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[AI-NN-PR] gmdh DL : 0: 神经网络gmdh的详细程序，demo是主程序-Neural Networks gmdh detailed procedures, demo is the main program
Update : 2025-02-19 Size : 26kb Publisher : cloud
[AI-NN-PR] knowledgeminer DL : 0: gmdh神经网络专用软件knowledgeminer5.0，注意要用中介软件executor才能在windows下使用-gmdh neural network-specific software knowledgeminer5.0, note that the software executor to use an intermediary to use in windows
Update : 2025-02-19 Size : 5mb Publisher : cloud
[matlab] gmdhbuild DL : 0: GMDH的MATLAB源代码，是主程序，也就是gmdhbuild.文件。与之配套的测试文件gmdhtest.m、输出误差gmdhpredice.m会接着发出。-GMDH The MATLAB source code, is the main program, which is gmdhbuild. File. Accompanying test file gmdhtest.m, output error will be followed by a gmdhpredice.m.
Update : 2025-02-19 Size : 12kb Publisher : songhuaixiang
[matlab] gmdhpredict DL : 0: GMDH的MATLAB源代码，是主程序，也就是gmdhbuild.文件。与之配套的测试文件gmdhtest.m、输出误差gmdhpredice.m会接着发出。-GMDH The MATLAB source code, is the main program, which is gmdhbuild. File. Accompanying test file gmdhtest.m, output error will be followed by a gmdhpredice.m.
Update : 2025-02-19 Size : 1kb Publisher : songhuaixiang
[matlab] gmdhtest DL : 0: GMDH的MATLAB源代码，是主程序，也就是gmdhbuild.文件。与之配套的测试文件gmdhtest.m、输出误差gmdhpredice.m会接着发出。-GMDH The MATLAB source code, is the main program, which is gmdhbuild. File. Accompanying test file gmdhtest.m, output error will be followed by a gmdhpredice.m.
Update : 2025-02-19 Size : 1kb Publisher : songhuaixiang
[Mathimatics-Numerical algorithms] VariReg DL : 0: VariReg是一款免费的GMDH软件，解压后记事本上有开发该代码的网址，里面还有丰富的MATLAB编写的GMDH原程序。非常好用。-VariReg is a free GMDH software, decompression after Notepad to develop the code on the URL, there is also a wealth of MATLAB programs written in the original GMDH. Is very easy to use.
Update : 2025-02-19 Size : 3.26mb Publisher : songhuaixiang
[matlab] GMDH-Shell-1.3.setup DL : 0: GMDH Shell 1.3 setup
Update : 2025-02-19 Size : 4.5mb Publisher : 宋怀翔
[ADO-ODBC] gmdh2 DL : 0: 数据分组处理算法GMDH源代码是自组织数据挖掘的核心算法，具有很强的泛化能力，相比回归分析法可以处理小样本数据-GMDH packet processing algorithms source code is the core of self-organizing data mining algorithm, which has strong generalization ability, compared with regression analysis can deal with small samples
Update : 2025-02-19 Size : 2kb Publisher : 张瑛
[matlab] gmdh DL : 0: this is a matlab implementation for gmdh network
Update : 2025-02-19 Size : 11kb Publisher : maryamhasan
[matlab] GMDH DL : 0: this simple sample of Group Method of Data Handling(GMDH) neural network main file: GMDH.m-this is simple sample of Group Method of Data Handling(GMDH) neural network main file: GMDH.m
Update : 2025-02-19 Size : 23kb Publisher : amin
[matlab] gmdhdemo DL : 0: gmdh神经网络的详细程序，demo是主程序源码。-gmdh detailed procedures for neural networks, demo is the main source.
Update : 2025-02-19 Size : 27kb Publisher : 认可
[matlab] maGMDH DL : 1: 采用MATLAB编写的GMDH软件，里面有三个.m程序，分别为训练、误差检测、预测输出。很好用。-GMDH using software written in MATLAB, which has three. M steps in the training, error detection, prediction output. Good use.
