With the widespread use of the Internet, network security issues have attracted more and more attention, and network intrusion detection has become one of the main security technologies. As for network intrusion detection, the original data source always has a high dimension and a large amount of data, which greatly influence the efficiency and the accuracy. Thus, both feature selection and the classifier then play a significant role in raising the performance of network intrusion detection. This paper takes the results of classification optimization of weighted K-nearest neighbor (KNN) with those of the feature selection algorithm into consideration, and proposes a combination strategy of feature selection based on an integrated optimization algorithm and weighted KNN, in order to improve the performance of network intrusion detection. Experimental results show that the weighted KNN can increase the efficiency at the expense of a small amount of the accuracy. Thus, the proposed combination strategy of feature selection based on an integrated optimization algorithm and weighted KNN can then improve both the efficiency and the accuracy of network intrusion detection.

Article citation info: (*) Tekst artykułu w polskiej wersji językowej dostępny w elektronicznym wydaniu kwartalnika na stronie www.ein.org.pl Kusz A, MArciniAK A, sKwArcz J. implementation of computation process in a bayesian network on the example of unit operating costs determination. Eksploatacja i niezawodnosc -Maintenance and reliability 2015; 17 (2): 266-272, http://dx.doi.org/10.17531/ein.2015.2.14. Andrzej Kusz Andrzej MArciniAK Jacek sKwArczImplementatIon of computatIon process In a bayesIan network on the example of unIt operatIng costs determInatIon Implementacja procedury oblIczenIowej w sIecI bayesowskIej na przykładzIe wyznaczanIa jednostkowych kosztów eksploatacjI* In technical systems understood in terms of Agile Systems, the important elements are information flows between all phases of an object existence. Among these information streams computation processes play an important role and can be done automatically and also in a natural way should include consideration of uncertainty. This article presents a model of such a process implemented in a Bayesian network technology. The model allows the prediction of the unit costs of operation of a combine harvester based on the monitoring of dependent variables. The values of the decision variables representing the parameters of the machine's operation and the intensity and the conditions for its operation, are known to an accuracy, which is defined by a probability distribution.The study shows, using inference mechanisms built into the network, how cost simulation studies of various situational options can be carried out. Keywords: agricultural machinery operation, computing processes, unit operating costs, Bayesian networks. W systemach technicznych rozumianych w kategoriach Agile Systems istotnym elementem są przepływy informacyjne pomiędzy wszystkimi fazami istnienia obiektu. Pośród tych strumieni informacyjnych istotną rolę odgrywają procesy obliczeniowe, które mogą być realizowane automatycznie a ponadto w naturalny sposób powinny umożliwiać uwzględnienie niepewności. W artykule przedstawiono przykład takiego procesu realizowanego w technologii sieci bayesowskiej. Model umożliwia predykcję jednostkowych kosztów eksploatacji kombajnu zbożowego na podstawie monitorowania wielkości zmiennych od których one zależą. Wartości zmiennych decyzyjnych reprezentujących parametry pracy maszyny oraz intensywność i warunki jej eksploatacji są znane z dokładnością do rozkładu prawdopodobieństwa. W pracy pokazano w jaki sposób wykorzystując mechanizmy wnioskowania wbudowane w sieci można prowadzić symulacyjne badania kosztów w różnych wariantach sytuacyjnych.Słowa kluczowe: eksploatacja maszyn rolniczych, procesy obliczeniowe, jednostkowe koszty eksploatacji, sieci bayesowskie. IntroductionThe technical systems of today can be understood in terms of Agile Systems. This means that their existence is not a series of separate phases: design, manufacturing, operation and recycling. The "agile paradigm" assumes the simultaneous presence of all these phases. For examp...

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The study attempts to compare the total annual emissions of selected air pollutants emitted during occasional grilling and the emission of the same pollutants from small domestic heating installations. For this purpose, in the absence of any data on the emission of pollutants during grilling processes, tests were carried out consisting of measuring the concentration of air pollutants in exhaust streams from two types of grills (solid fuel grill powered by charcoal briquette and gas grill powered by liquid propane), using popularly prepared dishes (previously marinated meat and raw, seasoned mixed vegetables). The concentrations of PM2.5, CH4, CO, CO2, H2O, NH3, N2O, NO, NO2, SO2 were measured in the exhaust stream from both grills using a particulate matter (PM) measuring device and a portable spectrometer, separately while grilling the same portions of meat and vegetables. Then, considering the available data on Poles’ barbecue habits, the emissions that are released into the air during occasional grilling were estimated. The calculated emissions were compared with the data on emissions from domestic heating installations used in Poland. It has been shown that during grilling, as much as 2.30, 92.07, 4.11, 3.83, 2.96, and 9.81 Gg of PM2.5, CO, NOx, SO2, NH3, and CH4 may be released into the atmosphere in Poland, respectively. In the case of PM, the amount of the pollutant emitted to the air is over 100 times lower than the emissions caused by the operation of small heating installations. In the case of other pollutants, the differences are smaller. Nevertheless, emissions from grills should not be underestimated as, in certain periods of the year, these sources may be responsible for not meeting the air quality standards in selected areas of the country, and thus the excessive exposure of people to pollutants resulting in negative health consequences. Therefore, attention was paid to the legitimacy of abandoning the use of charcoal and charcoal briquette grills and replacing them with gas-powered grills or electric ones, not only due to the health benefits of food and lower human exposure, but also by the reason of ecological values.

Electric vehicles are fully ecological means of transport only when the electricity required to charge them comes from Renewable Energy Sources (RES). When building a photovoltaic carport, the complex of its functions must consider the power consumption necessary to charge an electric vehicle. The performance of the photovoltaic system depends on the season and on the intensity of the sunlight, which in turn depends on the geographical conditions and the current weather. This means that even a large photovoltaic system is not always able to generate the amount of energy required to charge an electric vehicle. The problem discussed in the article is maximization of the share of renewable energy in the process of charging of electric vehicle batteries. Deep recurrent neural networks (RNN) trained on the past data collected by performance monitoring system can be applied to predict the future performance of the photovoltaic system. The accuracy of the presented forecast is sufficient to manage the process of the distribution of energy produced from renewable energy sources. The purpose of the numerical calculations is to maximize the use of the energy produced by the photovoltaic system for charging electric cars.