Introduction: Climate change in the current century is an important environmental challenge facing the world. Increase in atmospheric concentration of greenhouse gases such as CO2 as a result of human activities has caused a change in a number of hydroclimatic parameters. Climate change and global warming are the most important issues that have attracted many attentions in recent years. Climatic changes have interpreted as significant changes in average weather over a long period (Salari and ghandomkar, 2012). …

We provide a framework for the study of statistical quantities related to the Hurst phenomenon when the data are non-precise with bounded support.

Fractional Gaussian noise (fGn) is an important and widely used self-similar process, which is mainly parametrized by its Hurst exponent (H) to specify its long-term persistence (LTP). Many researchers have proposed methods for estimating the Hurst exponent of fGn. But there is only a few researches that has compared different methods for different time series covering different length of records. In this paper, we have compared the performance of 7 different methods covering rescaled range (R/S), 3 different approaches of aggregated standard deviation method (ASD[0], ASD[rec], ASD[opt]), variance method (VAR), and 2 approaches of autocorrelation method (r[1] and r[2]). Seven different time series including Mashhad annual temperature (127 and 66 years), yearly minimal water levels at the Nile River (660 years), two global phenomena of North Atlantic Oscillation (NAO) (62 years) and two Pacific Decadal Oscillation (PDO) series (112 and 331 years), and concentration of atmospheric CO2 measured at Mauna Loa, Hawaii (55 years) were considered. The results showed that NAO and CO2 series do not have LTP (H<0.5). The VAR method failed to satisfy the scaling relationship, r[1] and r[2] failed to have good correlation, ASD[rec] failed to work under T66 and CO2 series, both ASD[rec] and ASD[opt] yielded inconsistently high H and standard deviation. R/S and aggregated standard deviation showed to be suitable methods for computing H. It was shown that H decreases as record length increases where includes historic data.

The humans’ heart is a chaotic system so use of fractal dimension to identify cardiac arrhythmias has been considered. Cardiac arrhythmias are prevalent diseases that is very important to be diagnosed. Hurst index which is calculated using rescaled range analysis method, is used as a criterion to evaluate chaotic systems and to quantify the fractal dimensions. Previous studies have shown that classical Hurst index is not appropriate for classification of cardiac arrhythmias because not only selection of algorithm parameters affect the value of determined Hurst index, but also it significantly varies as the heart rate changes. In this paper, modified multiple Hurst index has been proposed to classify the cardiac arrhythmias.The presented index is resistant against changes in heart rate and can be used to identify appropriate features to classify the cardiac arrhythmias.80 signal from four types of ECG beats (normal, left bundle branch block, right bundle branch block and atrial premature beats) obtained from the MIT-BIH Arrhythmia dataset has been used to validate the algorithm. Results show that this method is able to detect normal rhythm and right bundle branch block (RBBB), left bundle branch block (LBBB) and atrial premature complex (APC) arrhythmias with accuracy of 100%, 96.25% and 88.75% using artificial neural network, k nearest neighbor and LDA classifiers respectively.

On all stock exchange of the world famous considerably derivatives are traded. Options are a patent for its owner, the most important are derivatives. The best economic tool management risk, the use of the option contract. It is obvious that at the conclusion of each contract, determining the price is the main element, Thus providing fair prices for securities is very important. In this study, the option pricing under fractional Black-Scholes is survived.The fractional Black-Scholes is based on fractional Brownian motion with Hurst parameter. The Hurst exponent be associated with fractal dimension and self-similary as an indicator of long-term memory is used in the process of stock prices. The aim to provide a pricing formula for European options with transaction costs is an approximate answer fractional pricing equation with transaction costs by way of variational iteration method is checked. The transaction costs contain fixed costs, a cost proportional to the volume traded and a cost proportional to the value traded. Expected, the price of the European option decreases as the Hurst exponent increases.To achieve this goal, we estimate (Hurst parameter time series), on the real data to the desired result, the option price reduction reached. Comparing results show that the actual prices by fractional black-scholes model, is closer to the actual results.

Objective: This study is the first to examine the issue of time-varying long-term memory in the Tehran Stock Exchange, using a new efficiency index through a rolling window technique. To test the robustness of the results, this estimation technique is repeated with time windows with 5-day shifts. Furthermore, the wild bootstrap versions of the Automatic Portmanteau test (AQ) and the Automatic Variance Ratio test (AVR) have been performed with 14-and 5-day shifts. Method: The sample employed in this paper consists of daily observations on the Tehran Stock Exchange Index (TEPIX), covering the period from December 2008 to October 2019, making up a total of 2621 observations. The TEPIX series are collected from the Rahavard Novin software. The hypotheses are analyzed by Excel, EViews, R, and MATLAB software. Results: The findings show that in the Tehran Stock Exchange the estimated values of the generalized Hurst exponents (GHE) for all windows with 14-day shifts are over the efficiency indicator 0/5. Therefore, a kind of long-term memory exists on the Tehran Stock Exchange. Moreover, a high degree of inefficiency ratio is observed in the market. Furthermore, the Tehran Stock Exchange does not become more efficient over time. Finally, the results from the time windows with 5-day shifts as well as wild bootstrap versions of the AQ and AVR tests with 14-and 5-day shifts indicate that the previously-mentioned empirical results are robust. The findings from the study provide important implications for investors, portfolio managers, and policy-makers.

