Data Mining (DM) is a relatively recent technology that is employed in inferring useful knowledge that can be put to use from a vast amount of data. This paper presents the data mining processes applied to the seemingly chaotic behavior of stock markets which could be well represented using the enhance GMDH, and we compared its results with published results using neural network, TS fuzzy syste...

optimization techniques can be efficiently utilized to achieve an optimal shape for arch dams. this optimal design can consider the conditions of the economy and safety simultaneously. the main aim is to present an applicable and practical model and suggest an algorithm for optimization of concrete arch dams to enhance their seismic performance. to achieve this purpose, a preliminary optimizati...

Modeling and multi-objective optimization of centrifugal pumps is performed at three steps. At the first step, η and NPSHr in a set of centrifugal pump are numerically investigated using commercial software NUMECA. Two metamodels based on the evolved group method of data handling (GMDH) type neural networks are obtained, at the second step, for modeling of η and NPSHr with respect to geometrica...

Virtual machines (VMs) dynamic consolidation is effective to improve the utilization of resources and energy efficiency in cloud environment. However, the obligation of providing high quality of service to customers leads to the necessity in dealing with the energy performance trade-off, as aggressive consolidation may lead to performance degradation. Current solutions to the problem of host lo...

Accurate estimation of carbon and water fluxes of forest ecosystems is of particular importance for addressing the problems originating from global environmental change, and providing helpful information about carbon and water content for analyzing and diagnosing past and future climate change. The main focus of the current work was to investigate the feasibility of four comparatively new metho...

Prediction of building energy consumption plays an important role in conservation, management, and planning. Continuously improving enhancing the performance forecasting models is key to ensuring sustainability systems. In this connection, current paper presented a new improved hybrid model machine learning application for cooling load (CL) heating (HL) residential buildings after studying anal...

Proper performance of water distribution networks (WDNs) plays a vital role in customer satisfaction. The aim this study is to conduct sensitivity analysis evaluate the behavior WDNs analyzed by pressure-driven (PDA) approach and classification technique using an appropriate artificial neural network, namely Group Method Data Handling (GMDH). For purpose, divided into four distinct steps. In fi...

Wave forecasting up to 168 h (one-week) ahead is crucial the operational management of shipping and construction in marine work site. The present study proposes a method areal-time One-week Forecast Nearshore Waves (OWFNW) at 13 stations on Japanese coast. For each station, two Group Method Data Handling (GMDH) based wave prediction models for height period are developed transform global data i...