nowadays, due to increasing the complexity of ic engines, calibration task becomes more severe and the need to use surrogate models for investigating of the engine behavior arises. accordingly, many black box modeling approaches have been used in this context among which network based models are of the most powerful approaches thanks to their flexible structures. in this paper four network base...

A novel approach is presented in this article for obtaining inverse mapping of thermodynamically Pareto-optimized ideal turbojet engines using group method of data handling (GMDH)-type neural networks and evolutionary algorithms (EAs). EAs are used in two different aspects. Firstly, multi-objective EAs (non–dominated sorting genetic algorithm-II) with a new diversity preserving mechanism are us...

Accurate forecasting of electricity load is one of the most important issues in the electricity industry. It is essential part of an efficient power system planning and operation. Due to the limited generic structure of conventional group method of data handling (GMDH) network (quadratic twovariable polynomial), it tends to produce an exceedingly complex network when it comes to highly nonlinea...

Abstract In this study, modeling of discharge was performed in compound open channels with non-prismatic floodplains (CCNPF) using soft computation models including multivariate adaptive regression splines (MARS) and group method data handling (GMDH), then their results were compared the multilayer perceptron neural networks (MLPNN). addition to total discharge, separation between floodplain ma...

Justyna PATALAS_MALISZEWSKA, Tadeusz KRUPA THE MULTICRITERIA SELECTION METHODOLOGY OF THE DECISION SUPPORT SYSTEM Abstract: An issue of building a tool orientated to the support of selection process of decision support system (DSS) for the sector of small and medium enterprises is presented in the article. A group method of data handling (GMDH) whose application allows to objectives a search pr...

Abstract In this research, water's surface elevation in compound channels with converging and diverging floodplains using soft computing models including the Multi-Layer Perceptron Neural Network (MLPNN), Group Method of Data Handling (GMDH), Neuro-Fuzzy (NF-GMDH) Support Vector Machine (SVM) was modeled predicted. For purpose, laboratory data published field were used. Parameters convergence a...