Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Adrian Letchford"'
Publikováno v:
PLoS ONE, Vol 11, Iss 2, p e0149025 (2016)
Vast records of our everyday interests and concerns are being generated by our frequent interactions with the Internet. Here, we investigate how the searches of Google users vary across U.S. states with different birth rates and infant mortality rate
Externí odkaz:
https://doaj.org/article/db30720fbf2840e18ee9c3cd5d1c3335
Publikováno v:
Royal Society Open Science, Vol 2, Iss 8 (2015)
Vast numbers of scientific articles are published each year, some of which attract considerable attention, and some of which go almost unnoticed. Here, we investigate whether any of this variance can be explained by a simple metric of one aspect of t
Externí odkaz:
https://doaj.org/article/832c41ea92174cb5adb039e64e29d156
Publikováno v:
PLoS ONE
PLoS ONE, Vol 11, Iss 2, p e0149025 (2016)
PLoS ONE, Vol 11, Iss 2, p e0149025 (2016)
Vast records of our everyday interests and concerns are being generated by our frequent interactions with the Internet. Here, we investigate how the searches of Google users vary across U.S. states with different birth rates and infant mortality rate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5fc8e8e3f8a62e8b92d99cbc424e202e
http://wrap.warwick.ac.uk/78429/1/WRAP_journal.pone.0149025.PDF
http://wrap.warwick.ac.uk/78429/1/WRAP_journal.pone.0149025.PDF
Publikováno v:
International Journal of Machine Learning and Cybernetics. 4:149-154
Modeling of financial time series with artificial intelligence is difficult due to the random nature of the data. The moving average filter is a common and simple form of filter to reduce this noise. There are several of these noise reduction methods
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b890f878aa2654afbdbd3d357e4bab1e
https://doi.org/10.1007/s13042-012-0081-0
https://doi.org/10.1007/s13042-012-0081-0
Publikováno v:
WebSci
Decision makers depend on socio-economic indicators to shape the world we inhabit. Reports of these indicators are often delayed due to the effort involved in gathering and aggregating the underlying data. Our increasing interactions with large scale
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa9bdc2b8bf1af8fa14004288afea1bf
http://wrap.warwick.ac.uk/79613/1/WRAP_Alis_et_al-2015-ACM_WebSci.pdf
http://wrap.warwick.ac.uk/79613/1/WRAP_Alis_et_al-2015-ACM_WebSci.pdf
Publikováno v:
Royal Society Open Science, Vol 2, Iss 8 (2015)
Royal Society Open Science
Royal Society Open Science
Vast numbers of scientific articles are published each year, some of which attract considerable attention, and some of which go almost unnoticed. Here, we investigate whether any of this variance can be explained by a simple metric of one aspect of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60f6a073f18d64e26532f712c946e048
https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.150266
https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.150266
Publikováno v:
ICPR
Asset prices fluctuate up and down chaotically. Traders, investors and fund managers comb the chaos for exploitable patterns with methods such as moving averages from the realm of technical analysis. In this paper we focus on linear moving averages w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26d81ed07dd0182895f4176ca307c2bb
https://doi.org/10.1109/icpr.2014.188
https://doi.org/10.1109/icpr.2014.188
Publikováno v:
AI 2011: Advances in Artificial Intelligence ISBN: 9783642258312
Australasian Conference on Artificial Intelligence
Australasian Conference on Artificial Intelligence
Modeling of financial time series data by methods of artificial intelligence is difficult because of the extremely noisy nature of the data. A common and simple form of filter to reduce the noise originated in signal processing, the finite impulse re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1196ac50954d1fcf905316afa4c26b4
https://doi.org/10.1007/978-3-642-25832-9_8
https://doi.org/10.1007/978-3-642-25832-9_8
Publikováno v:
Web of Science
IJCNN
IJCNN
This paper proposes a new and optimal moving average model that reduces the problems of alternative models. The random (noisy) nature of financial time series creates difficulties when modelling with any method. The most common linear model to deal w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b2fb192e11b50828b7683894ebce7f4
https://publons.com/wos-op/publon/51980187/
https://publons.com/wos-op/publon/51980187/