n 6 SSA 15.10 MMFA 2.04 The design results obtained by the MMFA algorithm are summarised with those by the SSA algorithm by Haines [6] in Table 1. It should be noted that they have the same quality of solutions. In this experiment, = 5.0, h = 0.98, T, = 5 x 1 t 8 , and N, = 100 were used. Fig. 1 shows the learning curve of the objective function in U and the changes of the average states for al...

The static single-assignment (SSA) form of a program provides data flow information in a form which makes some compiler optimizations easy to perform. In this paper we present a new, simple method for converting to SSA form, which produces correct solutions for nonreducible control-flow graphs, and produces minimal solutions for reducible ones. Our timing results show that, despite its simplici...

An optimal, polynomial-time algorithm for interprocedural register allocation in high-level synthesis and ASIP design is presented. The algorithm determines the minimum number of registers required to store all scalar variables in an application without spilling any to memory. Although an optimal polynomialtime algorithm has been presented in the past for individual procedures in Static Single ...

accurate and effective electricity price forecasting is critical to market participants in order to make an appropriate risk management in competitive electricity markets. market participants rely on price forecasts to decide on their bidding strategies, allocate assets and plan facility investments. however, due to its time variant behavior and non-linear and non-stationary nature, electricity...

Brachytherapy to treat prostate cancer uses transrectal ultrasound to guide transperitoneal needle implantation of titanium-shelled radioactive seeds. The standard external dimensions of all seeds used for prostate brachytherapy is 4.5 mm in length and 0.85 mm in diameter. Gland deformation and needle deflection during implantation allow seed-placement errors that cause suboptimal dosimetry. Co...

applying nonlinear models to estimation and forecasting economic models are now becoming more common, thanks to advances in computing technology. artificial neural networks (ann) models, which are nonlinear local optimizer models, have proven successful in forecasting economic variables. most ann models applied in economics use the gradient descent method as their learning algorithm. however, t...

We present non-standard denotational specifications of the SSA form and of its conversion processes from and to imperative programming languages. Thus, we provide a strong mathematical foundation for this intermediate code representation language used in modern compilers such as GCC or Intel CC. More specifically, we provide (1) a new functional approach to SSA, the Static Single Assignment for...

this paper presents a probabilistic optimal power flow (popf) algorithm considering different uncertainties in a smart grid. different uncertainties such as variation of nodal load, change in system configuration, measuring errors, forecasting errors, and etc. can be considered in the proposed algorithm. by increasing the penetration of the renewable energies in power systems, it is more essent...

Background: For biochemical systems, where some chemical species are represented by small numbers of molecules, discrete and stochastic approaches are more appropriate than continuous and deterministic approaches. The continuous deterministic approach using ordinary differential equations is adequate for understanding the average behavior of cells, while the discrete stochastic approach accurat...

A recurrent neural network is studied in this paper. A multi–context–recurrent neural network is defined and trained with back propagation, and is then applied to the short–term energy load forecasting task. The idea is to predict a daily maximum load for an arbitrary month ahead. A multi–context–recurrent neural network model was simulated and trained with different training sets to predict th...