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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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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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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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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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Improved BiLSTM Model For Online Food Safety Risk Prediction

Improved BiLSTM Model For Online Food Safety Risk Prediction

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第二十届分布式计算及其应用国际学术研讨会

作者： Zekai Zhang Mao Li Jun Sun Qidong Chen School Of Artificial Intelligence and Computer Science Jiangnan University

The prediction of security risk is a new problem in the field of *** value of food safety risk is dynamic,non-linear and *** order to improve the prediction accuracy of non-stationary sequences,this paper proposes an improved time series prediction model of bidirectional long short-term memory network based on NSADAM optimization *** using NS-ADAM optimization algorithm,the non-stationary series can be approximately regarded as stationary series in a fixed window *** with the advantages of two-way long-term and short-term network model to strengthen the correlation between current data and historical data,the combined network model significantly improves the prediction accuracy of non-stationary time *** experimental results show that compared with the traditional integrated moving average autoregressive model and the conventional long-term and short-term memory network model,the improved model has higher prediction accuracy and better fitting effect for non-stationary series.

关键词： network food safety risk prediction optimization algorithm bidirectional long short-term memory network

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OPTIMAL ONLINE CYBERBULLYING DETECTION

OPTIMAL ONLINE CYBERBULLYING DETECTION

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Daphney-Stavroula Zois Angeliki Kapodistria Mengfan Yao Charalampos Chelmis Electrical and Computer Engineering Department Department of Computer Science University at Albany SUNY Albany NY USA

ISBN: (纸本)9781538646595

Cyberbullying has emerged as a serious societal and public health problem that demands accurate methods for the detection of cyberbullying instances in an effort to mitigate the consequences. While techniques to automatically detect cyberbullying incidents have been developed, the scalability and timeliness of existing cyberbullying detection approaches have largely been ignored. We address this gap by formulating cyberbullying detection as a sequential hypothesis testing problem. Based on this formulation, we propose a novel algorithm designed to reduce the time to raise a cyberbullying alert by drastically reducing the number of feature evaluations necessary for a decision to be made. We demonstrate the effectiveness of our approach using a real-world dataset from Twitter, one of the top five networks with the highest percentage of users reporting cyberbullying instances. We show that our approach is highly scalable while not sacrificing accuracy for scalability.

关键词： cyber harassment social media optimization algorithm selection process classification Cyberbullying Social Media Process selection optimization algorithms Scalability

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OP-Synthetic: identification of optimal genetic manipulations for the overproduction of native and non-native metabolites

OP-Synthetic: identification of optimal genetic manipulation...

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第六届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会

作者： Honglei Liu Yanda Li Xiaowo Wang MOE Key Laboratory of Bioinformatics Bioinformatics Division and Center for Synthetic and Systems Biology TNLI ST/Department of Automation Tsinghua University Beijing 100084 China

Backgroud: Constraint-based flux analysis have been widely used in metabolic engineering to predict genetic optimization *** methods seek to find genetic manipulations that maximally couple the desired metabolite with the cellular growth ***, such framework does not work well for overproducing chemicals that are not closely connected with biomass, for example non-native biochemical production by introducing synthetic pathways into heterologous host cells.

关键词： Metabolic Engineering optimization algorithm Metabolic Network

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MECHANICAL BEHAVIOR OF HORIZONTAL SWIVEL SYSTEM WITH UHPC SPHERICAL HINGE UNDER SEISMIC ACTION

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CIVIL ENGINEERING JOURNAL-STAVEBNI OBZOR 2021年第2期30卷 474-489页

作者： Wang, Jiawei Cao, Bing Huang, Bo Du, Yihan Anhui Polytech Univ Sch Architecture & Civil Engn Dept Civil Engn Beijing Meddle Rd Wuhu City Peoples R China

In the process of rotation, the total weight of the bridge structure is jointly supported by the spherical hinge and the supporting structure, and its lateral stability is poor. It is easy to lose stability under the action of dynamic loads such as seismic action effect. The present paper takes a 10,000-ton continuous rigid frame swivel bridge as the re-search object, analyzes the dynamic response of the seismic action to the horizontal swivel system and establishes several structure simulation models. Eighteen seismic waves in three directions that meet the calculation requirements are screened for time history analysis and compared with the response spectrum method. Finally, an optimization algorithm for the seismic response of the bridge under horizontal swivel system is proposed based on the mode superposition method. The UHPC spherical hinge bears all the vertical forces and 20% of the bending moment caused by the seismic action, the support structure bearing the remaining 80% of the bending moment. The optimization algorithm proposed in this paper features high accuracy.

关键词： Horizontal rotation UHPC spherical hinge Rotating process simulation Seismic time history analysis optimization algorithm

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