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2010 International Conference on Intelligent Computing and Cognitive Informatics (ICICCI 2010)

作者： Mojtaba Romoozi Mehdi Vahidipour Morteza Romoozi Sudeh Maghsoodi Member of Young Scholars Club Islamic Azad University KashanI.R.Iran Faculty of Engineering The University of Kashan KashanI.R.Iran Faculty of Engineering Islamic Azad University KashanI.R.Iran Student of Engineering Islamic Azad University KashanI.R.Iran

Layout is an important issue in designing sensor *** paper brings a new idea for the positioning of nodes in a wireless sensor *** sensors communicate with each other to transmit their data to a high energy communication node which acts as an interface between data processing unit and *** of sensor locations is essential to provide communication for a longer *** energy efficient layout with good coverage based on Genetic algorithm is proposed *** the process of optimization,sensors move to form a uniformly distributed *** two objectives taken into consideration are coverage and *** a set of network layouts are *** simulation results also exhibit improvement of performance with increase in number of generations in the algorithm.

关键词： Wireless sensor networks Coverage Energy consumption Clustering algorithm optimization algorithm

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A Multi-objective Shuffled Bat algorithm for Optimal Placement and Sizing of DGs with Load variations

A Multi-objective Shuffled Bat Algorithm for Optimal Placeme...

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IEEE Region 10 Conference

作者： Chandrasekhar Yammani National Institute of Technology Warangal

ISBN: (纸本)9781509025985

A new hybrid Multi-objective Shuffled Bat optimization algorithm is proposed in this paper for Distributed generations (DGs) optimal placement and sizing. Multiple objectives like system power losses, cost of DG and system voltage profiles are considered to evaluate the impact of DG placement and sizing for an optimal development of the distribution system with load variations. Furthermore, the study is demonstrated with different % loading such as 80,100 and 120% of base load condition. The proposed technique is tested in 33 bus distribution network, and compared against Non-dominated Sorting Genetic algorithm II (NSGA-II).

关键词： Distributed Generation Distribution system loading Power Loss minimization optimization algorithm Shuffled Bat algorithm

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Design and Implementation of Monitoring Early-warning System for Subway Construction

Design and Implementation of Monitoring Early-warning System...

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作者： ZHANG Yu LV Yunbing Mechanical and automation School Hu Bei University Zhixing college

In the current of informatization,the control and monitor of multiple unpredictable factors during subway construction are to turn intellectualized. By using information technology and optimization,a monitoring early-warning system with multiple functions can be built,which can analyze the technical scheme and monitoring data effectively. Meanwhile,the system can offer practical guidance scheme and safety guarantee for field construction.

关键词： Subway construction Monitoring Early warning system optimization algorithm

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Intelligent Resource Scheduling Method for Surface Observation of Satellites based on Segmented Coding

Intelligent Resource Scheduling Method for Surface Observati...

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第六届体系工程学术会议—体系工程与高质量发展

作者：俞棋睿尹明娄矫媛媛王笑潘晓刚 College of Science National University of Defense Technology College of Systems Engineering National University of Defense Technology

With the development of modern military strategy, satellite observation has become a key asset for obtaining global security and operational environment dynamics. This article proposes an intelligent scheduling method for ground observation of satellite based on segmented coding, aiming to optimize observation plans, improve the quality and efficiency of data collection. The article first analyzes the current research status of satellite observation duration allocation and points out the shortcomings of current research on ground observation task duration allocation. In response to this issue, this article establishes an observation duration allocation model, which maximizes the observation benefits of satellites in different orbits(high, medium, and low) by adjusting the observation duration decision variables of each satellite. The model introduces an encoding system to represent different observation time allocation schemes and establishes a relationship function between observation duration and benefit value. Furthermore, this article proposes an improved genetic algorithm based on allele replacement to solve the allocation problem of observation time. The experimental results show that the method tends to stabilize after 10000 iterations, and the total allocatable time resource utilization rate of the proposed scheduling scheme reaches 99.9999%, which is much higher than the benefit value of the uniform allocation scheme, proving the feasibility and effectiveness of the proposed method in this paper.

