Wyniki 1-2 spośród 2 dla zapytania: authorDesc:"Łukasz CHOMĄTEK"

Adaptation of artificial hierarchical division of the road network to different traffic conditions

Czytaj za darmo! »

In this article an algorithm for adaptation of the artificial hierarchical division of the road network to different traffic conditions is presented. The algorithm is an extension of the known Highway Hierarchies algoritm. After application of the proposed improvements, obtained results revealed the reduction of the computational time required for finding optimal path between two points on the map. What is more, presented algorithm can be applied in case of solving dynamic Vehicle Routing Problem. Streszczenie. W niniejszym artykule zaprezentowano algorytm adaptacji sztucznego podziału hierarchicznego sieci drogowej do zmiennych warunków natężenia ruchu. Algorytm jest rozwinięciem algorytmu Highway Hierarchies. Po zastosowaniu zaproponowanych przez autorów zmian otrzymano redukcję czasu obliczeniowego potrzebnego do wyznaczenia optymalnej trasy pomiędzy punktami w grafie połączeń drogowych. (Adaptacja sztucznego podziału hierarchicznego sieci drogowej do zmiennych warunków natężenia ruchu) Keywords: road network hierarchical division, Parallel Hierarchies, Dynamic Vehicle Routing Problem. Słowa kluczowe: podział hierarchiczny sieci drogowej, dynamiczny problem marszrutyzacji Introduction Efficient vehicle routing is one of the major problems in most cities. Complexity of the road network causes the need of the efficient algorithms for finding the optimal routes between points on the map. Such algorithms are often implemented either to work on personal car navigation system or as an online services. Limited resources of personal devices as well as growing number of users of the web-based systems exacts optimization of the algorithms computational complexity and the memory usage. Classical algorithms for finding optimal itineraries for drivers are based on the priority queue, where each node’s priority is calculated in different methods. Modern approahes for this problem are based on the hierarchical division of the road network[...]

Detection of outliers in data streams using grouping methods DOI:

Czytaj za darmo! »

Introduction A data stream is a set of observations recorded in time intervals, i.e. containing a unit of time. They do not have to be data recorded at regular intervals, but usually these are data which have an equal time interval. An example of a data stream can be:  Air temperature measurement in the room every one second, which gives us a data stream consisting of the time value and the measurement result assigned to it in the form of degrees Celsius.  24-hour registration of the electrocardiographic signal using the Holter method, recording heart activity;  Electricityconsumption;  Record of monitoring at the airport;  Monitoring the workload of networks and websites;  Monitoring and recording of work;  Banking, telemetric and surveillance systems;  Tracking and analysis of biological and medical data;  Stock market data;  Data on all types of physical devices The data stream is defined as an ordered set of values of the analyzed feature or a specific phenomenon at different times (intervals) of time. It is also a series of observations recorded in a strictly defined time. Collection and storage of data in the form of streams increases the development of methods of processing them. There is also an increased problem of detection of outliers in data streams. The problem of detecting outliers in large data collections is, according to the authors, an important research problem. Among others, deterministic statistical methods, as well as methods based on distance and density, are used. However, none of the methods proposed in the literature is universal. A rich overview of this field is given in [1,2]. In addition, their effectiveness depends on the data set as well as on the parameters required for their operation. The authors dealt with the detection of outliers in their earlier works. Among other things, a method of dete-cting outliers[...]

 Strona 1