期刊文献+
共找到893篇文章
< 1 2 45 >
每页显示 20 50 100
Self-adaptive PID controller of microwave drying rotary device tuning on-line by genetic algorithms 被引量:6
1
作者 杨彪 梁贵安 +5 位作者 彭金辉 郭胜惠 李玮 张世敏 李英伟 白松 《Journal of Central South University》 SCIE EI CAS 2013年第10期2685-2692,共8页
The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and wi... The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design. 展开更多
关键词 industrial microwave DRYING ROTARY device self-adaptive PID controller genetic algorithm ON-LINE tuning SELENIUM-ENRICHED SLAG
下载PDF
Acid-pickling plates and strips speed control system by microwave heating based on self-adaptive fuzzy PID algorithm 被引量:7
2
作者 杨彪 彭金辉 +3 位作者 郭胜惠 张世敏 李玮 何涛 《Journal of Central South University》 SCIE EI CAS 2012年第8期2179-2186,共8页
Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful... Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful in overcoming non-linear dynamic behavior, uncertain and time-varying parameters, un-modeled dynamics, and couples between the automatic turbulence control (ATC) and the automatic acid temperature control (AATC) with varying parameters during the operation process. The quasi-cascade control system of inner and outer loop self-adaptive fuzzy PID controller was built, which could effectively control the pickling speed of plates and strips. The simulated results and real application indicate that the plates and strips acid pickling speed control system has good performances of adaptively tracking the parameter variations and anti-disturbances, which ensures the match of acid pickling temperature and turbulence of flowing with acid pickling speed, improving the surface quality of plates and strips acid pickling, and energy efficiency. 展开更多
关键词 self-adaptive fuzzy PID algorithm microwave heating acid pickling plates and strips mixed-acid media
下载PDF
Unfolding neutron spectra from water-pumping-injection multilayered concentric sphere neutron spectrometer using self-adaptive differential evolution algorithm 被引量:5
3
作者 Rui Li Jian-Bo Yang +2 位作者 Xian-Guo Tuo Jie Xu Rui Shi 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2021年第3期41-51,共11页
A self-adaptive differential evolution neutron spectrum unfolding algorithm(SDENUA)is established in this study to unfold the neutron spectra obtained from a water-pumping-injection multilayered concentric sphere neut... A self-adaptive differential evolution neutron spectrum unfolding algorithm(SDENUA)is established in this study to unfold the neutron spectra obtained from a water-pumping-injection multilayered concentric sphere neutron spectrometer(WMNS).Specifically,the neutron fluence bounds are estimated to accelerate the algorithm convergence,and the minimum error between the optimal solution and input neutron counts with relative uncertainties is limited to 10^(-6)to avoid unnecessary calculations.Furthermore,the crossover probability and scaling factor are self-adaptively controlled.FLUKA Monte Carlo is used to simulate the readings of the WMNS under(1)a spectrum of Cf-252 and(2)its spectrum after being moderated,(3)a spectrum used for boron neutron capture therapy,and(4)a reactor spectrum.Subsequently,the measured neutron counts are unfolded using the SDENUA.The uncertainties of the measured neutron count and the response matrix are considered in the SDENUA,which does not require complex parameter tuning or an a priori default spectrum.The results indicate that the solutions of the SDENUA agree better with the IAEA spectra than those of MAXED and GRAVEL in UMG 3.1,and the errors of the final results calculated using the SDENUA are less than 12%.The established SDENUA can be used to unfold spectra from the WMNS. 展开更多
关键词 Water-pumping-injection multilayered spectrometer Neutron spectrum unfolding Differential evolution algorithm self-adaptive control
下载PDF
An improved self-adaptive membrane computing optimization algorithm and its applications in residue hydrogenating model parameter estimation 被引量:1
4
作者 芦会彬 薄翠梅 杨世品 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第10期3909-3915,共7页
In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing(ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied... In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing(ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied improved self-adaptive crossover and mutation formulae that can provide appropriate crossover operator and mutation operator based on different functions of the objects and the number of iterations. The performance of ISMC was tested by the benchmark functions. The simulation results for residue hydrogenating kinetics model parameter estimation show that the proposed method is superior to the traditional intelligent algorithms in terms of convergence accuracy and stability in solving the complex parameter optimization problems. 展开更多
关键词 optimization algorithm membrane computing benchmark function improved self-adaptive operator
下载PDF
Enhanced self-adaptive evolutionary algorithm for numerical optimization 被引量:1
5
作者 Yu Xue YiZhuang +2 位作者 Tianquan Ni Jian Ouyang ZhouWang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第6期921-928,共8页
There are many population-based stochastic search algorithms for solving optimization problems. However, the universality and robustness of these algorithms are still unsatisfactory. This paper proposes an enhanced se... There are many population-based stochastic search algorithms for solving optimization problems. However, the universality and robustness of these algorithms are still unsatisfactory. This paper proposes an enhanced self-adaptiveevolutionary algorithm (ESEA) to overcome the demerits above. In the ESEA, four evolutionary operators are designed to enhance the evolutionary structure. Besides, the ESEA employs four effective search strategies under the framework of the self-adaptive learning. Four groups of the experiments are done to find out the most suitable parameter values for the ESEA. In order to verify the performance of the proposed algorithm, 26 state-of-the-art test functions are solved by the ESEA and its competitors. The experimental results demonstrate that the universality and robustness of the ESEA out-perform its competitors. 展开更多
关键词 self-adaptive numerical optimization evolutionary al-gorithm stochastic search algorithm.
