Geographically distributed and time-phased ecological and socio-economical indices are treated as source data for the analysis, carried out for taking reasoned management decision. Analysis complexity, related to multi-dimensional data is overcome thanks to using group methods of data handling (GMDH). This work shows the results of Ukraine's regions cluster analysis by the totality of ecologica...

Review Abstract: At present, GMDH algorithms give us the only way to get accurate identification and forecasts of different complex processes in the case of noised and short input sampling. In distinction to neural networks, the results are explicit mathematical models, obtained in a relative short time. For ill-defined objects with very big noises better results should be obtained by analogues...

Dependency of explicit costs index of mining opening on its parameters is modeled. In addition, the problem of structural identification is solved. Models enumeration is realized with the help of group methods of data handling (GMDH). Least-squares and least-modules methods are used for evaluating model parameters. The quality of resulting models is evaluated by the following criteria: (a) rema...

Residential sector is one of the energy-consuming districts countries that causes CO2 emission in large extent. In this regard, must be considered energy policy making related to reduction and other greenhouse gases. present work, residential three countries, including Indonesia, Thailand, Vietnam Southeast Asia, are discussed modeled by employing Group Method Data Handling (GMDH) Multilayer Pe...

This study comprises developing a more appropriate hybrid wavelet-modified GMDH model for forecasting the monthly crude palm oil (CPO) price of Malaysia. In proposed model, complex data CPO is decomposed into different sub series using discrete wavelet transform (DWT) and then it has been linked with modified model. Sigmoid, radial basis, tangent polynomial functions are selected as transfer in...