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1

Koncepcja nowego podejścia do oceny ryzyka w przygotowaniu i realizacji inwestycji budowlanych

Krawczyńska-Piechna A., Krzemiński P.

Materiały Budowlane

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2018

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nr 10

59--61

PL

Analiza ryzyka w procesie inwestycyjno-budowlanym powinna być wykonywana przez inwestora a priori, przy ogłoszeniu przetargu na roboty budowlane wg prawa zamówień publicznych i uwzględniana w systemie oceny ofert, niezależnie od tego, co i w jakiej procedurze jest budowane. Artykuł prezentuje koncepcję nowego podejścia do oceny ryzyka, wykorzystującą zarówno doświadczenie zarządzającego ryzykiem (dane archiwalne z wcześniej zrealizowanych inwestycji), jak i opracowywaną przez nas propozycję usprawnienia systemu zamówień publicznych na roboty budowlane. Zgodnie z nią, zidentyfikowane zagrożenia i ryzyka w procesie inwestycyjno-budowlanym dzieli się na 8 grup, zaś do oceny poziomu ryzyka w każdej z nich proponuje się zastosowanie metod zagregowanej analizy dyskryminacyjnej. W tym celu zbudowano model problemu decyzyjnego, zdefiniowano predyktory i zmienne objaśniane oraz zaproponowano sposób określania ich wartości.

EN

The risk analysis in the investment and construction process should be carried out by the investor a priori, on the notice for construction works according to the public procurement law and should be included in the offer evaluation system, regardless of what and in what procedure is being built. The paper presents a concept of a new approach to risk assessment, which incorporates both risk manager’s experience (archive data) and a developed by the authors improvements for public procurement system for construction works. According to the methodology, threats and risks identified in the investment and construction process, are divided into 8 groups. To assess the level of risk in each group, classifier ensembles are proposed. For this purpose, a model of decision problem was built, predictors, target attributes and a method for determining their value is proposed.

2

Wykorzystanie metod wielomodelowej analizy dyskryminacyjnej do wyboru systemu deskowania stropowego

Krawczyńska-Piechna A.

Materiały Budowlane

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2017

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nr 8

113--115

PL

Deskowania stropowe i ścienne są jednym z najistotniejszych środków realizacji robót betonowych, a koszt ich użycia stanowi 40 – 50% kosztu jednostkowego wykonania elementu żelbetowego. Z tego też względu wybór systemu deskowania począwszy od początku lat dziewięćdziesiątych jest poruszany przez naukowców na całym świecie. W artykule zaprezentowano zastosowanie wybranych metod wielomodelowej analizy dyskryminacyjnej do procesu wyboru deskowania stropowego. Określono model rozpatrywanego problemu decyzyjnego. Na podstawie danych pozyskanych z inwestycji zrealizowanych w kraju porównano skuteczność działania wybranych klasyfikatorów i wskazano możliwości udoskonalenia zaproponowanych rozwiązań.

EN

Formwork is the largest single cost item in cast-in place reinforced concrete structure and can be estimated as 40-50% of the cost of the concrete skeleton. This is why the formwork selection has been discussed since early 90’s by various researchers all over the world. The paper introduces classifier ensembles as a tool that can be applied to solve formwork selection problem and describes the mathematical model of the decision problem. The data collected on the national construction sites were used in order to compare various classifiers’ accuracy of classification. The paper ends with indications that should improve the proposed solutions.

3

Potential Contour Ensembles

Tomczyk A.

Schedae Informaticae

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2015

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Vol. 24

113--121

EN

In the paper a contour ensemble image segmentation concept is presented. It bases on the previously observed relationship between contours and classifiers. Because of the specificity of the active contour segmentation the method requires a special procedure to obtain ensemble members with desired properties. In this work it is achieved by early stopping of randomized optimization algorithm. The results of the method are illustrated with a practical problem of heart ventricle segmentation by means of active potential contours. Automatically found contours may be of use in a process of pulmonary embolism diagnosis.

4

Classifier ensembles using structural features for spammer detection in online social networks

Abulaish M., Bhat S. Y.

Foundations of Computing and Decision Sciences

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2015

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Vol. 40, No. 2

89--105

EN

As the online social network technology is gaining all time high popularity and usage, the malicious behavior and attacks of spammers are getting smarter and difficult to track. The newer spamming approaches using the social engineering concepts are making traditional spam and spammer detection techniques obsolete. Especially, content-based filtering of spam messages and spammer profiles in online social networks is becoming difficult. Newer approaches for spammer detection using topological features are gaining attention. Further, the evaluation of ensemble classifiers for detection of spammers over social networking behavior-based features is still in its infancy. In this paper, we present an ensemble learning method for online social network security by evaluating the performance of some basic ensemble classifiers over novel community-based social networking features of legitimate users and spammers in online social networks. The proposed method aims to identify topological and community-based features from users’ interaction network and uses popular classifier ensembles – bagging and boosting to identify spammers in online social networks. Experimental evaluation of the proposed method is done over a real-world data set with artificial spammers that follow a behavior as reported in earlier literature. The experimental results reveal that the identified features are highly discriminative to identify spammers in online social networks.

5

Medical diagnosis support system based on the ensemble of single-parameter classifiers

Orczyk T., Porwik P., Bernaś M.

Journal of Medical Informatics & Technologies

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2014

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Vol. 23

173--179

EN

This paper presents a medical diagnosis support system based on an ensemble of single parameter k–NN classifiers [1]. System was verified on a database containing real blood test results of diagnosed patients with a liver fibrosis. This dataset contains problems typical to a real medical data – especially missing values. Paper also describes the process of selecting a subset of parameters used for further evaluation (feature selection/elimination algorithm). Complete database contains many parameters, but not all are important for diagnosis, thus eliminating them is an important step. A comparison of proposed method of classification and feature selection with methods known from literature has also been presented.

6

Hypertension diagnosis using compound pattern recognition methods

Krawczyk B., Woźniak M.

Journal of Medical Informatics & Technologies

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2011

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Vol. 18

41--50

EN

The paper presents a hypertension type classification task where the decisions should be made only on the basis of blood pressure, general information and basis biochemical data. This problem has a great importance to the medical decision support systems, yet results achieved so far are not satisfactory. When the canonical approaches tend to fail we should look for the compound pattern recognition systems, such as multiple classifiers systems. This article presents the results of an experimental investigation of the pool of compound classifiers which have their origin in classifiers ensembles, random forest, and random subspace. Presented methods returned good, satisfactory results, outperforming canonical approaches for this problem.