下载PDF
Modified Self-adaptive Immune Genetic Algorithm for Optimization of Combustion Side Reaction of p-Xylene Oxidation 被引量:1
6
作者 陶莉莉 孔祥东 +1 位作者 钟伟民 钱锋 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2012年第6期1047-1052,共6页
In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation fa... In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained. 展开更多
关键词 self-adaptive immune genetic algorithm artificial neural network measurement p-xylene oxidation process
下载PDF
Dynamic self-adaptive ANP algorithm and its application to electric field simulation of aluminum reduction cell 被引量:1
7
作者 王雅琳 陈冬冬 +2 位作者 陈晓方 蔡国民 阳春华 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第12期4731-4739,共9页
Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index ... Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance. 展开更多
关键词 finite element parallel computing(FEPC) region partition(RP) dynamic self-adaptive ANP(DSA-ANP) algorithm electric field simulation aluminum reduction cell(ARC)
下载PDF
Marchenko imaging based on self-adaptive traveltime updating
8
作者 Chen Xiao-Chun Hu Ye-Zheng +4 位作者 Huang Xu-Ri Zhang Hou-Zhu Cao Wei-Ping Xu Yun-Gui Tang Jing 《Applied Geophysics》 SCIE CSCD 2020年第1期81-91,168,169,共13页
Marchenko imaging obtains the subsurface reflectors using one-way Green’s functions,which are retrieved by solving the Marchenko equation.This method generates an image that is free of spurious artifacts due to inter... Marchenko imaging obtains the subsurface reflectors using one-way Green’s functions,which are retrieved by solving the Marchenko equation.This method generates an image that is free of spurious artifacts due to internal multiples.The Marchenko imaging method is a target-oriented technique;thus,it can image a user specified area.In the traditional Marchenko method,an accurate velocity model is critical for estimating direct waves from imaging points to the surface.An error in the velocity model results in the inaccurate estimation of direct waves.In turn,this leads to errors in computation of one-way Green’s functions,which then affects the final Marchenko images.To solve this problem,in this paper,we propose a self-adaptive traveltime updating technique based on the principle of equal traveltime to improve the Marchenko imaging method.The proposed method calculates the time shift of direct waves caused by the error in the velocity model,and corrects the wrong direct wave according to the time shift and reconstructs the correct Green’s functions.The proposed method improves the results of imaging using an inaccurate velocity model.By comparing the results from traditional Marchenko and the new method using synthetic data experiments,we demonstrated that the adaptive traveltime updating Marchenko imaging method could restore the image of geological structures to their true positions. 展开更多
关键词 Marchenko imaging Marchenko equation Green’s function principle of equal traveltime self-adaptive traveltime updating
下载PDF
Generalized Self-Adaptive Genetic Algorithms
9
作者 Bin Wu Xuyan Tu +1 位作者 Jian Wu Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China Department of Information and Control Engineering, Southwest Institute of Technology, Mianyang 621002, China 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2000年第1期72-75,共4页
In order to solve the problem between searching performance and convergence of genetic algorithms, a fast genetic algorithm generalized self-adaptive genetic algorithm (GSAGA) is presented. (1) Evenly distributed init... In order to solve the problem between searching performance and convergence of genetic algorithms, a fast genetic algorithm generalized self-adaptive genetic algorithm (GSAGA) is presented. (1) Evenly distributed initial population is generated. (2) Superior individuals are not broken because of crossover and mutation operation for they are sent to subgeneration directly. (3) High quality im- migrants are introduced according to the condition of the population schema. (4) Crossover and mutation are operated on self-adaptation. Therefore, GSAGA solves the coordination problem between convergence and searching performance. In GSAGA, the searching per- formance and global convergence are greatly improved compared with many existing genetic algorithms. Through simulation, the val- idity of this modified genetic algorithm is proved. 展开更多
关键词 generalized self-adaptive genetic algorithm initial population IMMIGRATION fitness function
下载PDF
Differential Evolution Algorithm Based Self-adaptive Control Strategy for Fed-batch Cultivation of Yeast
10
作者 Aiyun Hu Sunli Cong +2 位作者 Jian Ding Yao Cheng Enock Mpofu 《Computer Systems Science & Engineering》 SCIE EI 2021年第7期65-77,共13页
