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Structure of Dominance among Tree Species in Relic Swiss Stone Pine (Pinus cembra L.) Forests in Tatra Mountains

Zięba Antoni, Różański Wojciech, Szwagrzyk Jerzy

Polish Journal of Ecology

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2020

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Vol. 68, nr 2

159--171

EN

Pinus cembra forests are limited to the Alps and Carpathians. Although several studies regarding their structure were carried out in some locations in the Tatra Mts. it required further investigations. Therefore, the aims of this study were to describe the stand and shrub structure of P. cembra forests, compare their structure with the Picea abies forests and analyse differences between silicate and calcicolous P. cembra forests in the Tatra Mts. The data were collected on the 16 sampling plots (500 m2), in the Swiss stone pine and Norway spruce forests. We measured the diameter at breast height (dbh) of each tree and recorded the young trees and shrubs. In order to compare species composition between silicate and calcicolous P. cembra forests, we made 91 relevés in their entire range of distribution (917 ha). Furthermore, we examined the share of main tree species along the altitude and inclination gradients, using the GAM models. The tree density in the P. cembra forests reaches 618 stems per ha, whereas their basal area (BA) 23.17 m2 ha-1. Main tree species are P. cembra and P. abies. P. cembra dominates in the higher thickness classes. The BA and dbh structure varies significantly between P. cembra and P. abies forests. The most abundant juveniles are P. abies and Sorbus aucuparia. The differences between forests growing on different substrate are relatively low. The altitude has a significant impact on the share of P. cembra (increase) and P. abies (decrease). The inclination has a significant impact on the increase of share of P. cembra.

2

Unsupervised learning in latent space with a fuzzy logic guided modified BA

Kiełkowicz K.

Technical Transactions

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2018

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Vol. 115, iss. 8

141--153

EN

In this paper, a modified bat algorithm with fuzzy inference Mamdani-type system is applied to the problem of document clustering in a semantic features space induced by SV D decomposition. The algorithm learns the optimal clustering of the documents as well as the optimal number of clusters in a concept space; thus, making it suitable for a large and spare dataset which occur in information retrieval system. A centroidbased solution in multidimensional space is evaluated with a silhouette index. A TF-IDF method is used to represent documents in vector space. The presented algorithm is tested on the 20 Newsgroup dataset.

PL

W publikacji zmodyfikowany algorytm nietoperzowy z rozmytym kontrolerem typu Mamdaniego został zastosowany do problemu analizy skupisk dla danych tekstowych. Proces uczenia odbywa się w przestrzeni skompresowanej, otrzymanej z dekompozycji SV D zbioru uczącego. Prezentowany algorytm uczy się jednocześnie optymalnego pokrycia klastrami przestrzeni oraz liczebności klastrów. Do oceny jakości rozwiązania zastosowano wskaźnik Sillhouette. Dane w reprezentacji wektorowej otrzymano z wykorzystaniem transformacji TF-IDF. Prezentowany algorytm przetestowana na zbiorze „20 Newsgroup”.

3

Assessment of management pathways of by-products from biomass combustion using BATNEEC options

Smol M., Kulczycka J.

Acta Innovations

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2016

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no. 19

52--59

EN

The paper presents a methodology for evaluating the Best Available Techniques Not Entailing Excessive Costs (BATNEEC) options for the management of by-products from biomass combustion - ash. Biomass ash BA was collected from Green Energy Block in Połaniec (Poland). Four variant of BA disposal were analysed: 1st – the storage of BA on conventional municipal waste landfills; 2nd, 3rd, 4th - use of BA for fertilisers production (2nd – 70% of BA, 3rd - 45% of BA, 4th - 90% of BA). Technical, environmental and economic consequences of the actions in the field of waste management technology were considered. BATNEEC evaluation indicated that the collected BA on dump (1st variant) is technical, environmental and economic inefficient, this solution has received lowest score - 29 points. The 2nd, 3rd and 4th variants have received 124, 113 and 30 points, respectively. This indicates that there are quantitative restrictions on substitution of nutrients in mineral fertilisers. Due to the possibility of secondary pollution during waste usage in agriculture, the use of BA in fertiliser products requires compliance with environmental rules - only the nutrient rich and rather heavy metal poor fractions of BA shall be used for fertilising and soil improvement purposes.

4

Application of the Bee Swarm Optimization BSO to the Knapsack Problem

Sotelo-Figueroa M. A., Baltazar B., Carpio J. M.

Journal of Automation Mobile Robotics and Intelligent Systems

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2011

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Vol. 5, No. 1

101-114

EN

Swarm Intelligence is the part of Artificial Intelligence based on study of actions of individuals in various decentralized systems. The optimization algorithms which are inspired from intelligent behavior of honey bees are among the most recently introduced population based techniques. In this paper, a novel hybrid algorithm based in Bees Algorithm and Particle Swarm Optimization is applied to the Knapsack Problem. The Bee Algorithm is a new population-based search algorithm inspired by the natural foraging behavior of honey bees, it performs a kind of exploitative neighborhood search combined with random explorative search to scan the solution, but the results obtained with this algorithm in the Knapsack Problem are not very good. Although the combination of BA and PSO is given by BSO, Bee Swarm Optimization, this algorithm uses the velocity vector and the collective memories of PSO and the search based on the BA and the results are much better. We use the Greedy Algorithm, which it's an approximate algorithm, to compare the results from these metaheuristics and thus be able to tell which is which gives better results.