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Permutation approach, high frequency trading and variety of micro patterns in financial time series
, Article Physica A: Statistical Mechanics and its Applications ; Vol. 413, issue , 2014 , pp. 25-30 ; ISSN: 03784371 ; Ebrahimian, M ; Tahmooresi H ; Sharif University of Technology
Abstract
Permutation approach is suggested as a method to investigate financial time series in micro scales. The method is used to see how high frequency trading in recent years has affected the micro patterns which may be seen in financial time series. Tick to tick exchange rates are considered as examples. It is seen that variety of patterns evolve through time; and that the scale over which the target markets have no dominant patterns, have decreased steadily over time with the emergence of higher frequency trading
Pattern recognition in financial surveillance with the ARMA-GARCH time series model using support vector machine
, Article Expert Systems with Applications ; Volume 182 , 2021 ; 09574174 (ISSN) ; Akhavan Niaki, S. T ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
As the intersection of finance and statistics, financial surveillance is a new interdisciplinary field of research. In this field, statistical process control methods are applied to monitor financial indices. The final aim is to detect out-of-control conditions and trigger a signal as soon as possible. These early signals can help practitioners in making on-time decisions. In this paper, a new method based on a support vector machine is proposed to detect upward and downward shifts with step and trend patterns in auto-correlated financial processes. These processes are modeled by the autoregressive moving average (ARMA) and generalized autoregressive conditional heteroskedasticity (GARCH)...
On the resolution of existing discontinuities in the dynamic responses of an Euler-Bernoulli beam subjected to the moving mass
, Article 8th Biennial ASME Conference on Engineering Systems Design and Analysis, ESDA2006, Torino, 4 July 2006 through 7 July 2006 ; Volume 2006 , 2006 ; 0791837793 (ISBN); 9780791837795 (ISBN) ; Saeedi, K ; Sharif University of Technology
American Society of Mechanical Engineers
2006
Abstract
The dynamic response of a one-dimensional distributed parameter system subjected to a moving mass with constant speed is investigated. An Euler-Bernoulli beam with the uniform cross-section and finite length with specified boundary support conditions is assumed. In this paper, rather a new method based on the time dependent series expansion for calculating the bending moment and the shear force due to motion of the mass is suggested. Governing differential equations of the motion are derived and solved. The accuracy of the numerical results primarily is verified and further the rapid convergence of this new technique was illustrated over other existing methods. Finally, it is shown that a...
On the existence of proper stochastic Markov models for statistical reconstruction and prediction of chaotic time series
, Article Chaos, Solitons and Fractals ; Volume 123 , 2019 , Pages 373-382 ; 09600779 (ISSN) ; Salarieh, H ; Alasty, A ; Sharif University of Technology
Elsevier Ltd
2019
Abstract
In this paper, the problem of statistical reconstruction and prediction of chaotic systems with unknown governing equations using stochastic Markov models is investigated. Using the time series of only one measurable state, an algorithm is proposed to design any orders of Markov models and the approach is state transition matrix extraction. Using this modeling, two goals are followed: first, using the time series, statistical reconstruction is performed through which the probability density and conditional probability density functions are reconstructed; and second, prediction is performed. For this problem, some estimators are required and here the maximum likelihood and the conditional...
On the control of unknown continuous time chaotic systems by applying takens embedding theory
, Article Chaos, Solitons and Fractals ; Volume 109 , April , 2018 , Pages 53-57 ; 09600779 (ISSN) ; Salarieh, H ; Hajiloo, R ; Sharif University of Technology
Elsevier Ltd
2018
Abstract
In this paper, a new approach to control continuous time chaotic systems with an unknown governing equation and limitation on the measurement of states, has been investigated. In many chaotic systems, disability to measure all of the states is a usual limitation, like in some economical, biological and many other engineering systems. Takens showed that a chaotic attractor has an astonishing feature in which it can embed to a mathematically similar attractor by using time series of one of the states. The new embedded attractor saves much information from the original attractor. This phenomenon has been deployed to present a new way to control continuous time chaotic systems, when only one of...
