Search results for "Average"
showing 10 items of 238 documents
The effect of geometrical parameters on the discharge capacity of meandering compound channels
2008
A number of methods and formulae has been proposed in the literature to estimate the discharge capacity of compound channels. When the main channel has a meandering pattern, a reduction in the conveyance capacity for a given stage is observed, which is due to the energy dissipations caused by the development of strong secondary currents and to the decrease of the main channel bed slope with respect to the valley bed slope. The discharges in meandering compound channels are usually assessed applying, with some adjustments, the same methods used in the straight compound channels. Specifically, the sinuosity of the main channel is frequently introduced to account for its meandering pattern, al…
Classes of sum-of-cisoids processes and their statistics for the modeling and simulation of mobile fading channels
2013
Published version of an article in the journal: EURASIP Journal on Wireless Communications and Networking. Also available from the publisher at: http://dx.doi.org/10.1186/1687-1499-2013-125 Open access In this paper, we present a fundamental study on the stationarity and ergodicity of eight classes of sum-of-cisoids (SOC) processes for the modeling and simulation of frequency-nonselective mobile Rayleigh fading channels. The purpose of this study is to determine which classes of SOC models enable the design of channel simulators that accurately reproduce the channel’s statistical properties without demanding information on the time origin or the time-consuming computation of an ensemble ave…
Upport vector machines for nonlinear kernel ARMA system identification.
2006
Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA 2k) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based syste…
Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics
2012
In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESC), exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing s…
Application of Statistical Process Control to Continuous Processes
2002
Control charts represent an efficient and easy tool to assure the state of statistical quality control in a manufacturing process. These tools are also implemented in continuous processes, where the critical parameters are often monitored by on line sensors measuring data with short time intervals. In this paper a continuous process is monitored by using control charts and its dynamic is modeled through linear time series that allow the effects of the autocorrelation to be eliminated. In this way, the control charts can operate on residuals that result identically and independently distributed. A statistical analysis on EWMA, CUSUM and control charts for individual measurements has been car…
A survey on data center network topologies
2018
Data centers are the infrastructures that support the cloud computing services. So, their topologies have an important role on controlling the performance of these services. Designing an efficient topology with a high scalability and a good network performance is one of the most important challenges in data centers. This paper surveys recent research advances linked to data center network topologies. We review some representative topologies and discuss their proprieties in details. We compare them in terms of average path length, network fault tolerance, scalability and connection pattern techniques. Springer Nature Switzerland AG 2018. Acknowledgment. This publication was made possible by …
Forecasting Electricity Consumption and Production in Smart Homes through Statistical Methods
2022
Abstract Over the last years, a steady increase in both domestic electricity consumption and in the adoption of personal clean energy production systems has been observed worldwide. By analyzing energy consumption and production on photovoltaic panels mounted in a house, this work focuses on finding patterns in electrical energy consumption and devising a predictive model. Our goal is to find an accurate method to predict electrical energy consumption and production. Being able to anticipate how consumers will use energy in the near future, homeowners, companies and governments may optimize their behavior and the import and export of electricity. We evaluated the ARIMA and TBATS statistical…
A Hierarchical Model for Analysing Consumption Patterns in Italy Before and During the Great Recession
2016
The paper aims to explore how the Great Recession of the twenty-first century has impacted on the consumption behaviour of Italian households. Following a hierarchical approach, the study investigates differences in consumption behaviour at both household and regional levels. Using micro data on Italian Household Expenditure for the years 2002, 2006, 2010 and 2012, multilevel and two-step regression models have been estimated. The analysis has been performed for four different consumption categories: food, housing, work-related and leisure. The analysis reveals that the economic crisis led to increasing income elasticity for each category of consumption, especially for food, the most essent…
Next-Day Bitcoin Price Forecast
2019
This study analyzes forecasts of Bitcoin price using the autoregressive integrated moving average (ARIMA) and neural network autoregression (NNAR) models. Employing the static forecast approach, we forecast next-day Bitcoin price both with and without re-estimation of the forecast model for each step. For cross-validation of forecast results, we consider two different training and test samples. In the first training-sample, NNAR performs better than ARIMA, while ARIMA outperforms NNAR in the second training-sample. Additionally, ARIMA with model re-estimation at each step outperforms NNAR in the two test-sample forecast periods. The Diebold Mariano test confirms the superiority of forecast …
When the Blockchain Does Not Block: On Hackings and Uncertainty in the Cryptocurrency Market
2019
A total of 1.1 million bitcoin were stolen in the 2013–2017 period. Noting that the average price for Bitcoin in 2018 was USD 7,572 the corresponding monetary equivalent of losses is USD 8.9 billion which strongly shows the societal impact of this criminal activity. Investigating the response of the uncertainty of Bitcoin when hacking incidents occur, the results of this study point toward a delayed response in volatility. The volatility increases significantly only at day t+5. Incidents of hacking that occur in the Bitcoin market affect uncertainty for another cryptocurrency Ethereum too. Again, the evidence suggests a delayed response. However, Bitcoin and Ethereum do not exhibit asymmetr…