关键词： satellite observation Resource scheduling Observation duration allocation Genetic algorithm optimization algorithm

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The performance of the progressive resolution optimizer (PRO) for RapidArc planning in targets with low-density media

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JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS 2013年第6期14卷 205-221页

作者： Kan, Monica W. K. Leung, Lucullus H. T. Yu, Peter K. N. Princess Margaret Hosp Dept Oncol Hong Kong Hong Kong Peoples R China City Univ Hong Kong Dept Phys & Mat Sci Kowloon Tong Hong Kong Peoples R China

A new version of progressive resolution optimizer (PRO) with an option of air cavity correction has been implemented for RapidArc volumetric-modulated arc therapy (RA). The purpose of this study was to compare the performance of this new PRO with the use of air cavity correction option (PRO10_air) against the one without the use of the air cavity correction option (PRO10_no-air) for RapidArc planning in targets with low-density media of different sizes and complexities. The performance of PRO10_no-air and PRO10_air was initially compared using single-arc plans created for four different simple heterogeneous phantoms with virtual targets and organs at risk. Multiple-arc planning of 12 real patients having nasopharyngeal carcinomas (NPC) and ten patients having non-small cell lung cancer (NSCLC) were then performed using the above two options for further comparison. Dose calculations were performed using both the Acuros XB (AXB) algorithm with the dose to medium option and the analytical anisotropic algorithm (AAA). The effect of using intermediate dose option after the first optimization cycle in PRO10_air and PRO10_no-air was also investigated and compared. Plans were evaluated and compared using target dose coverage, critical organ sparing, conformity index, and dose homogeneity index. For NSCLC cases or cases for which large volumes of low-density media were present in or adjacent to the target volume, the use of the air cavity correction option in PRO10 was shown to be beneficial. For NPC cases or cases for which small volumes of both low-and high-density media existed in the target volume, the use of air cavity correction in PRO10 did not improve the plan quality. Based on the AXB dose calculation results, the use of PRO10_air could produce up to 18% less coverage to the bony structures of the planning target volumes for NPC cases. When the intermediate dose option in PRO10 was used, there was negligible difference observed in plan quality between optimizations

关键词： RapidArc optimization algorithm Acuros XB algorithm low-density media air cavity correction

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Pressure Vessel Design Simulation Using Hybrid Harmony Search algorithm 19

Pressure Vessel Design Simulation Using Hybrid Harmony Searc...

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Proceedings of the 3rd International Conference on Big Data Research

作者： Alaa A. Alomoush Mohammed I. Younis Khalid S. Aloufi AbdulRahman A. Alsewari Kamal Z. Zamli College of Computing and Applied Sciences Univiersiti Malaysia Pahang Pahang Malaysia Department of Computer Engineering College of Engineering University of Baghdad Iraq College of Computer Science and Engineering Taibah University Medina Saudi Arabia IBM Centre of Excellence College of Computing and Applied Sciences Univiersiti Malaysia Pahang Pahang Malaysia

ISBN: (纸本)9781450372015

Recently the development of optimization algorithm is rapidly increased. Among several optimization algorithms, Harmony Search (HS) has been recently proposed for solving engineering optimization problems. The HS has some weaknesses such as parameters selection and falling in local optima. Many variants proposed to solve these problems. This paper presents successful hybrid algorithms with high performance to solve the pressure vessel design simulation. The hybrid algorithms consist of well-known variants of HS and an opposition-based learning technique. The hybrid algorithm improved the HS exploration and avoiding falling in local optima, which lead the algorithm to provide significant results.

关键词： Computational Intelligence Pressure Vessel Design hybrid algorithm opposition-based learning Harmony Search algorithm optimization algorithm

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Improved Model Predictive Control for Grid-connected Inverter

Improved Model Predictive Control for Grid-connected Inverte...

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第32届中国控制与决策会议

作者： Yong Chen Pengcheng Ma Jingjing Huang Lei Yang Xiangqian Tong School of Electrical Engineering Xi'an University of Technology CNPC Chuanqing Drilling Engineering Company Limited School of Electronic and Information Engineering Xi'an Jiaotong University

The traditional model predictive control（MPC） has the problems of heavy computational burden and low predictive *** improved MPC is therefore proposed in this paper via combining the idea of no-beat control to calculate the target reference voltage *** optimizing the voltage vector selection,not only the calculation times of the control algorithm are reduced,but also the load current harmonic content,the inverter switching frequency and the power loss are *** delay compensation is carried out to improve the accuracy of the model prediction,so as to improve the operation efficiency of the grid-connected ***,the improved MPC simulation model is established in MATLAB/SIMULINK and the improved MPC is compared with the traditional MPC to verify its effectiveness in the experimental prototype.