OmpF, a nucleotide-sensing nanoprobe, computational evaluation of single channel activities
, Article Physica A: Statistical Mechanics and its Applications ; Volume 457 , 2016 , Pages 215-224 ; 03784371 (ISSN) ; Mobasheri, H ; Nikouee, A ; Ejtehadi, M. R ; Sharif University of Technology
Elsevier B.V
2016
Abstract
The results of highthroughput practical single channel experiments should be formulated and validated by signal analysis approaches to increase the recognition precision of translocating molecules. For this purpose, the activities of the single nano-pore forming protein, OmpF, in the presence of nucleotides were recorded in real time by the voltage clamp technique and used as a means for nucleotide recognition. The results were analyzed based on the permutation entropy of current Time Series (TS), fractality, autocorrelation, structure function, spectral density, and peak fraction to recognize each nucleotide, based on its signature effect on the conductance, gating frequency and voltage...
Nonlinear seismic assessment of steel moment frames using time-history, incremental dynamic, and endurance time analysis methods
, Article Scientia Iranica ; Volume 20, Issue 3 , 2013 , Pages 431-444 ; 10263098 (ISSN) ; Zarringhalam, Y ; Estekanchi, H. E ; Yahyai, M ; Sharif University of Technology
2013
Abstract
A recent method in the seismic assessment of structures is Endurance Time Analysis (ETA). ETA is a time-history-based dynamic pushover procedure, in which structures are subjected to gradually intensifying acceleration functions called Endurance Time Acceleration Functions (ETAFs), and their performances are evaluated based on the equivalent intensity level that they can endure while satisfying required performance goals. In this paper, the accuracy of the ETA in the seismic assessment of steel moment resisting frames is compared with the Time History Analysis (THA) and Incremental Dynamic Analysis (IDA) methods. For this purpose, a set of mid-rise and high-rise frames were selected as a...
Nonlinear dynamic modeling of surface defects in rolling element bearing systems
, Article Journal of Sound and Vibration ; Volume 319, Issue 3-5 , 2009 , Pages 1150-1174 ; 0022460X (ISSN) ; Abbasion, S ; Farshidianfar, A ; Moeenfard, H ; Sharif University of Technology
2009
Abstract
In this paper an analytical model is proposed to study the nonlinear dynamic behavior of rolling element bearing systems including surface defects. Various surface defects due to local imperfections on raceways and rolling elements are introduced to the proposed model. The contact force of each rolling element described according to nonlinear Hertzian contact deformation and the effect of internal radial clearance has been taken into account. Mathematical expressions were derived for inner race, outer race and rolling element local defects. To overcome the strong nonlinearity of the governing equations of motion, a modified Newmark time integration technique was used to solve the equations...
Nonlinear dynamical structure of sway path during standing in patients with multiple sclerosis and in healthy controls is affected by changes in sensory input and cognitive load
, Article Neuroscience Letters ; Volume 553 , 2013 , Pages 126-131 ; 03043940 (ISSN) ; Sanjari, M. A ; Mofateh, R ; Parnianpour, M ; Sharif University of Technology
2013
Abstract
Although several studies have applied traditional linear measures to evaluate postural control of patients with multiple sclerosis (MS), little is known about the nonlinear dynamics of this patient group. In this study, recurrence quantification analysis (RQA), a well documented nonlinear method, was used to compare the nonlinear dynamical structure of postural sway in two groups consisting of MS patients (. n=. 23) and healthy matched controls (. n=. 23). The study focuses on three levels of postural difficulty consisting of (1) standing on a rigid surface (force platform) with eyes open, (2) standing on a rigid surface with eyes closed, and (3) standing on a foam surface with eyes closed....
Network-based direction of movement prediction in financial markets
, Article Engineering Applications of Artificial Intelligence ; Volume 88 , February , 2020 ; Haratizadeh, S ; Shouraki, S. B ; Sharif University of Technology
Elsevier Ltd
2020
Abstract
Market prediction has been an important research problem for decades. Having better predictive models that are both more accurate and faster has been attractive for both researchers and traders. Among many approaches, semi-supervised graph-based prediction has been used as a solution in recent researches. Based on this approach, we present two prediction models. In the first model, a new network structure is introduced that can capture more information about markets’ direction of movements compared to the previous state of the art methods. Based on this novel network, a new algorithm for semi-supervised label propagation is designed that is able to prediction the direction of movement faster...