Background and Aim: Ecosystems disturbances induced from social factors affect the environmental changes, temperature, evapotranspiration, runoff production and flow rate. In this regard, Hurst index has been used to analyze changes in hydrological processes due to various factors. The Hurst index is known as an important feature for analyzing hydrological effects. One of the most appropriate tests for long-term memory detection is the rescaling range (R/S) test. The R/S test makes it possible to calculate the self-similarity parameter H (Hurst), which measures the severity of long-term dependence over a time series. Towards this, the present study was conducted to determine the long-term memory using Hurst index for precipitation and discharge time series throughout some selected stations in Ardabil Province, NW Iran. Method: In the present study, long-term memory for annual precipitation and discharge time series (1991-2013) in 17 rain gauges stations and28 river gauge stations in Ardabil Province was assessed. The Hurst index computational values were classified into five categories from very weak to very strong in terms of dependency and scale of instability in the time series. Spatial correlation analysis of Hurst index was performed using Moran index. The Hurst index values were then interpolated by the inverse weighted distance (IDW) method in Arc Map 10. 8. Results: The results showed that the among 17 study stations, 23. 53, 29. 41, 17. 65, and 23. 53% respectively were classified in the stability scale of very weak (0. 50

Today, the occurrence of dust storms, in addition to having a direct impact on people's lives, has adversely affected the agricultural sector, including agronomy, horticulture, natural resources and the environment. This study was carried out to investigate the trend of frequency changes of days with dust storms and its relationship with Standardized Precipitation Index (SPI), using hourly and daily dust data and monthly rainfall data of 21 selected synoptic station in the west and southwest of the country with a seasonal scale over a 25 years (1990-2014) statistical period. After quality controlling all dust data for abnormality, using Kolmogorov-Smirnov test, and also measuring the long-term memory of time series using the Hurst Coefficient, non-parametric Mann-Kendall and Spearman tests were used at a 95% confidence level to examine the trend of abnormal data. Then, the seasonal SPI drought index was calculated in the proposed stations and its trend was analyzed by parametric linear regression test method. Also, the zoning of the Mann-Kendall statistics and the linear regression of the variables were performed by IDW method in ArcGIS software. Then, to investigate the climatic relationship with dust storms, stations with SPI index and also variable frequency of days associated with dust storms had a significant trend (dust storms in both Mann-Kendall and Spearman methods and SPI index in the method of linear regression), were analyzed by Pearson correlation technique. The results showed that out of a total 21 series of seasonal data; the stations of Hamedan (Nozheh), Ilam, Islamabade-Gharb, Keramnshah, Sarpole-Zahab, Abadan, Bandare-Mahshahr, Bostan, Dezful, Masjedsoleyman, Safiabad, Dogonbadan, Sanandaj, and Khorramabad have a high correlation between standard precipitation climatic index and the frequency of dusty days. So that the highest correlation between the number of dusty days and SPI drought index was attributed to Dezful, Bostan and Masjedsoleyman stations with the Pearson Coefficients of-0. 920,-0. 913 and-0. 911 and P-Values of 0. 002, 0. 025 and 0. 044, respectively. The results of this study could be useful in managing the consequences of dust storms in the study areas.

External fluted feed rolls are commonly used in grain drills. The fluted feed roll meters a volume of seeds and does not singulate the seeds as do the precision planters; therefore, there will be inherent variation in the number of seeds delivered per unit of time. This research was conducted to investigate the effect of seed meter drive shaft and ground speeds and outlet positions in a grain drill on the variation in wheat seeding rate and seed flow evenness from various outlets in short time intervals using the Coefficient of variation (CV) and the nonuniformity Coefficient (NUC). In this study, a grain drill with straight fluted metering mechanisms was evaluated on a test rig. Two rotational speeds of 16 and 23 rpm and two speeds of 2.5 and 3.6 km h-1 were selected for the seed meter drive shaft and the movement of the test rig, respectively. The results showed that, for a given test rig speed, the seeding rate changed proportional to the seed meter drive shaft speed, whereas for a constant speed of seed meter drive shaft, the seeding rate decreased as the speed of the test rig increased. Also, the seeding rates from all outlets were not the same. Outputs of some of the outlets were autocorrelated, for which selecting 12 or 24 seed samples randomly out of 36 consecutive samples were not essentially non-autocorrelated. Increasing rotational speed of seed meter drive shaft significantly increased the Coefficient of uniformity of all outlets. The seed breakage was significantly increased with the speed of seed meter drive shaft. The CV and NUC exhibited similar trends. It can, therefore, be concluded that in grain drill evaluation, either CV or NUC could be used as an index of seed flow non-uniformity.