nonlinear static procedure (nsp) is a common technique to predict seismic demands on various building structures by subjecting a monotonically increasing horizontal loading (pushover) to the structure. therefore, the pushover analysis is an important part of each nsp. accordingly, the current paper aims at investigating the efficiencyof various algorithms of lateral load patterns applied to the...

Model predictive controller is widely used in industrial plants. Uncertainty is one of the critical issues in real systems. In this paper, the direct adaptive Simplified Model Predictive Control (SMPC) is proposed for unknown or time varying plants with uncertainties. By estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly ca...

Satellite Image Time Series (SITS) have become more accessible in recent years and SITS analysis has attracted increasing research interest. Given that labeled training samples are time effort consuming to acquire, clustering or unsupervised methods need be developed. Similarity measure is critical for clustering, however, currently established represented by Dynamic Warping (DTW) still exhibit...

Simple exponential smoothing (SES) methods are the most commonly used methods in forecasting and time series analysis. However, they are generally insensitive to non-stationary structural events such as level shifts, ramp shifts, and spikes or impulses. Similar to that of outliers in stationary time series, these non-stationary events will lead to increased level of errors in the forecasting pr...

Dynamically Adaptive Systems (DASs) adjust their behaviour at runtime to tolerate changes in context. With potentially incomplete or inaccurate knowledge of an operating environment, tailoring specific behavioural adjustments to individual contextual changes is a time-consuming and errorprone process. i* models of a DAS' behavioural adjustments can aid understanding, and can form part of the sp...

This paper addresses the issue of employing space-time adaptive processing (STAP) prior to doppler filtering in radar systems. When STAP beamformer processing is applied to spatial/temporal samples that include successive radar pulses, the adaptive weights can cause modulation (spreading) of the desired target doppler. In this paper, a linearly constrained adaptive beamformer is proposed that e...

A modified method for satellite attitude control system in presence of novel actuators is proposed in this paper. The attitude control system is composed of three fluidic momentum controller (FMC) actuators that are used to control Euler angles and their dynamics is considered in satellite attitude equations as well. L1 adaptive control is utilized for satellite three-axial ...

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Monitoring forest disturbances using remote sensing data with high spatial and temporal resolution can reveal relationships between forest disturbances and forest ecological patterns and processes. In this study, we fused Landsat data at high spatial resolution (30 m) with 8-day MODIS data to produce high spatial and temporal resolution image time-series. The Spatial Temporal Adaptive Algorithm...

A new approach to the problem of time series classi cation is discussed in this paper. A new adaptive classi cation scheme is introduced and compared with existing approaches, such as the Bayesian approach and the Incremental Credit Assignment approach. Simulation results are included to demonstrate the e ectiveness of the new methodology.