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  2. BCM theory - Wikipedia

    en.wikipedia.org/wiki/BCM_theory

    This model is a modified form of the Hebbian learning rule, ˙ =, and requires a suitable choice of function to avoid the Hebbian problems of instability. Bienenstock at al. [ 6 ] rewrite ϕ ( c ) {\displaystyle \phi (c)} as a function ϕ ( c , c ¯ ) {\displaystyle \phi (c,{\bar {c}})} where c ¯ {\displaystyle {\bar {c}}} is the time average ...

  3. Nonlinear autoregressive exogenous model - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_autoregressive...

    In time series modeling, a nonlinear autoregressive exogenous model (NARX) is a nonlinear autoregressive model which has exogenous inputs. This means that the model relates the current value of a time series to both: past values of the same series; and

  4. Predictive modelling - Wikipedia

    en.wikipedia.org/wiki/Predictive_modelling

    The first clinical prediction model reporting guidelines were published in 2015 (Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD)), and have since been updated. [10] Predictive modelling has been used to estimate surgery duration.

  5. Bitcoin price prediction model running ‘like clockwork’ as ...

    www.aol.com/news/bitcoin-price-prediction-model...

    Average forecast from analysts put bitcoin reaching north of $100,000 in 2024, though some warn of history repeating itself Bitcoin price prediction model running ‘like clockwork’ as crypto ...

  6. Electricity price forecasting - Wikipedia

    en.wikipedia.org/wiki/Electricity_price_forecasting

    As Nowotarski and Weron [84] have recently shown, decomposing a series of electricity prices into a long-term seasonal and a stochastic component, modeling them independently and combining their forecasts can bring - contrary to a common belief - an accuracy gain compared to an approach in which a given model is calibrated to the prices themselves.

  7. Neural network - Wikipedia

    en.wikipedia.org/wiki/Neural_network

    In 1949, Donald Hebb described Hebbian learning, the idea that neural networks can change and learn over time by strengthening a synapse every time a signal travels along it. [ 8 ] Artificial neural networks were originally used to model biological neural networks starting in the 1930s under the approach of connectionism .

  8. Asset pricing - Wikipedia

    en.wikipedia.org/wiki/Asset_pricing

    Calculating option prices, and their "Greeks", i.e. sensitivities, combines: (i) a model of the underlying price behavior, or "process" - i.e. the asset pricing model selected, with its parameters having been calibrated to observed prices; and (ii) a mathematical method which returns the premium (or sensitivity) as the expected value of option ...

  9. Top adviser recommends against Elon Musk's $56B Tesla ... - AOL

    www.aol.com/news/top-adviser-recommends-against...

    Top proxy adviser Institutional Shareholder Services on Friday recommended Tesla shareholders vote against the reapproval of CEO Elon Musk’s $56 billion pay package and withhold their support ...