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The doomsday argument ( DA ), or Carter catastrophe, is a probabilistic argument that claims to predict the future population of the human species based on an estimation of the number of humans born to date. The doomsday argument was originally proposed by the astrophysicist Brandon Carter in 1983, [1] leading to the initial name of the Carter ...
Predicted date Claimant Notes After 2025 Alice A. Bailey: In January 1946, the New Age Theosophical guru prophesied that Christ would return "sometime after AD 2025": 530 (Theosophists identify "Christ" as being identical to a being they call Maitreya) to inaugurate the Age of Aquarius; thus, this event will be, according to Bailey, the New Age equivalent of the Christian concept of the Second ...
3 Oct 1988. Edgar C. Whisenant. Whisenant predicted in his book 88 Reasons Why the Rapture Could Be in 1988 that the rapture of the Christian Church would occur between September 11 and 13, 1988. After his September predictions failed to come true, Whisenant revised his prediction date to October 3.
Definition. Predictive analytics is a set of business intelligence (BI) technologies that uncovers relationships and patterns within large volumes of data that can be used to predict behavior and events. Unlike other BI technologies, predictive analytics is forward-looking, using past events to anticipate the future. [4]
Jehovah's Witnesses. Watch Tower Bible and Tract Society publications have made a series of predictions about Christ's Second Coming and the advent of God's Kingdom, each of which has gone unfulfilled. Almost all the predictions for 1878, 1881, 1914, 1918 and 1925 were later reinterpreted as a confirmation of the eschatological framework of the ...
The estimated date of delivery ( EDD ), also known as expected date of confinement, [1] and estimated due date or simply due date, is a term describing the estimated delivery date for a pregnant woman. [2] Normal pregnancies last between 38 and 42 weeks. [3] Children are delivered on their expected due date about 4% of the time.
In general, dark energy is a catch-all term for any hypothesized field with negative pressure, usually with a density that changes as the universe expands. Some cosmologists are studying whether dark energy which varies in time (due to a portion of it being caused by a scalar field in the early universe) can solve the crisis in cosmology.
In machine learning, backpropagation is a gradient estimation method used to train neural network models. The gradient estimate is used by the optimization algorithm to compute the network parameter updates. It is an efficient application of the Leibniz chain rule (1673) [1] to such networks. [2]
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