Symbolic Data Analysis (SDA) provides a framework for the representation and analysis of
data that comprehends inherent variability. While in Data Mining and classical Statistics the …

Interval time series forecasting can be used for forecasting special symbolic data comprising
lower and upper bounds and plays an important role in handling the complexity, instability …

With photovoltaic (PV) penetration increasing, PV-output prediction has become a research
hotspot. Due to the close correlation between PV-output fluctuation and weather conditions …

This paper introduces symbolic data analysis, explaining how it extends the classical data
models to take into account more complete and complex information. Several examples …

In recent years, model averaging, by which estimates are obtained based on not one single
model but a weighted ensemble of models, has received growing attention as an alternative …

Since the emergence of Bitcoin, cryptocurrencies have grown significantly, not only in terms
of capitalization but also in number. Consequently, the cryptocurrency market can be a …

Practitioners and policy makers rely on accurate crude oil forecasting to avoid price risks
and grasp investment opportunities, but the core of existing predictive models for such prices …

A system for reservoir formation characterization with a downhole wireless telemetry system,
including at least one sensor disposed along a tubular body; at least one sensor …

Forecasting with Interval and Histogram Data: Some Financial Applications Page 1
November 3, 2010 17:15 C7035 C7035C010 10 Forecasting with Interval and Histogram …

A method of transmitting data in a wellbore uses a signal receiver that is run into the
wellbore on a working string. The signal receiver receives wireless signals from receiver …