abstract one of the major factors on the amount of water resources is river flow which is so dependent to the hydrologic and meteorologic phenomena. simulation and forecasting of river flow makes the decision maker capable to effectively manage the water resources projects. so, simulation and forecasting models such as artificial neural networks (anns) are commonly used for simulation and predi...

This paper looks at forecasting daily exchange rates for the United Kingdom, European Union, and China. Here, the authors evaluate the forecasting performance of neural networks (NN), vector singular spectrum analysis (VSSA), and recurrent singular spectrum analysis (RSSA) for forecasting exchange rates in these countries. The authors find statistically significant evidence based on the RMSE, t...

Abs t r ac t . Static single assignment (SSA) form is an intermediate representation that is well suited for solving many data flow optimization problems. However, since the standard algorithm for building SSA form is exhaustive, maintaining correct SSA form throughout a multi-pass compilation process can be expensive. In this paper, we present incremental algorithms for restoring correct SSA f...

Synthetic aperture radar (SAR) has proven to be a powerful remote sensing instrument for underground and obscured object detection. However, SAR echoes are often contaminated by radio frequency interferences (RFI) from multiple broadcasting stations. Essentially, RFI suppression problem is one-dimensional stationary time series denoising problem. This article proposed a novel RFI suppression al...

this study focuses on the forecasting of energy demands of residential and commercial sectors using linear and exponential functions. the coefficients were obtained from genetic and particle swarm optimization (pso) algorithms. totally, 72 different scenarios with various inputs were investigated. consumption data in respect of residential and commercial sectors in iran were collected from the ...

Increasing electricity demand in Java-Madura-Bali, Indonesia, must be addressed appropriately to avoid blackout by determining accurate peak load forecasting. Econometric approach may not be sufficient to handle this problem due to limitation in modelling nonlinear interaction of factors involved. To overcome this problem, Elman and Jordan Recurrent Neural Network based on Levenberg-Marquardt l...

We consider the problem of power demand forecasting in residential micro-grids. Several approaches using ARMA models, support vector machines, and recurrent neural networks that perform one-step ahead predictions have been proposed in the literature. Here, we extend them to perform multi-step ahead forecasting and we compare their performance. Toward this end, we implement a parallel and effici...

Verification is essential for assuring the integrity of a Java virtual machine when executing untrusted code. Existing verifiers decide whether or not a given bytecode program is safe. In contrast, we introduce the concept of proofing. Proofing does not change the semantics of programs that would have passed the original bytecode verifier. For programs that would have failed verification, our a...

Array SSA form is a version of SSA form that captures precise element-level data flow information for array variables. As an example of program analysis using Array SSA form, we presented a conditional constant propagation algorithm that can lead to discovery of a larger set of constants than previous algorithms that analyze only scalar variables [7]. As an example of program transformation usi...