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Well production optimization using streamline features-based objective function and Bayesian adaptive direct search algorithm

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Petroleum Science 2022年第6期19卷 2879-2894页

作者： Qi-Hong Feng Shan-Shan Li Xian-Min Zhang Xiao-Fei Gao Ji-Hui Ni School of Petroleum Engineering China University of Petroleum(East China)Qingdao266580ShandongChina Shandong Institute of Petroleum and Chemical Technology Dongying257061ShandongChina CNOOC China Limited Shenzhen BranchShenzhen518000GuangdongChina

Well production optimization is a complex and time-consuming task in the oilfield *** combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well *** method spends most of computing time in objective function evaluation by reservoir numerical simulator which limits its optimization *** improve optimization efficiency,a well production optimization method using streamline features-based objective function and Bayesian adaptive direct search optimization(BADS)algorithm is *** new objective function,which represents the water flooding potential,is extracted from streamline *** only needs to call the streamline simulator to run one time step,instead of calling the simulator to calculate the target value at the end of development,which greatly reduces the running time of the *** the well production optimization model is established and solved by the BADS *** feasibility of the new objective function and the efficiency of this optimization method are verified by three *** demonstrate that the new objective function is positively correlated with the cumulative oil *** the BADS algorithm is superior to other common algorithms in convergence speed,solution stability and optimization ***,this method can significantly accelerate the speed of well production optimization process compared with the objective function calculated by other conventional *** can provide a more effective basis for determining the optimal well production for actual oilfield development.

关键词： Well production Optimization efficiency Streamline simulation Streamline feature objective function Bayesian adaptive direct search algorithm

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A Differential Game Based Approach Against objective function Attack in Cognitive Networks

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Chinese Journal of Electronics 2018年第4期27卷 879-888页

作者： FENG Guangsheng LIN Junyu ZHAO Qian WANG Huiqiang LYU Hongwu ZHAO Xiaoyu HAN Jizhong LI Bingyang College of Computer Science and Technology Harbin Engineering University Institute of Information Engineering Chinese Academy of Sciences School of Computer and Information Engineering Harbin University of Commerce

We study the problem of defense strategy against objective function attack(OFA) in Cognitive networks(CNs), where the network can be operated at the optimal state by adapting the parameters of its objective function. An OFA attacker can disrupt the parameter adaptation by interfering measures, which results in some operating parameters of the objective function deviating from their optimal settings. We first model the interactive process between the OFA attacker and defense system using differential game theory, and propose a defense strategy by introducing a new metric, namely, threat factor. Then,we obtain the optimal defense strategy by proving the existence of the saddle point of the proposed model. Moreover,this defense strategy is scale-free such that it can conquer a large number of OFAs in a decentralized way. Finally, we conduct extensive simulations to show that the proposed approach is effective.

关键词： Cognitive networks objective function Operating parameter Saddle point

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A Novel Separability objective function in CNN for Feature Extraction of SAR Images

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Chinese Journal of Electronics 2019年第2期28卷 423-429页

作者： GAO Fei WANG Meng WANG Jun YANG Erfu ZHOU Huiyu Department of Electronic and Information Engineering Beihang University Department of Design Manufacture and Engineering Management (DMEM) University of Strathclyde Department of Informatics University of Leicester

Convolutional neural network(CNN) has become a promising method for Synthetic aperture radar(SAR) target recognition. Existing CNN models aim at seeking the best separation between classes, but rarely care about the separability of them. We performs a separability measure by analyzing the property of linear separability, and proposes an objective function for CNN to extract linearly separable features. The experimental results indicate the output features are linearly separable,and the classification results are comparable with the other state of the art techniques.