In the fed-batch cultivation of Saccharomyces cerevisiae,excessive glucose addition leads to increased ethanol accumulation,which will reduce the efficiency of glucose utilization and inhibit product synthesis.Insuffi... In the fed-batch cultivation of Saccharomyces cerevisiae,excessive glucose addition leads to increased ethanol accumulation,which will reduce the efficiency of glucose utilization and inhibit product synthesis.Insufficient glucose addition limits cell growth.To properly regulate glucose feed,a different evolution algorithm based on self-adaptive control strategy was proposed,consisting of three modules(PID,system identification and parameter optimization).Performance of the proposed and conventional PID controllers was validated and compared in simulated and experimental cultivations.In the simulation,cultivation with the self-adaptive control strategy had a more stable glucose feed rate and concentration,more stable ethanol concentration around the set-point(1.0 g·L^(-1)),and final biomass concentration of 34.5 g-DCW·L^(-1),29.2%higher than that with a conventional PID control strategy.In the experiment,the cultivation with the self-adaptive control strategy also had more stable glucose and ethanol concentrations,as well as a final biomass concentration that was 37.4%higher than that using the conventional strategy. 展开更多
关键词 Saccharomyces cerevisiae Ethanol accumulation differential evolution algorithm self-adaptive control
下载PDF
Particle Swarm Optimization Algorithm Based on Chaotic Sequences and Dynamic Self-Adaptive Strategy
11
作者 Mengshan Li Liang Liu +4 位作者 Genqin Sun Keming Su Huaijin Zhang Bingsheng Chen Yan Wu 《Journal of Computer and Communications》 2017年第12期13-23,共11页
To deal with the problems of premature convergence and tending to jump into the local optimum in the traditional particle swarm optimization, a novel improved particle swarm optimization algorithm was proposed. The se... To deal with the problems of premature convergence and tending to jump into the local optimum in the traditional particle swarm optimization, a novel improved particle swarm optimization algorithm was proposed. The self-adaptive inertia weight factor was used to accelerate the converging speed, and chaotic sequences were used to tune the acceleration coefficients for the balance between exploration and exploitation. The performance of the proposed algorithm was tested on four classical multi-objective optimization functions by comparing with the non-dominated sorting genetic algorithm and multi-objective particle swarm optimization algorithm. The results verified the effectiveness of the algorithm, which improved the premature convergence problem with faster convergence rate and strong ability to jump out of local optimum. 展开更多
关键词 Particle SWARM algorithm CHAOTIC SEQUENCES self-adaptive STRATEGY MULTI-OBJECTIVE Optimization
下载PDF
Self-Adaptive Algorithms for the Split Common Fixed Point Problem of the Demimetric Mappings
12
作者 Xinhong Chen Yanlai Song +1 位作者 Jianying He Liping Gong 《Journal of Applied Mathematics and Physics》 2019年第10期2187-2199,共13页
The split common fixed point problem is an inverse problem that consists in finding an element in a fixed point set such that its image under a bounded linear operator belongs to another fixed-point set. In this paper... The split common fixed point problem is an inverse problem that consists in finding an element in a fixed point set such that its image under a bounded linear operator belongs to another fixed-point set. In this paper, we present new iterative algorithms for solving the split common fixed point problem of demimetric mappings in Hilbert spaces. Moreover, our algorithm does not need any prior information of the operator norm. Weak and strong convergence theorems are given under some mild assumptions. The results in this paper are the extension and improvement of the recent results in the literature. 展开更多
关键词 HILBERT Space Demimetric Mapping SPLIT Common Fixed Point PROBLEM self-adaptive algorithm
下载PDF
An Improved Binary Wolf Pack Algorithm Based on Adaptive Step Length and Improved Update Strategy for 0-1 Knapsack Problems
13
作者 Liting Guo Sanyang Liu 《国际计算机前沿大会会议论文集》 2017年第2期105-106,共2页
Binary wolf pack algorithm (BWPA) is a kind of intelligence algorithm which can solve combination optimization problems in discrete spaces.Based on BWPA, an improved binary wolf pack algorithm (AIBWPA) can be proposed... Binary wolf pack algorithm (BWPA) is a kind of intelligence algorithm which can solve combination optimization problems in discrete spaces.Based on BWPA, an improved binary wolf pack algorithm (AIBWPA) can be proposed by adopting adaptive step length and improved update strategy of wolf pack. AIBWPA is applied to 10 classic 0-1 knapsack problems and compared with BWPA, DPSO, which proves that AIBWPA has higher optimization accuracy and better computational robustness. AIBWPA makes the parameters simple, protects the population diversity and enhances the global convergence. 展开更多
