An effective forecasting model for short-term load plays a significant role in promoting the management efficiency of an electric power system. This paper proposes a new forecasting model based on the improved neural networks with random weights (INNRW). The key is to introduce a weighting technique to the inputs of the model and use a novel neural network to forecast the daily maximum load. Ei...

It is vital to ensure highway structures to cater for increasing demand in transport capacity. This involves the precise estimation of structural load-carrying capacity to withstand potential maximum load effects in residual lifetime. The scope of this research thus addresses estimation of traffic load effect. Many different methods have been used to model extreme traffic load effects on bridge...

The local dynamic stability of trunk movements was assessed during repetitive lifting using nonlinear Lyapunov analyses. The goal was to assess how varying the load-in-hands affects the neuromuscular control of lumbar spinal stability. Thirty healthy participants (15M, 15F) performed repetitive lifting at 10 cycles per minute for three minutes under two load conditions: zero load and 10% of eac...

This week, we consider a very simple load-balancing problem. Suppose you have n machines and m jobs. You want to assign the jobs to machines such that all machines have approximately the same load. Of course, there is a solution with load at most dmn e on every machine, but that requires central coordination. Without central coordination, the easiest thing you can do is let each job drawn one m...