Update : 2025-02-19 Size : 14kb Publisher : 清醒
[matlab] GMDH DL : 0: gmdH的MATLAB源代码，是主程序，也就是gmdhbuild.文件。与之配套的测试文件gmdhtest.m、输出误差gmdhpredice.m会接着发出-gmdH the MATLAB source code is the main program, which is gmdhbuild. file. The related test files gmdhtest.m, will then send the output error gmdhpredice.m
Update : 2025-02-19 Size : 2kb Publisher : 李增光
[matlab] gmdh_example DL : 0: GMDH_main为GMDH主函数； variable_Combin为输入层初始变量选为x1,x1^2,x1*x2,x2^2,x2时的输入变量矩阵值 variable_select计算X_train训练输入数据,Y_train训练输出数据,X_test测试输入数据,Y_test测试输出数据 Combin为求变量的两两组合 Sym_Combin为求符号变量的两两组合 PE_AIC求每层各神经元的参数估计W，及训练数据在参数估计后估计的输出out_train，测试数据在参数估计后的估计输出out_test，还有与实际比较的误差平方和PESS，以及准则值AIC sym_representation求最终的输入输出符号表达式 Criterion_value求准则值-GMDH_main main function for the GMDH variable_Combin initial variables chosen for the input layer, x1, x1 ^ 2, x1* x2, x2 ^ 2, x2 the value of the input variable matrix calculation X_train variable_select training input data, Y_train training output data, X_test test input data, Y_test for the sake of the test output data Combin pairwise combination of variables for the sake of symbolic variables Sym_Combin pairwise combinations PE_AIC neurons find each parameter estimation of the W, and after the training data is estimated in the estimation of output out_train, test data After the parameter estimates of the output estimated out_test, also compared with the actual sum of squared errors PESS, as well as the final criterion value AIC sym_representation seek the input and output values of symbolic expressions Criterion_value find criteria
Update : 2025-02-19 Size : 11kb Publisher : 李增光
[AI-NN-PR] Test DL : 0: GMDH _ Nureal Network _ Matlab code -GMDH _ Nureal Network _ Matlab code
Update : 2025-02-19 Size : 1kb Publisher : mehdis
[matlab] GMDH-(Function-Approximation) DL : 0: A project for function approximation by GMDH neural network (with GUI).
Update : 2025-02-19 Size : 12kb Publisher : hamed
[matlab] Ensemble-learning-based-on-GMDH DL : 0: 基于自组织数据挖掘的多分类器集成选择的程序-Multiple classifiers ensemble selection based on GMDH
Update : 2025-02-19 Size : 1.69mb Publisher : 肖进
[AI-NN-PR] A-hybrid-least-squares DL : 0: A hybrid least squares support vector machines and GMDH approach for river ﬂ ow forecasting-This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input vari- ables for LSSVM model and the LSSVM model which works as time series forecasting. 5 In this study the application of GLSSVM for monthly river ﬂ ow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artiﬁ cial neural network (ANN) models, Autoregres- sive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river ﬂ ow discharge. The standard statistical, the 10 root mean square error (RMSE) and coe ﬃ cient of correlation (R) are employed to eval- uate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to mo
Update : 2025-02-19 Size : 1.4mb Publisher :
[matlab] GMDH DL : 0: gmdh代码训练方法 —————————————— 1.将数据集分为训练集和测试集。 2.建立输入层 3.建立所有符合5楼条件的神经元（只考虑“攻”和“受”的关系，不考虑具体的权值）。如果前面几层共有N个神经元，那么我们就需要建立N(N-1)/2个神经元。 4.用最小二乘法确定权值 5.计算每一个神经元在测试集上的表现。 6.选取表现最好的K个神经元放在后面一层。（K可以自己选择） 7.重复3,直到网络的性能足够好，或者网络开始过拟合。(GMDH codeTraining methods -------------- 1. Divide the data set into training sets and test sets. 2. Create an input layer 3. Establish all neurons that meet the conditions of the 5th floor (only consider the "attack" and "by" the relationship, regardless of the specific weight). If there are N neurons in the first few layers, then we need to establish N (N-1) / 2 neurons. 4. Determine the weight using the least squares method 5. Calculate the performance of each neuron on the test set. 6. Select the best performing K neurons on the back. (K can choose their own) 7. Repeat 3, until the network performance is good enough, or the network began to fit.)
Update : 2025-02-19 Size : 3kb Publisher : adch
[Other] GMDH DL : 0: By means of gmdh algorithm a model can be represented as set of neurons in which different pairs of them in each layer are connected through a quadratic polynomial and thus produce new neurons in the next layer. Such representation can be used in modelling to map inputs to outputs. The formal defini.
Update : 2025-02-19 Size : 4.71mb Publisher : FADAIE

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