The paper presents a spatio-temporal wind speed forecasting algorithm using Deep Learning (DL) and in particular, Recurrent Neural Networks (RNNs). Motivated by recent advances in renewable energy integration and smart grids, we apply our proposed algorithm for wind speed forecasting. Renewable energy resources (wind and solar) are random in nature and, thus, their integration is facilitated wi...

Static Single Assignment form is an intermediate representation, that uses -functions to merge values at each confluent points of the control flow graph. functions are not machine instructions and should be renamed back to move operations when translating out-of-SSA form. Without a coalescing algorithm, out-of-SSA translation generates many move instructions. In this paper we propose an extensi...

OBJECTIVE To explore the association of non-organ-specific autoimmune responses against three distinct Ro antigen-related reactivities (Ro52, Ro60, p57) with a history of pregnancy loss in women with autoimmune disorders. Materials and methods. Seventy unselected anti-Ro/SSA-positive women were studied in a retrospective cohort study. Forty anti-Ro/SSA-positive women were age matched to an equa...

We propose a novel approach for constructing Singular Spectrum Analysis (SSA) forecast based on estimating new coefficients of Linear Recurrent Formula. The results indicate that the proposed method is more reliable in comparison to the widely used approaches that were proposed along with SSA. We conduct simulation studies to compare the relative performance of the new method with the existing ...

In response to the shortcomings of Salp Swarm Algorithm (SSA) such as low convergence accuracy and slow speed, a Multi-Strategy-Driven (MSD-SSA) was proposed. First, food sources or random leaders were associated with current bottle sea squirt at beginning iteration, which Levy flight walk crossover operators small probability added improve global search ability jump out local optimum. Secondly...

23 January 2016, Vol. 106, No. 1 Heart failure (HF) is a major public health challenge, accounting for significant morbidity and premature mortality globally, including in sub-Saharan Africa (SSA).[1] Owing to high prevalence and poor clinical outcomes, HF is associated with recurrent hospitalisation and substantial healthcare expenditure.[2] In contrast to Western countries, where HF is consid...

Full collaboration in supply chains is an ideal that the participant firms should try to achieve. However, a number of factors hamper real progress in this direction. Therefore, there is a need for forecasting demand by the participants in the absence of full information about other participants’ demand. In this paper we investigate the applicability of advanced machine learning techniques, inc...

To improve the accuracy of short-term wind speed forecasting, we proposed a Gated Recurrent Unit network forecasting method, based on ensemble empirical mode decomposition and Grid Search Cross Validation parameter optimization algorithm. In this study, first, in process decomposing, set was introduced to divide time series into high-frequency modal, low-frequency trend using Pearson correlatio...

Self-modifying policies (SMPs) trained by the success-story algorithm (SSA) have been successfully applied to various diicult reinforcement learning tasks (Schmidhuber et al. 1997a, 1997b). Here we present new results on an application where two cooperating/competing an-imats have to solve a complex version of the prisoner's dilemma. 1 Overview SMP/SSA. An animat's modiiable components that det...