Sentence examples for methodologies to forecast from inspiring English sources

Among other financial variables, stock market indices have received significant attention, and many researchers such as Atsalakis and Valavanis (2009), Vanstone and Finnie (2009), and Leung et al. (2000) proposed different methodologies to forecast them.

With recent developments in seasonal (1 3 months) weather forecast skill, such as those from the latest version of the UK Met Office global seasonal forecast system (GloSea5), there is now an opportunity to use similar methodologies to forecast groundwater levels in more slowly responding aquifers on seasonal timescales.

Once candidate metrics are identified and assembled into the tool, the team will use predictive modeling methodologies to forecast the impact of different thresholds for critical care admission on patient outcomes and also on facility-level and regional capacity and functioning.

Therefore, this paper presents a methodology to forecast trends in the material composition of waste streams.

This study presents a methodology to forecast diurnal cooling load energy consumption for institutional buildings using data driven techniques.

Gudarzi Farahani et al. (2012) applied a Bayesian vector auto-regressive methodology to forecast Iran's energy consumption and discussed its potential implications.

We applied the same methodology to forecast the average SV over the period 2010 2015, now based on a steady flow derived from a longer time-series of fifty monthly VO SV models using CHAMP data from 2004.5 2009.5.

The objective of the present study is to develop a methodology to forecast the human exposure of the Portuguese population based on the air quality forecasting system available and validated for Portugal since 2005.

Afterwards, it proposes a methodology to forecast a series of economic scenarios to quantify the feasibility of installing and running the HDA process (according to a dynamic interpretation of the economic potentials proposed by Douglas, 1988).

This study develops a novel hybrid methodology to forecast the patients' demand for different key resources in OPD, by combining a new feature selection method and a deep learning approach.

The system presented here uses the Case-Based Reasoning (CBR) methodology to forecast the presence or absence of oil slicks in certain open sea areas after an oil spill.