The Environmental Risk Assessment for Decision Support System for Water Management in the Vicinity of Open Cast Mines (Ds Wmvoc) / Rizikos Aplinkai Vertinimas Naudojant Netoli Atvirųjų Kasyklų Esančių Vandens Išteklių Valdymo Sprendimų Paramos Sistemą

Kochanek, Krzysztof; Tynan, Suzanne

doi:10.3846/tede.2010.26

Cited by 6 publications

(4 citation statements)

References 15 publications

(14 reference statements)

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“…The largest areas of contamination have formed in the landfill sites and fields of the largest industrial companies, railway objects, fuel bases, asbestos polluted sites, etc. Groundwater influenced by the industry makes potential danger to the supplies of upper and lower groundwater (Kochanek, tynan 2010).…”

Section: The Status Of Cleaning Contaminated Sites In Lithuaniamentioning

confidence: 99%

Comparison of Requirements for Environmental Protection and a Model for Evaluating Contaminated Sites in Lithuania

Vasarevičius

Kadūnas

Baltrėnaitė

2013

Technological and Economic Development of Economy

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This work is aimed at addressing attention to the situation of contaminated sites and emphasizing importance and need for their rehabilitation. The study presents the experience gained by European countries evaluating contaminated sites and rehabilitation framework. A model of assessing contaminated sites in Lithuania consisting of two main stages – preliminary and detailed investigation has been developed. The first one is used for collecting preliminary information on the contaminated site and for evaluating the need for detailed analysis. The second is subjected to a comprehensive risk assessment of the site shifting focus on the environment and human health. The model for evaluating contaminated sites involves organic chemical materials and metals. Risk assessment depends on the sensitivity of a site to contamination. Equations for establishing the level of contamination involve the content of soil organic matter and clay. Correction coefficients used for calculating the level of contamination have been based on statistical analysis and experience gained by the EU countries.

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Section: The Status Of Cleaning Contaminated Sites In Lithuaniamentioning

confidence: 99%

Comparison of Requirements for Environmental Protection and a Model for Evaluating Contaminated Sites in Lithuania

Vasarevičius

Kadūnas

Baltrėnaitė

2013

Technological and Economic Development of Economy

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“…In order to ensure traffic safety, measures are taken to help to avoid accidents and reduce the risk of traffic accidents, traffic jams, consumer expenses and environmental pollution (Kochanek, Tynan 2010). Thousands of tonnes of chemicals are applied on Lithuanian roads.…”

Section: Introductionmentioning

confidence: 99%

The impact on grass vegetation of materials reducing gravel road dustiness

Bradulienė

Vasarevičius

2012

The Baltic Journal of Road and Bridge Engineering

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Materials used to reduce dustiness on gravel roads affect both the gravel road surfacing and the neighbouring vegetation. Materials used to reduce dustiness may access vegetation directly (when sprayed on gravel roads) and indirectly (when leached out by precipitation). The investigation examined a new substance, the aqueous solution Safecote (of different concentrations) and its mixtures with calcium chloride. 10%, 20% and 30% concentrations of Safecote and 36.5% of calcium chloride were used. The mixture ratio was 1:1 by volume. The investigation addressed the impact of the applied solutions on the length and viability of the above-ground part of plants. The timothy grass, white clover and crimson clover species of grass vegetation were selected for the investigation. The choice was determined by the fact that these species frequently grow in pastures by gravel roads. As it was determined during the investigation the viability of the selected plants in non-contaminated soil was 85-89%, in soil contaminated with dust reducing agent was 67-88% using solution Safecote, and 0-1% when applying mixtures of solutions. After 6 weeks of growth the length of aboveground part was 6.41-8.57 cm in uncontaminated soil, 4.22-8.18 cm in soil contaminated with Safecote solution and 0.00-2.07 cm in soil contaminated with the mixture.

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“…Technological and Economic Development of Economy, 2012, 18(1): 5-33 Other applications in economics, including motor insurance fraud management (Furlan et al 2011), environmental risk assessment (Kochanek, Tynan 2010), e-banking website quality assessment (Kaya, Kahraman 2011) and etc., can also be explored by SVMs.…”

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confidence: 99%

Recent Advances on Support Vector Machines Research

Tian

Shi

Liu

2012

Technological and Economic Development of Economy

152

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Support vector machines (SVMs), with their roots in Statistical Learning Theory (SLT) and optimization methods, have become powerful tools for problem solution in machine learning. SVMs reduce most machine learning problems to optimization problems and optimization lies at the heart of SVMs. Lots of SVM algorithms involve solving not only convex problems, such as linear programming, quadratic programming, second order cone programming, semi-definite programming, but also non-convex and more general optimization problems, such as integer programming, semi-infinite programming, bi-level programming and so on. The purpose of this paper is to understand SVM from the optimization point of view, review several representative optimization models in SVMs, their applications in economics, in order to promote the research interests in both optimization-based SVMs theory and economics applications. This paper starts with summarizing and explaining the nature of SVMs. It then proceeds to discuss optimization models for SVM following three major themes. First, least squares SVM, twin SVM, AUC Maximizing SVM, and fuzzy SVM are discussed for standard problems. Second, support vector ordinal machine, semisupervised SVM, Universum SVM, robust SVM, knowledge based SVM and multi-instance SVM are then presented for nonstandard problems. Third, we explore other important issues such as lp-norm SVM for feature selection, LOOSVM based on minimizing LOO error bound, probabilistic outputs for SVM, and rule extraction from SVM. At last, several applications of SVMs to financial forecasting, bankruptcy prediction, credit risk analysis are introduced.

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The Environmental Risk Assessment for Decision Support System for Water Management in the Vicinity of Open Cast Mines (Ds Wmvoc) / Rizikos Aplinkai Vertinimas Naudojant Netoli Atvirųjų Kasyklų Esančių Vandens Išteklių Valdymo Sprendimų Paramos Sistemą

Cited by 6 publications

References 15 publications

Comparison of Requirements for Environmental Protection and a Model for Evaluating Contaminated Sites in Lithuania

Comparison of Requirements for Environmental Protection and a Model for Evaluating Contaminated Sites in Lithuania

The impact on grass vegetation of materials reducing gravel road dustiness

Recent Advances on Support Vector Machines Research

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