关键词： MPC time delay compensation optimization algorithm

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Identification of functional information subgraphs in cultured neural networks

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BMC NEUROSCIENCE 2009年第1-Sup期10卷 1-1页

作者： Gintautas, Vadas Bettencourt, Luis M. A. Ham, Michael I. Los Alamos Natl Lab Ctr Nonlinear Studies & T5 Los Alamos NM 87545 USA Santa Fe Inst Santa Fe NM 87501 USA Univ N Texas Ctr Network Neurosci Denton TX 76203 USA

We present a general information theoretic approach for identifying functional subgraphs in complex neuronal networks where the spiking dynamics of a subset of nodes (neurons) are observable. We show that the uncertainty in the state of each node can be written as a sum of information quantities involving a growing number of variables at other nodes. We demonstrate that each term in this sum is generated by successively conditioning mutual information on new measured variables, in a way analogous to a discrete differential calculus. The analogy to a Taylor series suggests efficient optimization algorithms for determining the state of a target variable in terms of functional groups of other nodes. We apply this methodology to electrophysiological recordings of cortical neuronal network grown in vitro. Despite strong stochasticity, we show that each cell's firing is generally explained by the activity of a small number of other neurons. We identify these neuronal subgraphs in terms of their redundant or synergetic character and reconstruct neuronal circuits that account for the state of target cells. [ABSTRACT FROM AUTHOR]

关键词： Neural Network optimization algorithm Mutual Information Theoretic Approach Taylor Series

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Distributed Optimized Tracking algorithms for an AUV Formation Application

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INTEGRATED FERROELECTRICS 2015年第1期160卷 18-26页

作者： Li, Ya-Li Lei, Jing Li, Wu-Xin Jiang, Zuo Yunnan Nationalities Univ Sch Math & Comp Sci Kunming 650500 Peoples R China Michigan State Univ Dept Elect & Comp Engn E Lansing MI 48824 USA

This paper addresses the design problem of the distributed optimization algorithms for tracking targets over Wireless Sensor Networks through coordinative communication. To balance the tradeoff between tracking error and control power consumption, a performance index is established in advance. Then, the optimization algorithm is designed consisting of an error integrator term and a feedforward term which can eliminate the steady-state tracking error and compensate the disturbance effect respectively. Finally, the numerical simulation is performed. By applying the designed control in an Autonomous Underwater Vehicle leader-follower formation control system, the algorithms are validated effective, feasible, and easy to be implemented.

关键词： distributed control system Wireless Sensor Networks integrator optimization algorithm coordinative communication

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Effective optimization Technique for Power System Stabilization using Artificial Bee Colony

Effective Optimization Technique for Power System Stabilizat...

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International Conference on Computer Communication and Informatics

作者： V. Ravi K. Duraiswamy Dept. of EEE K.S.R College of Technology Dept. of CSE K.S.R College of Technology

ISBN: (纸本)9781457715808;9781457715839

The power system stabilizer can suppress the electromechanical oscillation and enhance the power system stability with the aid of its additional excitation control. The need for power system stabilizations has been increasing day by day. The demand for electric power requirement has motivated the usage of power system in an effective and reliable way. The stability of the power system is the ability to extend restoring forces equal to or greater than the disturbing forces to sustain the state of equilibrium. Power industries are restructured to provide effective utilization to more users at lower prices and better power efficiency. The complexity of the Power systems has been increasing as they become inter-connected. Load demand also increases linearly with the increase in users. Since stability phenomena limits the transfer capability of the system, there is a need to ensure stability and reliability of the power system due to economic reasons. With these conditions, experts and researchers were continually tasked to find simple, effective and economical strategy of attaining stabilization of the power system, which is considered of highest priority. Thus, because of the importance of the stability of the power systems, stabilizing control techniques have been used for the multi-machine power system with the help of intelligent methods. The optimal sequential design for multi-machine power systems is very essential. As a result, serious consideration is now being given on the concern of power system stabilization control. In recent times, the utilization of optimization techniques becomes possible to deal with control signals in power system. This paper uses the Artificial Bee Colony algorithm for better stability of the power system. Simulation results suggest that the proposed technique is better for power system stabilization when compared to the conventional techniques.

关键词： Power System Stabilization optimization algorithm Artificial Bee Colony

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