Search - matrix ga

Search - matrix ga - List

[matlab] matrix_gain DL : 0: 基于MATLAB的matrix_gain详解，主要解决的是matrix_gain的问题-Based on MATLAB-matrix_gain explain, the main problem lies in the question of matrix_gain
Update : 2025-02-19 Size : 2kb Publisher : wangwei
[Data structs] graph2M DL : 0: 程序首先给出边集数组中的元素类型、邻接矩阵类定义。其中，建立图的邻接矩阵CREATEMatrix函数的形参N为图的点数形参e为边数，rcw为结构体类型RCW的数组利用PRIM算法从定点V0出发求出用邻接矩阵GA表示的图的最小生成树，其边集存与数组CT中，PRIM算法对应的函数为PRIM。-First of all, given the procedures margination array element type, adjacency matrix class definition. Among them, the establishment of graph adjacency matrix CREATEMatrix function parameter N points for the map parameter e for the edge, rcw for the structure of the array type RCW use PRIM algorithm derived from the fixed point of departure V0 with adjacency matrix GA expressed Minimum Spanning Tree, and its margination CT in keeping with the array, PRIM algorithm corresponding function for the PRIM.
Update : 2025-02-19 Size : 3kb Publisher : sjw87522
[Windows Develop] initializega DL : 0: initializega creates a matrix of random numbers with a number of rows equal to the populationSize and a number columns equal to the number of rows in bounds plus 1 for the f(x) value which is found by applying the evalFN. This is used by the ga to create the population if it is not supplied. -initializega creates a matrix of random numbers with a number of rows equal to the populationSize and a number columns equal to the number of rows in bounds plus 1 for the f(x) value which is found by applying the evalFN. This is used by the ga to create the population if it is not supplied.
Update : 2025-02-19 Size : 2kb Publisher : Aron
[Software Engineering] TSPwith DL : 0: this the TSP problem with input GA algoritm that get input from matrix,i put test case too, you can use them-this is the TSP problem with input GA algoritm that get input from matrix,i put test case too, you can use them...
Update : 2025-02-19 Size : 294kb Publisher : Navid Yamini
[AI-NN-PR] 189-199 DL : 0: As the compact design of a muffler system within a constrained environment of a existing machine room becomes obligatory, it also becomes essential to maximize the acoustic performance of mufflers under space constraints. In this paper, the shape optimization of a double-chamber muffler with an extended tube is presented. The main characteristic of the solution methodology is the use of genetic algorithm (GA) as the optimizer. In the paper, the acoustic perfor- mance of sound transmission loss (STL) derived by transfer matrix is conjugated with the techniques of GA searching. A numerical case-As the compact design of a muffler system within a constrained environment of a existing machine room becomes obligatory, it also becomes essential to maximize the acoustic performance of mufflers under space constraints. In this paper, the shape optimization of a double-chamber muffler with an extended tube is presented. The main characteristic of the solution methodology is the use of genetic algorithm (GA) as the optimizer. In the paper, the acoustic perfor- mance of sound transmission loss (STL) derived by transfer matrix is conjugated with the techniques of GA searching. A numerical case
Update : 2025-02-19 Size : 443kb Publisher : payal
[MPI] GA DL : 0: 遗传算法的matlab程序，有详细的子函数，自适应求解多维矩阵参数，浮点型实数求解，程序明了易懂！-Genetic algorithm matlab program, detailed subfunctions adaptive solving multidimensional matrix parameters, floating point real numbers to solve the program is clear and easy to understand!
Update : 2025-02-19 Size : 7kb Publisher : andy
[matlab] Files DL : 1: I send a file that contains 7 source code and simulation in matlab. source codes contain GA and HGAPSO and PSO local&global.simulink files contain svpwm,matrix converter direct&improve.
Update : 2025-02-19 Size : 47kb Publisher : Mohsen Rezaie
[Software Engineering] weka DL : 0: tspData <- read.csv( D:\\weka\\hw\\TSP.csv , header = T, sep = , ) #tspData <- `colnames<-`(tspData,c(1:8)) D <- as.matrix(tspData) tourLength <- function(tour, distMatrix) { tour <- c(tour, tour[1]) route <- embed(tour, 2)[, 2:1] sum(distMatrix[route]) } tpsFitness <- function(tour, ...) 1/tourLength(tour, ...) GA.fit <- ga(type = permutation , fitness = tpsFitness, distMatrix = tspData, min = 1, max = 8, popSize = 10, maxiter = 500, run = 100, pmutation = 0.2, monitor = NULL) summary(GA.fit) -tspData <- read.csv( D:\\weka\\hw\\TSP.csv , header = T, sep = , ) #tspData <- `colnames<-`(tspData,c(1:8)) D <- as.matrix(tspData) tourLength <- function(tour, distMatrix) { tour <- c(tour, tour[1]) route <- embed(tour, 2)[, 2:1] sum(distMatrix[route]) } tpsFitness <- function(tour, ...) 1/tourLength(tour, ...) GA.fit <- ga(type = permutation , fitness = tpsFitness, distMatrix = tspData, min = 1, max = 8, popSize = 10, maxiter = 500, run = 100, pmutation = 0.2, monitor = NULL) summary(GA.fit)
Update : 2025-02-19 Size : 2kb Publisher : peipei
[Other] matlab-daima DL : 0: 包括：6机组系统的分布式梯度算法代码；基于GA的21节点无功优化；基于GA的二次型优化；matlab高级指令；依据matpower进行潮流计算中JJ矩阵的求解。-Comprising: a distributed gradient algorithm code 6 Unit System optimization based on GA 21 nodes reactive power quadratic optimization based on GA matlab advanced instruction matpower flow calculation based on the JJ matrix solver.
Update : 2025-02-19 Size : 9kb Publisher : 曹驰
[matlab] GA DL : 0: 线性规划，求最大值！使用矩阵的运算，求解多元一次函数的节！(Linear programming, the maximum value!The calculation of the matrix is used to solve the node of a multiple function.)
Update : 2025-02-19 Size : 4kb Publisher : 四书
[matlab] 雷达目标 DL : 0: 雷达目标分配，在可探测矩阵的约束下，利用简单的遗传算法，仅供参考(Radar target assignment, under the constraint of detectable matrix, makes use of simple genetic algorithm for reference only.)
Update : 2025-02-19 Size : 2kb Publisher : ES2157
[AI-NN-PR] BP神经网络python简单实现 DL : 0: 去掉神经元类，把功能合并入NetLayer类中，使用矩阵计算加快速度调整代码实现批量训练方法。优化程序中numpy库运算顺序，避免产生中间变量(Remove neuron classes, merge functions into NetLayer classes, and use matrix to calculate speed.)
Update : 2025-02-19 Size : 12kb Publisher : 朱朱521
[matlab] 基于遗传算法优化EKF算法的SOC估算 DL : 0: 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)
Update : 2025-02-19 Size : 243kb Publisher : 中国足球队