Multivariate Synchronization Analysis of Brain Electroencephalography Signals: A Review of Two Methods
, Article Cognitive Computation ; Volume 7, Issue 1 , February , 2013 , Pages 3-10 ; 18669956 (ISSN) ; Sharif University of Technology
Springer New York LLC
2013
Abstract
Temporal synchronization of neuronal activity plays an important role in various brain functions such as binding, cognition, information processing, and computation. Patients suffering from disorders such as Alzheimer’s disease or schizophrenia show abnormality in the synchronization patterns. Electroencephalography (EEG) is a cheap, non-invasive, and easy-to-use method with fine temporal resolution. Modern multichannel EEG data are increasingly being used in brain studies. Traditional approaches for identifying synchronous activity in EEG are through univariate techniques such as power spectral density or bivariate techniques such as coherence. In this paper, we review two methods for...
Multifractal detrended fluctuation analysis of continuous neural time series in primate visual cortex
, Article Journal of Neuroscience Methods ; Volume 312 , 2019 , Pages 84-92 ; 01650270 (ISSN) ; Bahadorian, M ; Doostmohammadi, J ; Davoodnia, V ; Khodadadian, S ; Lashgari, R ; Sharif University of Technology
Elsevier B.V
2019
Abstract
Background: Local field potential (LFP) recordings have become an important tool to study the activity of populations of neurons. The functional activity of LFPs is usually compared with the activity of neighboring single spike neurons with sampling rates much higher than those of the continuous field potential channel (5 kHz). However, comparison of these signals generated with the lower sampling rate technique is important. New method: In this study, we provide an analysis of extracellular field potential time series using the sophisticated nonlinear multifractal detrended fluctuation analysis (MF-DFA). Using the MF-DFA, we demonstrate that the integral of the singularity spectrum is a...
Multiclass classification of patients during different stages of Alzheimer's disease using fMRI time-series
, Article Biomedical Physics and Engineering Express ; Volume 6, Issue 5 , 2020 ; Fatemizadeh, E ; Motie Nasrabadi, A ; Sharif University of Technology
IOP Publishing Ltd
2020
Abstract
Alzheimer's Disease (AD) begins several years before the symptoms develop. It starts with Mild Cognitive Impairment (MCI) which can be separated into Early MCI and Late MCI (EMCI and LMCI). Functional connectivity analysis and classification are done among the different stages of illness with Functional Magnetic Resonance Imaging (fMRI). In this study, in addition to the four stages including healthy, EMCI, LMCI, and AD, the patients have been tracked for a year. Indeed, the classification has been done among 7 groups to analyze the functional connectivity changes in one year in different stages. After generating the functional connectivity graphs for eliminating the weak links, three...
Modeling the accuracy of traffic crash prediction models
, Article IATSS Research ; Volume 46, Issue 3 , 2022 , Pages 345-352 ; 03861112 (ISSN) ; Keshavarz, S ; Pazari, P ; Safahieh, N ; Samimi, A ; Sharif University of Technology
Elsevier B.V
2022
Abstract
Crash forecasting enables safety planners to take appropriate actions before casualty or loss occurs. Identifying and analyzing the attributes influencing forecasting accuracy is of great importance in road crash forecasting. This study aims to model the forecasting accuracy of 31 provinces using their macroeconomic variables and road traffic indicators. Iran's road crashes throughout 2011–2018 are calibrated and cross-validated using the Holt-Winters (HW) forecasting method. The sensitivity of crash forecast reliability is studied by a regression model. The results suggested that the root mean square error (RMSE) of crash prediction increased among the provinces with higher and more variant...
Model-free chaos control in a chaotic henon-like system using takens embedding theory
, Article 5th International Conference on Control, Instrumentation, and Automation, ICCIA 2017, 21 November 2017 through 23 November 2017 ; Volume 2018-January , 2018 , Pages 80-85 ; 9781538621349 (ISBN) ; Salarieh, H ; Alasty, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2018
Abstract
In this paper, the problem of chaos control in a chaotic Henon-like system without using the governing equations of the system is investigated. It is also assumed that the system has only one measurable state. The time-series of the measurable state is used to stabilize chaos by a three-step method. First, using Takens embedding theory, a delayed phase space is reconstructed preserving the topological characteristics of the system. Then, an appropriate dynamic model is identified to estimate the time-series data in the reconstructed phase space. Finally, the unstable fixed point of the system is stabilized using an appropriate linear delayed feedback controller with controller gains...