关键词： Synthetic aperture radar(SAR) Convolution neural network(CNN) Classification Linear separability objective function

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FUZZY IDENTIFICATION METHOD BASED ON A NEW objective function

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Chinese Journal of Aeronautics 2000年第3期13卷 162-166页

作者：王宏伟贺汉根黄柯棣 Dept. of Automatic Control Natl. Univ. of Defense Technology Changsha 410073 China

A method of fuzzy identification based on a new objective function is proposed. The method could deal with the issue that input variables of a system have an effect on the input space while output variables of the system do not exert an influence on the input space in the proposed objective functions of fuzzy clustering. The method could simultaneously solve the problems about structure identification and parameter estimation; thus it makes the fuzzy model become optimal. Simulation example demonstrates that the method could identify non linear systems and obviously improve modeling accuracy.

关键词： objective function fuzzy clustering fuzzy identification non linear systems

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Modularity-like objective function in annotated networks

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Frontiers of physics 2017年第6期12卷 109-113页

作者： Jia-Rong Xie Bing-Hong Wang Department of Modern Physics University of Science and Technology of China Hefei 230026 China

We ascertain the modularity-like objective function whose optimization is equivalent to the maximum likelihood in annotated networks. We demonstrate that the modularity-like objective function is a lin- ear combination of modularity and conditional entropy. In contrast with statistical inference methods, in our method, the influence of the metadata is adjustable; when its influence is strong enough, the metadata can be recovered. Conversely, when it is weak, the detection may correspond to another partition. Between the two, there is a transition. This paper provides a concept for expanding the scope of modularity methods.

关键词： community structure annotated networks modularity objective function

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Randomized objective function Linear Programming in Risk Management

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Journal of Applied Mathematics and Physics 2021年第3期9卷 391-402页

作者： Dennis Ridley Felipe Llaugel Inger Daniels Abdullah Khan School of Business and Industry Florida A&M University Tallahassee FL USA Department of Scientific computing Florida State University Tallahassee FL USA College of Engineering Universidad Dominicana O&M Santo Domingo Dominican Republic School of Business Claflin University Orangeburg SC USA

The traditional linear programming model is deterministic. The way that uncertainty is handled is to compute the range of optimality. After the optimal solution is obtained, typically by the simplex method, one considers the effect of varying each objective function coefficient, one at a time. This yields the range of optimality within which the decision variables remain constant. This sensitivity analysis is useful for helping the analyst get a sense for the problem. However, it is unrealistic because objective function coefficients tend not to stand still. They are typically profit contributions from products sold and are subject to randomly varying selling prices. In this paper, a realistic linear program is created for simultaneously randomizing the coefficients from any probability distribution. Furthermore, we present a novel approach for designing a copula of random objective function coefficients according to a specified rank correlation. The corresponding distribution of objective function values is created. This distribution is examined directly for central tendency, spread, skewness and extreme values for the purpose of risk analysis. This enables risk analysis and business analytics, emerging topics in education and preparation for the knowledge economy.

关键词： Linear Programming Random objective function Profit Distribution Risk Monte Carlo Simulation

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A Novel Approach to Optimize the objective function Based on VC Dimension and Structural Risk Minimization

A Novel Approach to Optimize the Objective Function Based on...

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第三十届中国控制会议

作者： QIU Xintao,FU Dongmei,YANG Tao School of Automation,University of Science and Technology Beijing,Beijing 100083,P.R.China

＜正＞So far,lots of algorithms and learning methods are taking the empirical risk for the optimization *** this paper,we propose a new way to optimize the objective function based on VC dimension and structural risk *** optimized function F is firstly defined by us,and some effective design forms of it will also be *** we fulfill a useful criterion—the balance minimum optimization *** principle considers not only the empirical risk,but also considers the VC dimension of learning *** the two factors can avoid the underfitting problem and overfitting *** results show that the method we proposed is effective to improve the property of algorithm efficiency,convergence and generalization of the learning ***,the proposed principle for optimization is a new criterion,which is not a practical method for a particular problem of ***,this method is suitable to be applied in many practical situations, which may bring a good generalization performance and efficiency in some learning problems.

