The Formation of Migrant Networks This paper provides the first direct evidence on the determinants of link formation among immigrants in the host society. We use a purposely-designed survey on a representative sample of Sri Lankan immigrants living in Milan to study how migrants form social links among them and the extent to which this network provides them with material support along three di...

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...

Neural networks (NN) are a relatively new option to model growth in animal production systems. One self-organizing submodel of artificial NN is the group method of data handling (GMDH)-type NN. The use of such self-organizing networks has led to successful application of the GMDH algorithm over a broad range of areas in engineering, science, and economics. The present study aimed to apply the G...

forecasting of macroeconomic variables has specific importance in economic topics. indeed, different models are invented to forecast variables to help economic policy makers in adopting appropriate monetary and fiscal policies. in this paper, the performance of integrated model of input-output (io) and neural network is investigated in forecasting final demand and total production and the resul...

In this paper, we propose novel recurrent architectures for Genetic Programming (GP) and Group Method of Data Handling (GMDH) to predict software reliability. The effectiveness of the models is compared with that of well-known machine learning techniques viz. Multiple Linear Regression (MLR), Multivariate Adaptive Regression Splines (MARS), Backpropagation Neural Network (BPNN), Counter Propaga...

In this paper, the forecasting problem of share prices at New York Stock Exchange (NYSE) was considered and investigated. For its solution alternative methods computational intelligence were suggested investigated: LSTM networks, GRU, simple recurrent neural networks (RNN) Group Method Data Handling (GMDH). The experimental investigations intelligent for CISCO carried out efficiency estimated c...

Agile software development is now accepted as a superior alternative to conventional methods of software development, because of its inherent benefits like iterative development, rapid delivery and reduced risk. Hence, the industry must be able to efficiently estimate the effort necessary to develop projects using agile methodology. For this, different techniques like expert opinion, analogy, d...

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...

We construct an arti cial neural network to act as a system of leading indicators. We focus on radial basis functions as the architecture and forward selection as the method for determining the number of basis functions in the network. A brief review is given of the advantages of this as a strategy. Using common heuristics to determine scaling, radii and centre population, we nd that the result...

An Artificial Neural Network is a flexible mathematical structure which is capable of identifying complex nonlinear relationships between input and output data sets. Such Neural Networks have been characterized by passive neurons that are not able to select and estimate their own inputs. In a new approach, which corresponds in a better way to the actions of human nervous system, the connections...