Mixture of mlp-experts for trend forecasting of time series: A case study of the tehran stock exchange
, Article International Journal of Forecasting ; Volume 27, Issue 3 , 2011 , Pages 804-816 ; 01692070 (ISSN) ; Nikoo, H ; Masoudnia, S ; Yousefi, M. R ; Ghaemi, M. S ; Sharif University of Technology
2011
Abstract
A new method for forecasting the trend of time series, based on mixture of MLP experts, is presented. In this paper, three neural network combining methods and an Adaptive Network-Based Fuzzy Inference System (ANFIS) are applied to trend forecasting in the Tehran stock exchange. There are two experiments in this study. In experiment I, the time series data are the Kharg petrochemical company's daily closing prices on the Tehran stock exchange. In this case study, which considers different schemes for forecasting the trend of the time series, the recognition rates are 75.97%, 77.13% and 81.64% for stacked generalization, modified stacked generalization and ANFIS, respectively. Using the...
Minimizing the uncertainties of seismological-geotechnical source parameters using a genetic algorithm approach
, Article 9th International Conference on Computational Structures Technology, CST 2008, Athens, 2 September 2008 through 5 September 2008 ; Volume 88 , 2008 ; 17593433 (ISSN); 9781905088232 (ISBN) ; Abbasnia, R ; Bozorgnasab, M ; Eslamian, Y ; Nicknam, A ; Sharif University of Technology
Civil-Comp Press
2008
Abstract
The main purpose of this article is to estimate the seismological source parameters of the December 26, 2003, Bam earthquake Mw6.5 (Iran). The selected station is far away from the causative fault so that the synthesized ground motion would not be influenced by near source problems such as directivity effects. The well known Empirical Green's Functions (EGF) is used to synthesize the three components of main shock. The Kostrov slip model describing the entire rupture process was incorporated in the model. A generic algorithm (GA) technique is proposed for minimizing the differences between the synthesized time series and those of observed data. The estimated time series were validated by...
Long-term prediction of solar and geomagnetic activity daily time series using singular spectrum analysis and fuzzy descriptor models
, Article Earth, Planets and Space ; Volume 61, Issue 9 , 2009 , Pages 1089-1101 ; 13438832 (ISSN) ; Kamaliha, E ; Shafiee, M ; Lucas, C ; Sharif University of Technology
Abstract
Of the various conditions that affect space weather, Sun-driven phenomena are the most dominant. Cyclic solar activity has a significant effect on the Earth, its climate, satellites, and space missions. In recent years, space weather hazards have become a major area of investigation, especially due to the advent of satellite technology. As such, the design of reliable alerting and warning systems is of utmost importance, and international collaboration is needed to develop accurate short-term and long-term prediction methodologies. Several methods have been proposed and implemented for the prediction of solar and geomagnetic activity indices, but problems in predicting the exact time and...
Levels of complexity in turbulent time series for weakly and high Reynolds number
, Article Physica A: Statistical Mechanics and its Applications ; Volume 391, Issue 11 , 2012 , Pages 3151-3158 ; 03784371 (ISSN) ; Sharif University of Technology
2012
Abstract
We use the detrended fluctuation analysis (DFA), the detrended cross correlation analysis (DCCA) and the magnitude and sign decomposition analysis to study the fluctuations in the turbulent time series and to probe long-term nonlinear levels of complexity in weakly and high turbulent flow. The DFA analysis indicate that there is a time scaling region in the fluctuation function, segregating regimes with different scaling exponents. We discuss that this time scaling region is related to inertial range in turbulent flows. The DCCA exponent implies the presence of power-law cross correlations. In addition, we conclude its multifractality for high Reynold's number in inertial range. Further, we...
Iran atlas of offshore renewable energies
, Article Renewable Energy ; Volume 36, Issue 1 , January , 2011 , Pages 388-398 ; 09601481 (ISSN) ; Rahimi, R ; Sharif University of Technology
2011
Abstract
The aim of the present study is to provide an Atlas of IRAN Offshore Renewable Energy Resources (hereafter called 'the Atlas') to map out wave and tidal resources at a national scale, extending over the area of the Persian Gulf and Sea of Oman. Such an Atlas can provide necessary tools to identify the areas with greatest resource potential and within reach of present technology development. To estimate available tidal energy resources at the site, a two-dimensional tidally driven hydrodynamic numerical model of Persian Gulf was developed using the hydrodynamic model in the MIKE 21 Flow Model (MIKE 21HD), with validation using tidal elevation measurements and tidal stream diamonds from...