关键词 BINARY WOLF PACK algorithm 0-1 knapsack problem ADAPTIVE step length update strategy
下载PDF
EVOLUTIONARY FUZZY GUIDANCE LAW WITH SELF-ADAPTIVE REGION 被引量:3
14
作者 邹庆元 姜长生 吴柢 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2004年第3期234-240,共7页
Effective guidance is one of the most important tasks to the performance of air-to-air missile. The fuzzy logic controller is able to perform effectively even in situations where the information about the plant is ina... Effective guidance is one of the most important tasks to the performance of air-to-air missile. The fuzzy logic controller is able to perform effectively even in situations where the information about the plant is inaccurate and the operating conditions are uncertain. Based on the proportional navigation, the fuzzy logic and the genetic algorithm are combined to develop an evolutionary fuzzy navigation law with self-adapt region for the air-to-air missile guidance. The line of sight (LOS) rate and the closing speed between the missile and the target are inputs of the fuzzy controller. The output of the fuzzy controller is the commanded acceleration. Then a nonlinear function based on the conventional fuzzy logic control is imported to change the region. This nonlinear function can be changed with the input variables. So the dynamic change of the fuzzy variable region is achieved. The guidance law is optimized by the genetic algorithm. Simulation results of air-to-air missile attack using MATLAB show that the method needs less acceleration and shorter flying time, and its realization is simple.[KH*3/4D] 展开更多
关键词 guidance law fuzzy logic genetic algorithm self-adaptive region
下载PDF
Dynamic finite element model updating using meta-model and genetic algorithm 被引量:3
15
作者 费庆国 李爱群 缪长青 《Journal of Southeast University(English Edition)》 EI CAS 2006年第2期213-217,共5页
Current dynamic finite element model updating methods are not efficient or restricted to the problem of local optima. To circumvent these, a novel updating method which integrates the meta-model and the genetic algori... Current dynamic finite element model updating methods are not efficient or restricted to the problem of local optima. To circumvent these, a novel updating method which integrates the meta-model and the genetic algorithm is proposed. Experimental design technique is used to determine the best sampling points for the estimation of polynomial coefficients given the order and the number of independent variables. Finite element analyses are performed to generate the sampling data. Regression analysis is then used to estimate the response surface model to approximate the functional relationship between response features and design parameters on the entire design space. In the fitness evaluation of the genetic algorithm, the response surface model is used to substitute the finite element model to output features with given design parameters for the computation of fitness for the individual. Finally, the global optima that corresponds to the updated design parameter is acquired after several generations of evolution. In the application example, finite element analysis and modal testing are performed on a real chassis model. The finite element model is updated using the proposed method. After updating, root-mean-square error of modal frequencies is smaller than 2%. Furthermore, prediction ability of the updated model is validated using the testing results of the modified structure. The root-mean-square error of the prediction errors is smaller than 2%. 展开更多
关键词 finite element model model updating response surface model genetic algorithm
下载PDF
Finite Element Model Updating of Bridge Structures Based on Sensitivity Analysis and Optimization Algorithm 被引量:6
16
作者 HUANG Minshui ZHU Hongping 《Wuhan University Journal of Natural Sciences》 CAS 2008年第1期87-92,共6页
The dynamic characteristics of bridge structures, such as the natural frequencies, mode shapes and model damping ratio, are the basis of structural dynamic computation, seismic analysis, vibration control and structur... The dynamic characteristics of bridge structures, such as the natural frequencies, mode shapes and model damping ratio, are the basis of structural dynamic computation, seismic analysis, vibration control and structural health condition monitoring. In this paper, a three-dimensional finite-element model is established for a highway bridge over a railway on No.312 National Highway and the ambient test is carried out in site, the dynamic characteristics of the bridge are studied using the finite-element analysis and ambient vibration measurements. Comparison between the theoretical and experimental results shows that the frequency differences of the modes range between 0.44% and 8.77%. If the measurement is more reliable, the finite element model updating is necessary. Thus, a set of design variables is selected based on sensitivity analysis, then the finite element model of the bridge is updated based on optimization algorithm. The results of model updating show that the proposed updating method in this paper is more simple and effective, the updated finite element model can reflect the dynamic characteristics of the bridge better, the analytical results can provide the theoretical basis for damage identification and health condition monitoring of the bridge. 展开更多
