In this paper, the effect of super plasticizer amount, water/cement ratio, the cement, silica fume and steel micro fiber content is studied on the ultimate compressive strength of new generation of Ultra High Strength Concrete (UHSC).Known as Reactive Powder Concrete (RPC) and also have used two non-linear functions; Genetic Programming (GP) and Group Method of Data Handling (GMDH), which are t...

Recently, a lot of attention has been devoted to advanced techniques of system modeling. PNN(polynomial neural network) is a GMDH-type algorithm (Group Method of Data Handling) which is one of the useful method for modeling nonlinear systems but PNN performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, w...

stable. The main results are: data normalization is fundamental to obtain better precision, the larger the number of data points, the lesser the error, the error decreases with the decreasing of noise level. The next step is to develop an Ipen nuclear research reactor model and apply the GMDH methodology to predict the reactor variables. This work is a part of a Monitoring and Diagnosis System ...

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...

This paper presents a constructive approach to neural network modeling of polynomial harmonic functions. This is an approach to growing higher-order networks like these build by the multilayer GMDH algorithm using activation polynomials. Two contributions for enhancement of the neural network learning are offered: (1) extending the expressive power of the network representation with another com...

The current study proposes a two-step approach for pore facies characterization in the carbonate reservoirs with an example from the Kangan and Dalanformations in the South Pars gas field. In the first step, pore facies were determined based on Mercury Injection Capillary Pressure (MICP) data incorporation with the Hierarchical Clustering Analysis (HCA) method. In the next step, polynomial meta...

In this study, it was aimed to develop an accurate forecasting model for the monthly electricity demand of Turkey in medium-term. For purpose, Group Method Data Handling (GMDH)-type Neural Network (NN) approach used structure a nonlinear time-series based model. A large dataset containing considered period 2003-2018. The developed tested 2019/01-2019/11 order determine generalization ability te...

Traffic flow forecasting, the core element of intelligent transportation system, plays an important role in traffic information services and traffic guidance. Since neural network prediction needs plenty of training samples, it cannot guarantee the real-timeness of traffic flow forecasting. In this paper, a GMDH network was constructed by self-organization, and the network was applied to traffi...

The isolation and sequence of a cDNA clone encoding the complete glyoxysomal malate dehydrogenase [gMDH; (S)-malate:NAD+ oxidoreductase, EC 1.1.1.37] of watermelon cotyledons are presented. Partial cDNA clones were synthesized in a three part strategy, taking advantage of the polymerase chain reaction technology with oligonucleotides based on directly determined amino acid sequences. Subsequent...

We have studied the significance of the N-terminal presequence of watermelon (Citrullus vulgaris) glyoxysomal malate dehydrogenase [gMDH; (S)-malate:NAD+ oxidoreductase; EC 1.1.1.37] in microbody targeting. The yeast Hansenula polymorpha was used as heterologous host for the in vivo expression of various genetically altered watermelon MDH genes, whose protein products were localized by immunocy...