نتایج جستجو برای: exponential moving average ema
تعداد نتایج: 531976 فیلتر نتایج به سال:
روندهای فصلی و الگوهای قابل توجیه در دادههای کشوری نظام مراقبت بیماری سرخک: رویکردهای شناسایی و حذف
Background & Objectives: Knowledge of the presence of seasonal trends and other explainable patterns in the prediagnostic data sources and removing such patterns before applying outbreak detection methods seem very important. This study aimed to detect and remove the explainable patterns such as seasonality, day-of-week (DOW) and holiday effects of the daily counts of suspected cases of measles...
This paper proposes a novel simultaneous localization and mapping (SLAM) approach, namely Attention-SLAM, which simulates human navigation mode by combining visual saliency model (SalNavNet) with traditional monocular SLAM. Firstly SalNavNet is proposed. In SalNavNet, we introduce correlation module propose an adaptive Exponential Moving Average (EMA) module. These modules mitigate the center b...
Abstract: The realization of credit proposed by customers is one the essential factors for a bank. Moreover, especially during Covid-19 pandemic, shows business conditions prospective borrowers, whether they are in good condition or not. So, it crucial to predict how many new debtors will achieve. In this article, forecasting number uses Simple Moving Average and Double Exponential Smoothing me...
In order to improve the accuracy of all kinds of information in the cash business and enhance the linkage between cash inventory forecasting and cash management information in the commercial bank, the first moving average prediction method, the second moving average prediction method, the first exponential smoothing prediction and the second exponential smoothing prediction methods are adopted ...
The sample autocorrelation function (acf) of a stationary process has played a central statistical role in traditional time series analysis, where the assumption is made that the marginal distribution has a second moment. Now, the classical methods based on acf are not applicable in heavy tailed modeling. Using the codifference function as dependence measure for such processes be shown it be as...
Meteorological stations usually contain some missing data for different reasons.There are several traditional methods for completing data, among them bivariate and multivariate linear and non-linear correlation analysis, double mass curve, ratio and difference methods, moving average and probability density functions are commonly used. In this paper a blended model comprising the bivariate expo...
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