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2015 International Conference on Advanced Educational Technology and Information Engineering(AETIE 2015)

作者： G.C.Du Yellow River Conservancy Technical Institute

In the paper, Radial Basis Function(RBF) neural network optimized by particle swarm optimization algorithm is proposed to fault diagnosis for embedded system. The parameters of Radial Basis Function(RBF) neural network are selected by particle swarm optimization algorithm to solve the problem of the parameters selection of Radial Basis Function(RBF) neural network. In order to testify the superiority of Radial Basis Function(RBF) neural network optimized by particle swarm optimization algorithm in fault diagnosis for embedded system, traditional Radial Basis Function(RBF) neural network and Back Propagation(BP) neural network are applied to compare with the proposed Radial Basis Function(RBF) neural network optimized by particle swarm optimization algorithm. The comparison results show that the diagnosis accuracy of Radial Basis Function(RBF) neural network optimized by particle swarm optimization algorithm is the best methods among traditional Radial Basis Function(RBF) neural network, Back Propagation(BP) neural network and Radial Basis Function(RBF) neural network optimized by particle swarm optimization algorithm.

关键词： embedded system RBF neural network fault diagnosis particle swarm optimization algorithm

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An Energy-Efficient Operation Approach Based on the Utilization of Regenerative Braking Energy among Trains

An Energy-Efficient Operation Approach Based on the Utilizat...

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International IEEE Conference on Intelligent Transportation Systems

作者： Erchao Chen Bing Bu Wenzhe Sun State Key Lab. of Rail Traffic Control & Safety Beijing Jiaotong Univ. Beijing China

ISBN: (纸本)9781467365970

With the rapid development of urban rail transit, the problem of energy consumption is drawing more and more attentions. Based on the utilization of regenerative braking energy among trains, this paper studies the energy-efficient operation method. We propose an utilization strategy of regenerative energy among trains. Based on the proposed strategy, we set up the energy-saving model which optimizes the timetable and speed profile of trains simultaneously. Based on the particle swarm optimization algorithm, taking Beijing Yizhuang subway line and Changping subway line as examples of short section and long section for simulation, we verify the effectiveness of the proposed method. It is showed that the energy consumption of Yizhuang line and Changping line can be reduced by 3.2% and 5.5%, respectively, through improving the utilization of regenerative energy.

关键词： energy conservation particle swarm optimisation railway electrification regenerative braking energy consumption energy-efficient operation approach particle swarm optimization algorithm regenerative braking energy urban rail transit Acceleration Brakes Energy consumption Linear programming Power supplies Public transportation Rails

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Transmission planning with renewable generation and energy storage

Transmission planning with renewable generation and energy s...

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

作者： Jing Zheng Fushuan Wen Minglei Zhou Liexiang Hu Qian Xu Zhou Lan State Grid Zhejiang Electric Power Company Hangzhou China Department of Electrical and Electronic Engineering Institut Teknologi Brunei Brunei

ISBN: (纸本)9781510830059

An energy storage system (ESS) can provide regulation and reserve capacities for the power system, and hence alleviate the negative impacts of renewable energy such as wind power. Nonetheless, challenges remain as to how the operation of wind farms and ESSs can be coordinated efficiently, and how transmission system expansion planning will be impacted. This paper addresses these challenges by: (1) examining the correlation between the cost of ESS and its cycle life, exampled with a Natrium Sulfur (NaS) ESS; (2) investigating the integrated operation of a wind farm and an ESS taking into account both the cost of ESSs and their smoothing effect of wind power fluctuations; (3) developing a transmission system expansion planning model with particular reference to both the investment cost of the transmission system concerned and the operating costs of wind farms and ESSs; and (4) solving the developed planning formulation using an improved particle swarm optimization algorithm. The proposed planning method is illustrated through its applications to two sample systems.

关键词： particle swarm optimization algorithm wind farm energy storage system integrated operation transmission system expansion planning

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PSO algorithm for Block Sequencing Problem in Open Pit Mining

PSO Algorithm for Block Sequencing Problem in Open Pit Minin...

