evolution algorithm is proposed to solve the reliability redundancy optimization problem. A differential evolution algorithm is embedded in Tabu search algorithm. TS is applied for searching solutions space, and DE is used for generating neighborhood solutions. the advantages of both algorithms are considered simultaneously. And an adaptive hybrid TS-DE approach is developed to solve three benchmark reliability redundancy allocation problems. By comparing with other algorithms reported in previous literatures, experimental results show that the proposed method is effective and efficient for solving the reliability redundancy optimization problem.

关键词： nonlinear programming Tabu search differential evolution reliability optimization redundancy allocation

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