Gruszczyński, Stanisław
Loading...
Email Address
Employee
nieaktywny
Alternative name
Discipline
inżynieria środowiska, górnictwo i energetyka
Author Profiles
Systemy AGH
4 results
Search Results
Now showing 1 - 4 of 4
Item type:Article, Access status: Open Access , Zastosowanie algorytmów interpolacji i sztucznych sieci neuronowych do wyznaczania charakterystyki zawartości chromu w glebach(Wydawnictwa AGH, 2005) Gruszczyński, Stanisław ; Urbański, KrzysztofVarious ways of approach, to determine the horizontal distribution trend (tendency) of Chromium (Cr) in soil, where is high pollution by this element are analysed. Polynominal regression algorithms (I, II, III degree polynominals), interpolation algorithms (TIN, Kriging, RST), and also artificial neural networks (MLP, CANFIS, RBF, GRNN, PNN, MDN) are applied. Data from field experiments, carried out in the area of Chemical Plant in Alwernia were used. The differences between several ways of approach are presented in a graphical form, and also in some remainders distribution statistics. The soil pollution spatial distribution examinations lead to following conclusion, that in the first place is the information precision determination, and also the limit of error, through the pollution evaluation acceptance, whereas in the second place is the indication or standing out the regularity connected with the imission effect mechanism. It seems that the chromium concentration in soils variation, noticed even on short distances, makes it difficult the acceptance of interpolation method, as a method of contamination distribution evaluation. On the other hand the considerable nonlinearity makes difficult the acceptance of regression model. In these circumstances, the possibility which is worth consideration, is the modelling with the application of neuron networks, that is also hybrid solution application (for instance MDN), which gives the possibility of Cr concentration in soils variation deeper analysis.Item type:Article, Access status: Open Access , Geoinformatyczne narzędzia w badaniu gleb(Wydawnictwa AGH, 2006) Gruszczyński, StanisławPresent requirements in terms of the content and purposes of documenting soils, unlike traditional soil maps, differentiate three significant circumstances: the possibility of the application of digital techniques of collecting and analysing spatial data, the increase of the role of environmental criteria for the assessment of the quality of grounds, compared to dominating earlier indexes of their values viewed only in the aspect of the needs of agriculture and forestry, and supplementing the list of the goals of documentation with the prediction of the changes in soils influenced by different factors. All these circumstances cause changes in the ways of the interpretation and understanding of spatial soil data. In methodological sense, the tools of the new approach are: including the fuzzy inference as the proper for the procedures of the classification of soils and visualization of the ranges of their units, the application of knowledge discovery in databases (KDD) and data mining (DM) in the modelling of morphologic and spatial relations useful in predicting changes in soils in new environmental conditions. Nowadays, systems of spatial information, equipped with KDD algorithms make - in the relation to the documentation of soils in technologically advanced countries - systems of the extraction of knowledge and information, allowing environmental risk assessment related to the propagation of pollutants and complex studies of their transformations under the influence of multidirectional anthropogenic influence. In the paper the application of KDD algorithms was presented in the assessment of present and forecasted state of soils.Item type:Article, Access status: Open Access , Przydatność różnych typów sieci neuronowych w klasyfikacji gleb(Wydawnictwa AGH, 2006) Gruszczyński, StanisławThe application of three neural networks algorithm in task soils classification, on the basis of features obtained from analog cartographic documentation, is presented. The MLP (Multi-Layer Perceptron) type net and PNN (Probabilistic Neural Network) give the best classification results among examined algorithms. The PNN and SOM (Self-Organizing Map) combination of net operational results gives more deep classification relations within sphere this study, based among others on fuzzy relationships visualization between complexes in analyzed area.Item type:Article, Access status: Open Access , Ocena i prognozowanie stanu gleb na potrzeby planów i programów(Wydawnictwa AGH, 2006) Gruszczyński, StanisławThe environmental assessment of effects of the plans and programs realization is relatively novelty in Polish Environmental Impast Assessment practice. In the next few years one might await a considerable increase of demand of this kind of studies. The evaluation of the present state and also the prognosis of future soils states needs methodological basis, including the applied procedures settling a reliable description of forecast transformation and their effects. The paper presents some aspects of this problem, putting interest mainly on digital methods data processing and information integration.