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2015 5th International Conference on Computer Sciences and Automation Engineering(ICCSAE 2015)

作者： Wenbo Liu Hongyi Zhang Liaoning Key Laboratory of Manufacturing System and Logistics The Logistics InstituteNortheastern University

Iron ore is the main raw material of the production in iron and steel enterprises in China. It is a non-renewable resource and with limited reserves. In this paper, in combination with the practical situation of the mine, an integer linear programming model of a strip mining block scheduling problem is established with the scientific, reasonable, and economical principle. The maximization of mining profit is set as the goal under the precedence constraints and production capacity constraints. This paper designs an improved particle swarm optimization algorithm to solve the problem and compares with results with CPLEX optimizing software. According to the results of different scale experiment, the improved particle swarm optimization algorithm has better performance.

关键词： Mining particle swarm optimization algorithm CPLEX

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A simulation-based optimization method for cost-optimal analysis of nearly Zero Energy Buildings

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ENERGY AND BUILDINGS 2014年 84卷 442-457页

作者： Ferrara, Maria Fabrizio, Enrico Virgone, Joseph Filippi, Marco Politecn Torino DENERG I-10129 Turin Italy Univ Turin DISAFA I-10095 Grugliasco TO Italy Univ Lyon 1 INSA Lyon CETHIL UMR5008 F-69621 Villeurbanne France

This study was developed in the context of new challenges imposed by the recast of the Energy Performance of Buildings Directive 2010/31/EU (EPBD) and its supplementing regulation. The aim is to find the cost-optimal level for the French single-family building typology, while providing an effective method to deal with a huge number of simulations corresponding to a large number of building configurations. The method combines the use of TRNSYS, dynamic energy simulation software, with GenOpt, Generic optimization program. The building that was taken as a reference is a real low-consumption house located in Amberieu-en-Bugey, Rhone-Alpes, France. The model was created and calibrated in TRNSYS and the energy efficiency measures, concerning different technologies for envelope systems and technical systems, were set up as parameters in GenOpt. After a research on the French market, a cost function was created for each parameter and the global cost function (EN15459 Standard) was taken as objective function for the optimization. The particle swarm optimization algorithm was used to minimize the objective function and find the cost-optimal building configuration within the current regulatory framework. (C) 2014 Elsevier B.V. All rights reserved.

关键词： EPBD recast Cost optimal analysis nZEB Dynamic building simulation particle swarm optimization algorithm France Building elements cost function Single family house Design parameters

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Mass optimization of functionally graded plate for mechanical loading in the presence of deflection and stress constraints

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COMPOSITE STRUCTURES 2014年第1期110卷 118-132页

作者： Ashjari, M. Khoshravan, M. R. Univ Tabriz Fac Mech Engn Tabriz 51666 Iran

In this work, a method for the single-objective optimization of material distribution of simply supported functionally graded isotropic plates is presented. The material composition is assumed to vary only in the thickness direction. Piecewise cubic interpolation of volume fractions are used to calculate volume fractions of constituent material phases at a point;these fractions are defined at a limited number of evenly spaced control points. The effective material properties of the plate are obtained by applying linear rule of mixtures. Behavior of functionally graded plate is predicted by the assumptions of the third-order shear deformation theory of Reddy. Exact solutions for deflections and stresses of simply supported plates are presented by using Navier type solution technique. Those volume fractions at control points that are selected as decision variables are optimized by two evolutionary algorithms: (1) Real-coded genetic algorithm and (2) particle swarm optimization algorithm. Three models are optimized as primary goal to verify the capability and efficiency of the proposed model with flexibility and stress constraints under various transverse loads. Secondary goal of this article is survey accuracy and convergence of two algorithms aforementioned. The proposed framework for designing functionally graded plates under pure mechanical conditions has been furnished by the founded results. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Heterogeneous material Functionally graded plates optimization particle swarm optimization algorithm Genetic algorithm Mechanical loading

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Fractional-order particle swarm optimization

