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A Machine Learning Model for Stock Market Prediction
The proposed model is based on the study of historical data, technical indicators and optimizing LS-SVM with PSO algorithm to be used in the prediction of daily stock prices. -
Algorithmic Trading Using Continuous Action Space
Price movement prediction has always been one of the traders concerns in financial market trading. In order to increase their profit, they can analyze the historical data and... -
PANGAEA (Data Publisher for Earth & Environmental Science)
Imported
Daily mean-sea-level atmospheric pressure from 1841 to 2018 at Trieste, Italy
This dataset has no description
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PANGAEA (Data Publisher for Earth & Environmental Science)
Imported
Monthly mean-sea-level atmospheric pressure from 1841 to 2018 at Trieste, Italy
This dataset has no description
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PANGAEA (Data Publisher for Earth & Environmental Science)
Imported
Annual mean-sea-level atmospheric pressure from 1841 to 2018 at Trieste, Italy
This dataset has no description
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PANGAEA (Data Publisher for Earth & Environmental Science)
Imported
Mean-sea-level atmospheric pressure from 1841 to 2018 at Trieste, Italy
A time series of mean-sea-level atmospheric pressure was built from observations performed in Trieste from 1 January 1841 to 31 December 2018. Data until 1877 come from direct... -
PANGAEA (Data Publisher for Earth & Environmental Science)
Imported
Meteorological records of the Malaspina Expedition (1789-1794)
Meteorological observations made in the Malaspina Expedition from 1789 to 1794 have been retrieved. Variables such as air temperature, atmospheric pressure, wind direction and...