1,720,976 research outputs found
Dropout method for XGBoost algorithm
No full textTika izpētīta izslēgšanas metode, DART algoritms, XGBoost algoritms un XGBoost algoritma hiperparametri (α, λ, γ, srinkage un subsample), kas saistīti ar modeļa regularizāciju un pārpielāgošanas samazināšanu. Tika izpētīti un attēloti izslēgšanas metodes un XGBoost hiperparametru efekti uz atsevišķu lēmumu koku ietekmi uz ansambļa prognozi un efekti uz modeļu pārpielāgošanos. Iegūtie attēli tika salīdzināti starp izslēgšanas metodi, XGBoost modeļiem ar regularizācijas hiperparametriem un XGBoost modeli bez regularizācijas.Dropout method, DART algorithm, XGBoost algorithm and XGBoost hyperparameters (α, λ, γ, srinkage un subsample) related to model regularization were researched. Ways of graphically depicting the effect of dropouts and XGBoost hyperparameters on the contribution of individual decion trees on the output of the model and on the overfit of the model were researched and employed. The obtained plots were compared between models with XGBoost parameters and models with dropouts as well as a XGBoost model without any regularization
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Modelling of Traffic Loads for Bridge Spans from 200 to 600 Meters
No full textTraffic load models available in building codes are most often developed for short or medium span bridges, but most unfavorable traffic situations for long span bridges are very different from the ones considered in them. For this reason funds may be used irrationally, if inappropriate traffic load models are used for long span bridge design.
Weigh – in – Motion (WIM) data from WIM station installed on 72. kilometer of highway A1, have been used in these thesis. First data cleaning was performed, then data were split into two lanes.
Long span bridge loads were calculated by using information about vehicles found in traffic flow from the cleaned WIM data. Load calculations were done for 200, 300, 400, 500 and 600 meter long spans, traffic flow was simulated using seven different traffic scenarios, out of which first six simulates traffic with varying percentage of trucks, the seventh scenario simulates traffic flow consisting entirely out of cars.
For each lane, span, traffic scenario combination Gumbel’s distributions were fitted to the highest 30% of the calculated loads, by using maximum likelihood estimate for left truncated data; loads were extrapolated to the probability of exceedance of 10% in hundred years period.
Results show that Eurocode 1 part 2 load model 1 loads are too conservative for use in long span bridge design even when very unlikely scenario of only trucks in the leftmost lane is considered
Analysis of Yearly Traffic Fluctuation on Latvian Highways
No full textAverage annual daily traffic and average annual truck traffic are two most used metrics
for road management decisions. They are calculated from data gathered by continuous counting
stations embedded in road pavement, manual counting sessions or mobile counting devices. Last
two usually aren’t longer than a couple of weeks so the information gathered is influenced by
yearly traffic fluctuations.
Data containing a total of 8’186’871 vehicles or 1989 days from 4 WIM stations installed on
highways in Latvia were used in this study. Each of the files were supposed to contain data from
only 1 day and additional data were deleted. No other data cleaning steps were performed, which
increased the number of vehicles as counting systems sometimes split vehicles in two.
Weekly traffic and weekly truck traffic was normalized against respective average values. Each
weekly value was then plotted against its number in a year for better visual perception. Weekly
traffic amplitudes were used to assess differences between different locations and standard
deviations for fluctuation comparison of truck and regular traffic at the same location.
Results show that truck traffic fluctuates more than regular traffic during a year, especially
around holidays. Differences between counting locations were larger for regular traffic than
truck traffic. These results show that average annual daily traffic could be influenced more if
short term counting results are adjusted by factors derived from unsuitable continuous counting
stations, but truck traffic is more influenced by the time of year in which counting is done
Comparision of Constant-Span and Influence Line Methods for Long-Span Bridge Load Calculations
No full textTraffic load models available in building standards are most often developed for short or medium span bridges, however, it is necessary to develop traffic load models just for long span bridges, because the most unfavourable traffic situations are different. Weigh-in-Motion system data from highway A1 and A3 were used in this study. Measurement errors from data were cleaned using two groups of filters. The first group was based on vehicle validity codes recorded by both systems, if any circumstances might have influenced the measurements, the second group cleaned data using general filters for all vehicles and specific filters for trucks and cars. Additionally, vehicles were adjusted for influence of temperature. Data cleaning increased the average gross vehicle, so it could be considered as a conservative choice. Six traffic scenarios, each with different percentage of cars in the traffic, were made to assess the difference in loads from different traffic compositions. Traffic loads for long-span bridges were calculated using two approaches: the first assuming constant span length, the second, using influence lines from a bridge currently in design stage. Gumbel distribution were fitted to the calculate loads and they were extrapolated to probability of exceedance of 5% in 50 year period. Results show that influence line approach yield larger loads than those from constant-span. Both approaches result in loads larger than ones in Eurocode 1 Load Model 1, however, increase might have been caused by an increase in vehicle weight
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