Fractional-order particle swarm optimization

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第26届中国控制与决策会议

作者： Zhe Gao Junxiu Wei Chao Liang Ming Yan College of Light Industry Liaoning University

By introducing the fractional-order difference into the updating formulas of the velocity and position,fractional-order particle swarm optimization algorithm is proposed. The effects on the convergence rate and accuracy are analyzed, by introducing fractional-orders in the updating formulas for the velocity and position. Moreover, the linear increasing methods to adjust the fractional-orders are proposed. Compared with the standard particle swarm optimization algorithm, the higher convergence rate is achieving to improve the accuracy of the optimal result. Finally, five standard functions are tested, and the results of the numerical experiments illustrate the effectiveness of the fractional-order particle swarm optimization

关键词： particle swarm optimization algorithm Fractional-order difference Linear increasing method

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The effects of magnetic fringe fields on beam dynamics in a beam transport line of a terahertz FEL source

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2014年 764卷 284-290页

作者： Zeng, Han Xiong, Yongqian Pei, Yuanji Huazhong Univ Sci & Technol State Key Lab Adv Elect Engn & Technol Wuhan 430074 Hubei Peoples R China Univ Sci & Technol China Natl Synchrotron Radiat Lab Hefei 230029 Anhui Peoples R China

The transport line used in a terahertz FEL device has to transport electron beam through the entire system efficiently and meet the requirements of the beam parameters at the undulator entrance. Due to space limitations, the size of the magnets (five quadrupoles and two bending magnets) employed in the transport line was limited, and some devices were densely packed. In this paper, analyses of the effect of fringe fields and magnetic interference of magnets are presented. 3D models of these magnets are built and their linear optical properties are compared with those obtained by hard edge models. The results indicated that the effects of these factors are significant and they would cause a mismatch of the beam at the exit of the transport line under the preliminary lattice design. To solve this problem, the beam was re-matched using the particle swarm optimization algorithm. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Beam transport line Beam optics Magnetic fringe field Beam re-matching particle swarm optimization algorithm

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Optimal control of an earth pressure balance shield with tunnel face stability

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AUTOMATION IN CONSTRUCTION 2014年第Oct.期46卷 22-29页

作者： Shao, Cheng Lan, Dongsheng Dalian Univ Technol Inst Adv Control Technol Dalian 116024 Peoples R China

To ensure security during the excavation process of an earth pressure balance shield, this paper presents an optimal control method that accounts for the tunnel face's stability. The tunnel face is controlled by an optimal screw conveyor speed derived from the particle swarm optimization algorithm for a designed stable normal vector angle range on the distribution surface of the chamber pressure field. These normal vector angles can be computed online by measuring the changes to the earth pressure in the shield's chamber using a BP neural network model of the chamber pressure field distribution. An experimental example that uses excavation data from an actual EPB shield is given to illustrate the effectiveness of the proposed method. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Shield machine Earth pressure balance Normal vector Stability particle swarm optimization algorithm

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Stochastic numerical treatment for solving Troesch's problem

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INFORMATION SCIENCES 2014年 279卷 860-873页

作者： Raja, Muhammad Asif Zahoor COMSATS Inst Informat Technol Dept Elect Engn Attock Pakistan Int Islamic Univ Fac Engn & Technol Dept Elect Engn Islamabad Pakistan

In this article, the numerical techniques are presented for the solution of Troesch's problem based on neural networks optimized with three different methods including particle swarm optimization (PSO), active set (AS) and PSO hybridized with AS (PSO-AS) algorithms. The variable transformation is applied in order to convert the original problem to a transformed problem which is relatively less stiff to solve. Feed-forward artificial neural networks are used to model the transformed problem. Learning of adjustable parameters is made with PSO, AS and PSO-AS algorithms. The proposed methodologies are applied to a number of cases for stiff and non-stiff boundary value problems. The comparative analyses are carried out with other standard numerical solutions, as well as approximate analytical solver. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Troesch's problem Non-linear ODE Artificial neural network particle swarm optimization algorithm Active set algorithm Hybrid technique

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