Sharif Digital Repository

Long-term electricity load and price forecasts have become critical inputs to energy service provider (ESP) decision makings in restructured environments. This paper presents a three-stage hierarchical approach for long-term electricity load forecasting. These stages are called yearly trend model (YTM), weekly trend model (WTM), and daily trend model (DTM). The first stage fits an appropriate function to data and extracts its yearly trend. The weekly and daily trends are then extracted using the Box-Jenkins method in WTM and DTM, respectively. For doing so, candidate trends are identified using auto correlation function (ACF) and partial auto correlation function (PACF) plots. Then, Akaike... 

High resolution range profile (HRRP) is being known as one of the most powerful tools for radar target recognition. The main problem with range profile for radar target recognition is its sensitivity to aspect angle. To overcome this problem, consecutive samples of HRRP were assumed to be identically independently distributed (IID) in small frames of aspect angles in most of the related works. Here, considering the physical circumstances of maneuver of an aerial target, we have proposed dynamic system which models the short dependency between consecutive samples of HRRP in segments of the whole HRRP sequence. Dynamic system (DS) is used to model the sequence of PCA (principal component... 

The high resolution range profile (HRRP) is known as the most important tool in radar target recognition. Mainly, the sensitivity to the aspect angle limits the performance of the related methods. To overcome this problem, Gaussian mixture distribution is used to model the short-term relation of consecutive HRRPs. In this work, an alternative dynamical system based method is proposed to overcome the limitations of recent methods in the field such as the independency assumption. Here, the performance of the method is tested by the data produced in an electromagnetic simulation for the radar return from an aerial maneuvering target. The results show the performance of the proposed method... 

An approach based on unitary transformation for the problem of estimating the number of signals is proposed in this study. Among the information theoretic criteria, the authors focus on the conventional Bayesian information criterion (BIC) in the presence of a uniform linear array. The sample covariance matrix of this array is transformed into the real symmetric one by using a unitary transformation. This real symmetric matrix has real eigenvalues and eigenvectors. Therefore its eigenvalue decomposition needs only real computations. Since the eigenvalues of this real symmetric matrix are equal to the eigenvalues of the sample covariance matrix, by replacing them in BIC formula, the term... 

This study presents a new method for epilepsy detection based on autoregressive (AR) estimation of EEG signals. In this method, optimum order for AR model is determined by Bayesian Information Criterion (BIC) and then AR parameters of EEG signals (from EEG data set of epilepsy center of the University of Bonn, Germany) and their sub-bands (created with the help of wavelet decomposition) are extracted based on it. These parameters are used as a feature to classify the EEG signals into Healthy, Interictal (seizure free) and Ictal (during a seizure) groups using multilayer perceptron (MLP) classifier. Correct classification scores at the range of 91% to 96% reveals the potential of our approach... 

A novel, robust and practical method for active user enumeration in asynchronous CDMA in multipath channel condition is proposed in this paper. Most of the previous works do not consider the fact that in practical case, user's signals with the help of receiver arrive asynchronously. The proposed method can be used practically in blind multi-user detection such as eavesdropping; moreover, the method is based on information theory criteria which outperform other methods. Minimum description length (MDL) has better performance than all other information criteria used in such scenarios. Unlike most of the pervious works, we do not exploit array antenna to gather necessary data of the users.... 

Wireless Body Area Networks (WBANs) are one of the emerging technological trends that have gained a lot of attention both from academic and industrial domains. WBAN, as standardized by IEEE 802.15.6, is a network composed of intelligent, miniaturized, low power nodes that are implanted in, placed on or in close proximity of human body for certain healthcare applications. Sensors send their acquired data to a central hub wirelessly for further processing. In this paper, based on a publicly available channel data set, we investigate the applicable channel models in a typical WBAN. Considering various scenarios with different carrier frequencies, bandwidths, body movements, and transceiver... 

According to crash configuration and pre-crash conditions, traffic crashes are classified into different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear-end, and angle crashes, are more frequent than single-vehicle crashes, and most often result in serious consequences. From a methodological point of view, the majority of prior studies focused on multivehicle collisions have employed univariate count models to estimate crash counts separately by collision type. However, univariate models fail to account for correlations which may exist between different collision types. Among others, multivariate Poisson lognormal (MVPLN) model with spatial correlation... 

In the literature of model selection, Vuong’s test and Akaike information criterion aim to find the best statistical model. Both of them are related to the expectation of the log-likelihood function of the rival models, but they are not sensitive to the small difference between rival models. The goal of this study is to develop a simple model selection approach which does not assume a true distribution for data. We have introduced a nonparametric tracking interval in the context of model selection. We have shown that this interval is compatibale with the known Vuong’s test results, but here we let the magnitude of the data enhance the performance of statistical inference. Simulation study... 

In the literature of model selection, Vuong’s test and Akaike information criterion aim to find the best statistical model. Both of them are related to the expectation of the log-likelihood function of the rival models, but they are not sensitive to the small difference between rival models. The goal of this study is to develop a simple model selection approach which does not assume a true distribution for data. We have introduced a nonparametric tracking interval in the context of model selection. We have shown that this interval is compatibale with the known Vuong’s test results, but here we let the magnitude of the data enhance the performance of statistical inference. Simulation study...