关键词 sensitivity analysis optimization algorithm model updating bridge structure
下载PDF
Self-adaptive fuzzy controller with formulary rule for servo control of discharge gap in Micro EDM 被引量:2
17
作者 TongHao LiYong 《High Technology Letters》 EI CAS 2012年第3期223-229,共7页
In micro electrical discharge machining (micro EDM), it is difficult for servo controlling the narrow discharge gap with the characters of non-linear and quick change. In this paper, aiming at solving the problems a... In micro electrical discharge machining (micro EDM), it is difficult for servo controlling the narrow discharge gap with the characters of non-linear and quick change. In this paper, aiming at solving the problems above, a self-adaptive fuzzy controller with formulary rule (SAFCFR) is presented based on the dual feedbacks composed by gap electric signal and discharge-ratio statistics. To ensure the properties of self-optimizing and fast stabilization, the formulary rule was designed with a tuning factor. In addition, the fast-convergence algorithms were introduced to adjust control target center and output scale factor. In this way, the normal discharge ratio can tend to the highest value during micro-EDM process. Experimental results show that the proposed algorithms are effective in improving the servo-control performance. According to the drilling-micro-EDM experiments, the machining efficiency is improved by 20% through applying SAFCFR. Moreover, SAFCFR is a prompt way to optimize parameters of discharge-gap servo control. 展开更多
关键词 MICRO-EDM self-adaptive fuzzy control discharge gap formulary rule fast con-vergence algorithm
下载PDF
Computing the Moore-Penrose Inverse of a Matrix Through Symmetric Rank-One Updates 被引量:1
18
作者 Xuzhou Chen Jun Ji 《American Journal of Computational Mathematics》 2011年第3期147-151,共5页
This paper presents a recursive procedure to compute the Moore-Penrose inverse of a matrix A. The method is based on the expression for the Moore-Penrose inverse of rank-one modified matrix. The computational complexi... This paper presents a recursive procedure to compute the Moore-Penrose inverse of a matrix A. The method is based on the expression for the Moore-Penrose inverse of rank-one modified matrix. The computational complexity of the method is analyzed and a numerical example is included. A variant of the algorithm with lower computational complexity is also proposed. Both algorithms are tested on randomly generated matrices. Numerical performance confirms our theoretic results. 展开更多
关键词 FINITE RECURSIVE algorithm Moore-Penrose INVERSE SYMMETRIC Rank-One update
下载PDF
关于数据库更新UPDATE命令的算法
19
作者 鹿宏 谢印宝 《淄博学院学报(自然科学与工程版)》 2000年第3期19-21,共3页
本文从教学方法的角度讨论用其它工作区中数据库更新当前工作区中数据库的更新命令 UPDATE的算法,并通过实例加以说明 .
关键词 教学方法 数据库 更新算法 update命令 更新操作
下载PDF
A self-adaptive stochastic resonance system design and study in chaotic interference
20
作者 鲁康 王辅忠 +1 位作者 张光璐 付卫红 《Chinese Physics B》 SCIE EI CAS CSCD 2013年第12期38-42,共5页
The us of stochastic resonance (SR) can effectively achieve the detection of weak signal in white noise and colored noise. However, SR in chaotic interference is seldom involved. In view of the requirements for the ... The us of stochastic resonance (SR) can effectively achieve the detection of weak signal in white noise and colored noise. However, SR in chaotic interference is seldom involved. In view of the requirements for the detection of weak signal in the actual project and the relationship between the signal, chaotic interference, and nonlinear system in the bistable system, a self-adaptive SR system based on genetic algorithm is designed in this paper. It regards the output signal-to-noise ratio (SNR) as a fitness function and the system parameters are jointly encoded to gain optimal bistable system parameters, then the input signal is processed in the SR system with the optimal system parameters. Experimental results show that the system can keep the best state of SR under the condition of low input SNR, which ensures the effective detection and process of weak signal in low input SNR. 展开更多
关键词 chaotic interference self-adaptive genetic algorithm optimal SR
下载PDF
上一页 1 2 45 下一页 到第
使用帮助 返回顶部