Agile Software development has become famous in industries and replacing the traditional methods of software development. A correct estimation of effort in this concept still remains an argument in industries. Thus, the industry must be able to estimate the effort necessary for software development using agile methodology. For estimating effort different types of neural-networks Probabilistic N...

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...

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 ...

The rest of this paper is organized as follows. Section 2 describes traditional System Identification and introduces the use of Particle Swarm Optimization (PSO) for determining the coefficients of a simple autoregressive moving average model (SwARMA). Section 3 explains Particle Swarm Optimization. Section 4 describes the results of using PSO for determining the ARMA model parameter (SwARMA) f...

Many organelle enzymes coded for by nuclear genes have N-terminal sequences, which directs them into the organelle (precursor) and are removed upon import (mature). The experiments described below characterize the differences between the precursor and mature forms of watermelon glyoxysomal malate dehydrogenase. Using recombinant protein methods, the precursor (p-gMDH) and mature (gMDH) forms we...

In this paper we show how the performance of the basic algorithm of the Group Method of Data Handling (GMDH) can be improved using Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The new improved GMDH is then used to predict currency exchange rates: the US Dollar to the Euros. The performance of the hybrid GMDHs are compared with that of the conventional GMDH. Two performance mea...

in this work, a hybrid gmdh–neural network model was developed in order to predict the moisture content of papaya slices during hot air drying in a cabinet dryer. for this purpose, parameters including drying time, slices thickness and drying temperature were considered as the inputs and the amount of moisture ratio (mr) was estimated as the output. exactly 50% of the data points were used for ...

Group Method of Data Handling (GMDH)-type neural network algorithms are the heuristic self organization method for the modelling of complex systems. GMDH algorithms are utilized for a variety of purposes, examples include identification of physical laws, the extrapolation of physical fields, pattern recognition, clustering, the approximation of multidimensional processes, forecasting without mo...

doi:10.1111/j.1742-4658.2004.04475.x Many organelle enzymes coded for by nuclear genes have N-terminal sequences, which directs them into the organelle (precursor) and are removed upon import (mature). The experiments described below characterize the differences between the precursor and mature forms of watermelon glyoxysomal malate dehydrogenase. Using recombinant protein methods, the precurso...