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...

Construction of a system for measuring the brain activity (electroencephalogram (EEG)) and recognising thinking patterns comprises significant challenges, in addition to the noise and distortion present in any measuring technique. One of the most major applications of measuring and understanding EGG is the brain-computer interface (BCI) technology. In this paper, ANNs (feedforward back-prop and...

Vortex finder is a key part of cyclone separator. In the present study, multi-objective optimization of vortex finder is performed at three steps. At the first step, collection efficiency (η) and the pressure drop (∆p) in a set of cyclones with different vortex finder shape are numerically investigated using CFD techniques. Two meta-models based on the evolved group method of data handling (GMD...

Transition Initiation Sites (TIS) prediction is a challenging problem in computational biology. In the literature TIS is predicted using various machine learning techniques such as Neural Network (NN), Support Vector Machine, etc. We have applied Principal Component Analysis (PCA) to remove highly correlated features which improves the performance in terms of time and accuracy. In this paper we...

Abstract Machine learning (ML) has been recognized as a feasible and reliable technique for the modeling of multi-parametric datasets. In real applications, there are different relationships with various complexities between sets inputs their corresponding outputs. As result, models have developed levels complexity in input–output relationships. The group method data handling (GMDH) employs fam...

Network intrusion detection has been an area of rapid advancement in recent times. Similar advances in the field of intelligent computing have led to the introduction of several classification techniques for accurately identifying and differentiating network traffic into normal and anomalous. Group Method for Data Handling (GMDH) is one such supervised inductive learning approach for the synthe...

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...