Welcome![Sign In][Sign Up]
Location:
Search - estimation and genetic algorithm

Search list

[Other resourcemathmodel

Description: 这是一个好的建模学习资料,赶快下载吧, 数学建模十大算法 ( 包含:蒙特卡罗算法、数据拟合、参数估计、 插值等数据处理算法、线性规划、整数规划、多元规划、二次规划等规划类问题、 图论算法、动态规划、回溯搜索、分治算法、分支定界等计算机算法、 最优化理论的三大非经典算法:模拟退火法、神经网络、遗传算法、 网格算法和穷举法、一些连续离散化方法、数值分析算法、图象处理算法)-This a good model to study the information, download it quickly, mathematical modeling algorithm 10 (includes : Monte Carlo algorithm, data fitting, parameter estimation, interpolation of data-processing algorithms, linear programming, integer programming, diversity planning, Quadratic Programming category of zoning, graph-theoretical algorithms, dynamic programming, retroactive search, the partition algorithm, branch-and-bound algorithm computer, most optimization theory of the three non-classical algorithm : simulated annealing, neural networks, genetic algorithms, mesh algorithms and exhaustive, some consecutive discrete method, numerical analysis algorithms, image processing algorithm)
Platform: | Size: 5929399 | Author: zhxj | Hits:

[Other resourceGAnonlinearEstimation

Description: 非线性参数估计的遗传算法解。《非线性模型参数估计理论与方法》,武汉大学出版社。所列出的代码为该书算例的具体实现。-nonlinear parameter estimation of the genetic algorithm solution. "Nonlinear model parameter estimation theory and method", Wuhan University Press. The code shown examples of the book is a concrete realization.
Platform: | Size: 11966 | Author: asdf | Hits:

[AI-NN-PRmathmodel

Description: 这是一个好的建模学习资料,赶快下载吧, 数学建模十大算法 ( 包含:蒙特卡罗算法、数据拟合、参数估计、 插值等数据处理算法、线性规划、整数规划、多元规划、二次规划等规划类问题、 图论算法、动态规划、回溯搜索、分治算法、分支定界等计算机算法、 最优化理论的三大非经典算法:模拟退火法、神经网络、遗传算法、 网格算法和穷举法、一些连续离散化方法、数值分析算法、图象处理算法)-This a good model to study the information, download it quickly, mathematical modeling algorithm 10 (includes : Monte Carlo algorithm, data fitting, parameter estimation, interpolation of data-processing algorithms, linear programming, integer programming, diversity planning, Quadratic Programming category of zoning, graph-theoretical algorithms, dynamic programming, retroactive search, the partition algorithm, branch-and-bound algorithm computer, most optimization theory of the three non-classical algorithm : simulated annealing, neural networks, genetic algorithms, mesh algorithms and exhaustive, some consecutive discrete method, numerical analysis algorithms, image processing algorithm)
Platform: | Size: 5928960 | Author: zhxj | Hits:

[AI-NN-PRGAnonlinearEstimation

Description: 非线性参数估计的遗传算法解。《非线性模型参数估计理论与方法》,武汉大学出版社。所列出的代码为该书算例的具体实现。-nonlinear parameter estimation of the genetic algorithm solution. "Nonlinear model parameter estimation theory and method", Wuhan University Press. The code shown examples of the book is a concrete realization.
Platform: | Size: 1720320 | Author: asdf | Hits:

[AI-NN-PRIntEDA

Description: UMDA. a kind of estimation of distribution algorithm , which is the improvement of genetic algorithm-UMDA. A kind of estimation of distribution algorithm, which is the improvement of genetic algorithm
Platform: | Size: 47104 | Author: sunxiaodian | Hits:

[Windows DevelopHOS_MIMO

Description: This package contains the MATLAB code for the algorithm proposed in the following papers. The file "mimo_main.m" is the implementation of the algorithm in the papers. The goal of this Matlab script is to identify a MIMO system with white inputs based on the second and higher-order statistics of the outputs only. This code will plot the blind estimation results using figures.-This package contains the MATLAB code for t he algorithm proposed in the following papers. The file "mimo_main.m" is the implementation o f the algorithm in the papers. The goal of this Ma tlab script is to identify a MIMO system with whi te inputs based on the second and higher-order's tatistics of the outputs only. This code will pl ot the blind estimation results using figures.
Platform: | Size: 23552 | Author: 刘美 | Hits:

[Other20090918

Description: 在实时平台上,高斯混合模型(GMM)具有计算有效性和易于实现的优点。最大似然规则中,模型参数不 断更新,但由于爬山特征,任意的原始模型参数估计通常将导致局部最优 遗传算法(GA)适于求解复杂组合优化问 题及非线性函数优化。提出了基于说话人识别的可以解决GMM局部最优问题的GMM/GA新算法,实验结果表明, 提出的GMM/GA新算法比纯粹的GMM算法能获得更优的效果。 - In real-time platform, the Gaussian mixture model (GMM) with the calculation of the effectiveness and easy to realize benefits. Maximum likelihood rule, the model parameters are not Broken updates, but due to climbing features, any of the original model parameter estimation will usually result in local optimum genetic algorithm (GA) is suitable for solving complex combinatorial optimization question Title and non-linear function optimization. Proposed speaker recognition based on GMM can solve the problem of local optimal GMM/GA new algorithm, experimental results show that the Proposed GMM/GA new algorithm than purely GMM algorithm can get better results.
Platform: | Size: 4448256 | Author: 于高 | Hits:

[AI-NN-PRAutomatedNegotiatioDecisionModelasedonMachineLearn

Description: 模型利用协商历史中隐含的信息自动对数据进行标注以形成训练样本,用最小二乘支持向量回 归机学习此样本得到对手效用函数的估计,然后结合自己和对手的效用函数构成一个约束优化问题,用遗传算法求 解此优化问题,得到的最优解就是己方的反建议.实验结果表明,在信息保密和没有先验知识的条件下,此模型仍然 表现出较高的效率和效用-The proposed model labels the negotiation history data automatically by making full use of the implicit information in negotiation history.Then,the labeled data become the training samples of least-squares support vector machine that outputs the estimation of opponent’s utility function.After that,the self s utility function and the estimation of opponent’s utility function constitute a constraint optimization problem that will be further figured out by genetic algorithm.The optimal solution is the counter-ofer of onesel~ Experimental results show that the proposed model is efective and efi cient in environments where information is private and the prior knowledge is not available.
Platform: | Size: 514048 | Author: 11 | Hits:

[matlabmatlabxuexi

Description: 这是一个好的建模学习资料,赶快下载吧, 数学建模十大算法 ( 包含:蒙特卡罗算法、数据拟合、参数估计、 插值等数据处理算法、线性规划、整数规划、多元规划、二次规划等规划类问题、 图论算法、动态规划、回溯搜索、分治算法、分支定界等计算机算法、 最优化理论的三大非经典算法:模拟退火法、神经网络、遗传算法、 网格算法和穷举法、一些连续离散化方法、数值分析算法、图象处理算法)-This is a good model to study the information, download it quickly, mathematical modeling algorithm 10 (includes: Monte Carlo algorithm, data fitting, parameter estimation, interpolation of data processing algorithms, linear programming, integer programming, diversity planning, Quadratic Programming Programming category of zoning, graph algorithms, dynamic programming, backtracking search, divide and conquer algorithm, branch and bound algorithm computer, optimization theory of the three non-classical algorithm: simulated annealing, neural networks, genetic algorithms, network lattice algorithms and exhaustive, some consecutive discrete method, numerical analysis algorithms, image processing algorithm)
Platform: | Size: 4994048 | Author: 高雄飞 | Hits:

[CA auth1-s2.0-S0952197602000878-main

Description: The paper presents an in situ parameter estimation method to determine the equivalent circuit parameters of the three-winding transformer (TWT). The suggested method also estimates geometrically a complex parameter that is mutual leakage between secondary and tertiary windings, which would be useful in transient studies. Beside the saturation effect of the transformer is taken into account by estimating a highly nonlinear parameter that is magnetizing circuit reactance. Different search based optimization tools are applied for parameter estimation among which the results obtained using genetic algorithm is found to be encouraging. Load test data at one particular operating point namely supply voltage, load currents, input power, and load impedance is suffi cient to estimate the parameters.
Platform: | Size: 129024 | Author: fouzirock | Hits:

[Industry researchestimation-extended-Kalman-filter

Description: 针对感应电机扩展卡尔曼滤波器转速估计中难以取得卡尔曼滤波器系统噪声矩阵和测量噪声矩阵最优值的问题,提出了一种基于改进粒子群算法优化的扩展卡尔曼滤波器转速估计方法。算法通过融合遗传算法和粒子群算法的优点,采用可调整的算法模型对粒子群算法进行改进,将改进的粒子群算法对扩展卡尔曼滤波器中的系统噪声矩阵和测量噪声矩阵进行优化处理,将优化后的卡尔曼滤波器应用于感应电机转速估计。- Extended Kalman Filter for induction motor speed estimation problem is difficult to obtain a Kalman filter system noise matrix and the measurement noise matrix optimal value proposed speed estimation method based on improved particle swarm optimization of the extended Kalman filter. By virtue of the genetic algorithm and particle swarm optimization algorithm fusion algorithm using the adjustable model PSO improvements that will improve the PSO extended Kalman filter system noise matrix and the measurement noise matrix optimization process, the optimized Kalman filter is applied to the induction motor speed estimate.
Platform: | Size: 1201152 | Author: | Hits:

[Industry researchParticle Swarm Optimization of an Extended Kalman Filter for speed and rotor flux estimation of an induction motor drive

Description: A novel method based on a combination of the Extended Kalman Filter (EKF) with Particle Swarm Optimization (PSO) to estimate the speed and rotor flux of an induction motor driveis presented. The proposed method will be performed in two steps. As a first step, the covariance matrices of state noise and measurement noise will be optimized in an off-line manner by the PSO algorithm. As a second step, the optimal values of the above covariance matrices are injected in our speed-rotor flux estimation loop (on-line).Computer simulations of the speed and rotor-flux estimation have been performed in order to investigate the effectiveness of the proposed method. Simulations and comparison with genetic algorithms (GAs) show that the results are very encouraging and achieve good performances.
Platform: | Size: 665750 | Author: pudn0507@yahoo.fr | Hits:

[matlab基于遗传算法优化EKF算法的SOC估算

Description: 采用遗传算法对 EKF 中的系统噪声矩阵和测量矩阵的协方差进行在线优化,以实现在模型误差最小时对 SOC 进行在线估计(Genetic algorithm is used to optimize the covariance of system noise matrix and measurement matrix in EKF on-line, so as to realize the on-line estimation of SOC at the minimum model error)
Platform: | Size: 248832 | Author: 中国足球队 | Hits:

[matlabSOC Estimation Using Extended Kalman Filter, BRO, PSO, and GA

Description: The code helps to estimate the State of Charge (SOC ) by optimizing the battery parameters using Genetic Algorithm, Particle Swarm Optimization, and Battle Royal Optimization
Platform: | Size: 6660524 | Author: phdabhay | Hits:

CodeBus www.codebus.net