Краткосрочный прогноз часового потребления электроэнергии с учетом погоды для субъектов РФ
The power consumption is determined by various factors. It is affected by time of day, day of week, and of season. The price of electricity is determined by the controller, and can affect the schedule of consumption of various consumers. And this formulae depends essentially on the concrete region. Forecast of consumption may influence both the tactics of consumers and producers of electricity and the strategy of the regulator. The impact will be stronger, when more reliable the forecast. One of the non-recurrent factors is the weather. We developed operational computer technology short-term forecasting of hourly electricity consumption for 63 subjects of the Russian Federation, using the short-term forecast of the air temperature. We evaluate the parameters of our algorithm according to information from archives, which describes electricity consumption and air temperature. The MAPE error obtained forecast the average for the subjects is 3.2% while the forecast for 1 day and 3.7% in the second. The impact of the weather forecast into the error decreasing corresponds to the reduction of the forecast lead-time of 1 day.
This paper presents a method and computational technology for forecasting ambulance trips. We used statistical information about the number of the trips (per day or per night) in 2009-2013, the meteorological archive, and the corresponding archive of the meteorological measurements and meteorological forecasts for the same period. We take into account both social and meteorological predictors simultaneously. The impact of the meteorological factors (both climatic and short range lead times) into the statistics may be significant for some diseases. We present also the errors of these forecasts and demonstrate that the quality of our weather forecasts for the lead times 1- 3 days is good for the forecasting the number of ambulance trips.
The method may be used operatively for planning and control in the ambulance service. It may be applied for all trips and for specific subgroups of diseases. The method and the technology may be applied for any megalopolis if the corresponding medical and meteorological information is available.
Measuring indirect importance of various attributes is a very common task in marketing analysis for which researchers use correlation and regression techniques. We have listed and illustrated some common problems with widely used latent importance measures. A more theoretically sound approach - the Shapley Value decomposition - was applied to a rich data set of US internet stores. The use of store-level data instead of respondent-level data allowed us to reveal the factors, which are powerful in explaining, why some stores have higher rates of willingness to make repeat purchases than the others. By confronting the indirect importance and performance measures for three different internet stores, we have revealed strengths, weaknesses, attributes that the company should bring customers' attention to and attributes that do not require immediate improvement.
In the process of developing an information system for logistics transportation, there is a need to determine the initial rating of the new carrier within the parent company. The presence of the rating helps to more accurately carry out the formation of orders and build forecasts of its interaction with the parent company in the future
A simple measure of similarity for the construction of the market graph is proposed. The measure is based on the probability of the coincidence of the signs of the stock returns. This measure is robust, has a simple interpretation, is easy to calculate and can be used as measure of similarity between any number of random variables. For the case of pairwise similarity the connection of this measure with the sign correlation of Fechner is noted. The properties of the proposed measure of pairwise similarity in comparison with the classic Pearson correlation are studied. The simple measure of pairwise similarity is applied (in parallel with the classic correlation) for the study of Russian and Swedish market graphs. The new measure of similarity for more than two random variables is introduced and applied to the additional deeper analysis of Russian and Swedish markets. Some interesting phenomena for the cliques and independent sets of the obtained market graphs are observed.
Measuring indirect importance of various attributes is a very common task in marketing analysis for which researchers use correlation and regression techniques. We have listed and illustrated some common problems with widely used latent importance measures. A more theoretically sound approach – the Shapley Value decomposition – was applied to a rich data set of US internet stores. The use of store-level data instead of respondent-level data allowed us to reveal the factors, which are powerful in explaining, why some stores have higher rates of willingness to make repeat purchases than the others. By confronting the indirect importance and performance measures for three different internet stores, we have revealed strengths, weaknesses, attributes that the company should bring customers’ attention to and attributes improvement of which is not of a high priority.
This article proposes a mutual adaptation of the procedure for extracting digital watermark from video sequences and fingerprinting code decoding. Proposed solution includes two interrelated techniques. The first one is a usage of “soft” decision making instead of “hard” decision during watermark extraction. This means that the additional information on extracted bit reliability will be obtained from the hidden channel. The second one is an including of the reliability to decoding procedure. The use of such a solution allows more effective work of fingerprinting codes and achieves zero accusation error rates.
This proceedings publication is a compilation of selected contributions from the “Third International Conference on the Dynamics of Information Systems” which took place at the University of Florida, Gainesville, February 16–18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and academia in order to exchange new discoveries and results in a broad range of topics relevant to the theory and practice of dynamics of information systems. Dynamics of Information Systems: Mathematical Foundation presents state-of-the art research and is intended for graduate students and researchers interested in some of the most recent discoveries in information theory and dynamical systems. Scientists in other disciplines may also benefit from the applications of new developments to their own area of study.