关键词： VC Dimension objective function Structural Risk Minimization Balance Minimum Optimization Principle

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SELECTION OF objective functionS AND APPLICATION OF GENETIC ALGORITHMS IN DAMPING DESIGN OF PIPE SYSTEM

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Acta Mechanica Solida Sinica 2003年第2期16卷 171-178页

作者： ChenYanqiu FanQinsban ZhuZigen DepartmentofEngineeringMechanics TsinghuaUniversityBeijing100084China DepartmentofDynamicsEngineering BeltingUniversityofAerosnauticsandAstronauticsBeijing100083China

The vibration failure of pipe system of aeroengine seriously influences the safety of *** damping design is determined by the selection of the design target,method and their *** objective functions for the vibration design of a pipeline or pipe system are introduced,namely,the frequency,amplitude,transfer ratio,curvature and deformation energy as options for the optimization *** genetic algorithms(GA)are adopted as the opti- mization method,in which the selection of the adaptive genetic operators and the method of implementation of the GA process are *** optimization procedure for all the above ob- jective functions is carried out using GA on the basis of finite element software-MSC/NASTRAN. The optimal solutions of these functions and the stress distribution on the structure are calculated and compared through an example,and their characteristics are *** we put forward two new objective functions,curvature and deformation energy for pipe system *** calculations show that using the curvature as the objective function can reflect the case of minimal stress,and the optimization results using the deformation energy represent lesser and more uni- form stress *** calculation results and process showed that the genetic algorithms can effectively implement damping design of engine pipelines and satisfy the efficient engineering design requirement.

关键词： objective function genetic algorithms optimization pipe system

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Noisy component extraction with reference

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Frontiers of Computer Science 2013年第1期7卷 135-144页

作者： Yongjian ZHAO Hong HE Jianxun Mi School of Information Engineering Shandong University Weihai 264209 China Bio-Computing Research Center Shenzhen Graduate School Harbin Institute of Technology Shenzhen 518055 China Key Laboratory of Network Oriented Intelligent Computation Shenzhen 518055 China

Blind source extraction （BSE） is particularly at- tractive to solve blind signal mixture problems where only a few source signals are desired. Many existing BSE methods do not take into account the existence of noise and can only work well in noise-free environments. In practice, the desired signal is often contaminated by additional noise. Therefore, we try to tackle the problem of noisy component extraction. The reference signal carries enough prior information to dis- tinguish the desired signal from signal mixtures. According to the useful properties of Gaussian moments, we incorporate the reference signal into a negentropy objective function so as to guide the extraction process and develop an improved BSE method. Extensive computer simulations demonstrate its validity in the process of revealing the underlying desired signal.

关键词： blind signal processing reference signal Gaus- sian moments negentropy objective function biomedical signal measure performance index

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Dynamic finite element model updating of prestressed concrete continuous box-girder bridge

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Earthquake Engineering and Engineering Vibration 2009年第3期8卷 399-407页

作者： Lin Xiankun Zhang Lingmi Guo Qintao Zhang Yufeng Institute of Vibration Engineering Nanjing University of Aeronautics and Astronautics Nanjing 210016 China College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics Nanjing 210016 China Jiangsu Transportation Research Institute Nanjing 210017 China

The dynamic finite element model （FEM） of a prestressed concrete continuous box-girder bridge, called the Tongyang Canal Bridge, is built and updated based on the results of ambient vibration testing （AVT） using a real-coded accelerating genetic algorithm （RAGA）. The objective functions are defined based on natural frequency and modal assurance criterion （MAC） metrics to evaluate the updated FEM. Two objective functions are defined to fully account for the relative errors and standard deviations of the natural frequencies and MAC between the AVT results and the updated FEM predictions. The dynamically updated FEM of the bridge can better represent its structural dynamics and serve as a baseline in long-term health monitoring, condition assessment and damage identification over the service life of the bridge .

关键词： prestressed concrete continuous box-girder bridge field ambient vibration testing dynamic characteristics model updating accelerating genetic algorithm objective function

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