Search results for "A-weighting"
showing 4 items of 4 documents
Improved Neural Networks with Random Weights for Short-Term Load Forecasting.
2015
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. Eight factors are selected as the inputs. A mutual information weighting algorithm is then used to allocate different weights to the inputs. The neural networks with random weights and kernels (KNNRW) is applied to approximate the nonlinear function between the selected inputs and the daily maximum load…
Market Timing with a Robust Moving Average
2015
In this paper we entertain a method of finding the most robust moving average weighting scheme to use for the purpose of timing the market. Robustness of a weighting scheme is defined its ability to generate sustainable performance under all possible market scenarios regardless of the size of the averaging window. The method is illustrated using the long-run historical data on the Standard and Poor's Composite stock price index. We find the most robust moving average weighting scheme, demonstrates its advantages, and discuss its practical implementation.
Automatically Modeling Linguistic Categories in Spanish
2010
This paper presents an approach to process Spanish linguistic categories automatically. The approach is based in a module of a prototype named WIH (Word Intelligent Handler), which is a project to develop a conversational bot. It basically learns category usage sequence in a sentence. It extracts a weighting metric to discriminate most common structures in real dialogs. Such a metric is important to define the preferred organization to be used by the robot to build an answer.