b a c k g r o u n d & aim: one of the common used models in time series is auto regressive integrated moving  average  (arima)  model.  arima  will  do  modeling  only  linearly.  artificial  neural networks (ann) are modern methods that be used for time series forecasting.  these models can identify non-linear relationships  among data. the breast cancer has the most mortality of cancers among...

Great Salt Lake (GSL) is the largest salt lake in the western hemisphere, the fourthlargest terminal lake in the world. The elevation of GSL has critical effect on the people who live nearby and their properties. It is crucial to build an exact model of GSL elevation time series in order to predict the GSL elevation precisely. Although some models, such as ARIMA or FARIMA (fractional auto-regre...

The paper discusses the properties of Auto-Regressive Integrated Moving Average (ARIMA) models and proceeds to estimate a model for monthly evolution annual inflation rate in Moldova from January 2013 October 2021. aim is develop relying exclusively upon historical as an additional instrument forecasting purposes. estimated explains close 97 % variation over model’s estimation period used gener...

Recent psychological and neural studies indicate that when people talk their changing facial expressions and head movements provide a dynamic cue for recognition. Therefore, both fixed facial features and dynamic personal characteristics are used in the human visual system (HVS) to recognize faces. However, most automatic recognition systems use only the static information as it is unclear how ...

Emerging Bio-engineering fields such as Brain Computer Interfaces, neuroprothesis devices and modeling and simulation of neural networks have led to increased research activity in algorithms for the detection, isolation and classification of Action Potentials (AP) from noisy data trains. Current techniques in the field of ‘unsupervised no-prior knowledge’ biosignal processing include energy ope...

Simulated models suffer intrinsically from validation and comparison problems. The choice of a suitable indicator quantifying the distance between the model and the data is pivotal to model selection. However, how to validate and discriminate between alternative models is still an open problem calling for further investigation, especially in light of the increasing use of simulations in social ...

Although it has been widely discussed in video surveillance, background subtraction is still an open problem in the context of complex scenarios, e.g., dynamic backgrounds, illumination variations, and indistinctive foreground objects. To address these challenges, we propose a simple yet effective background subtraction method that learns and maintains dynamic texture models within spatio-tempo...

Abstract: According to the chaotic features and typical fractional order characteristics of the bearing vibration intensity time series, a forecasting approach based on long range dependence (LRD) is proposed. In order to reveal the internal chaotic properties, vibration intensity time series are reconstructed based on chaos theory in phase-space, the delay time is computed with C-C method and ...