منابع مشابه
GMDH: An R Package for Short Term Forecasting via GMDH-Type Neural Network Algorithms
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...
متن کاملA GMDH-Based Traffic Flow Forecasting Model
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...
متن کاملGMDH-based networks for intelligent intrusion detection
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...
متن کاملNeural Network Training Using a GMDH Type Algorithm
Authors have developed a Group Method of Data Handling (GMDH) type algorithm for designing multilayered neural networks. The algorithm is general enough that it will accept any number of inputs and any sized training set. Each neuron of the resulting network is a function of two of the inputs to the layer. The equation for each of the neurons is a quadratic polynomial. Several forms of the equa...
متن کاملUsing Gmdh for Modeling Economical Indices of Mine Opening
Dependency of explicit costs index of mining opening on its parameters is modeled. In addition, the problem of structural identification is solved. Models enumeration is realized with the help of group methods of data handling (GMDH). Least-squares and least-modules methods are used for evaluating model parameters. The quality of resulting models is evaluated by the following criteria: (a) rema...
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ژورنال
عنوان ژورنال: Journal of Japan Society for Fuzzy Theory and Systems
سال: 1995
ISSN: 0915-647X,2432-9932
DOI: 10.3156/jfuzzy.7.2_270