Translations:Berechnungsschema von Speichern/7/en - Versionsgeschichte

Froehlich am 26. November 2020 um 15:24 Uhr

2020-11-26T15:24:44Z

← Nächstältere Version		Version vom 26. November 2020, 17:24 Uhr
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	After linearization, a straight line equation which is only dependent on the storage volume can be determined for each process function. The gradient "m" of the line changes from node to node of the process function.		After linearization, a straight line equation which is only dependent on the storage volume can be determined for each process function. The gradient "m" of the line changes from node to node of the process function.
	Thus, for each function dependent on the storage volume, there is a ~~piecewise~~ linearized function for the entire range of possible storage volumes. The function itself can be scaled with a factor (A) that is constant for each time step, which summarizes all further dependencies as a product.		Thus, for each function dependent on the storage volume, there is a piecewisely linearized function for the entire range of possible storage volumes. The function itself can be scaled with a factor (A) that is constant for each time step, which summarizes all further dependencies as a product.

Froehlich am 26. November 2020 um 15:01 Uhr

2020-11-26T15:01:42Z

← Nächstältere Version		Version vom 26. November 2020, 17:01 Uhr
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	After linearization, a straight line equation ~~can be set up for each sampling function,~~ which is only dependent on the storage ~~capacity~~. The gradient "m" of the line changes from ~~interpolation point~~ to ~~interpolation point~~.		After linearization, a straight line equation which is only dependent on the storage volume can be determined for each process function. The gradient "m" of the line changes from node to node of the process function.
	Thus, for each function dependent on the storage ~~rate~~, there is a linearized ~~course along~~ the storage ~~filling~~. The function itself can be scaled with a ~~constant~~ factor (A) for each time step, which summarizes all further dependencies as product.		Thus, for each function dependent on the storage volume, there is a piecewise linearized function for the entire range of possible storage volumes. The function itself can be scaled with a factor (A) that is constant for each time step, which summarizes all further dependencies as a product.

Ferrao am 25. November 2020 um 09:31 Uhr

2020-11-25T09:31:07Z

← Nächstältere Version		Version vom 25. November 2020, 11:31 Uhr
Zeile 1:		Zeile 1:
	After linearization, a straight line equation can be set up for each sampling function, which is only dependent on the ~~memory content~~. The gradient "m" of the line changes from interpolation point to interpolation point.		After linearization, a straight line equation can be set up for each sampling function, which is only dependent on the storage capacity. The gradient "m" of the line changes from interpolation point to interpolation point.
	Thus, for each function dependent on the storage rate, there is a linearized course along the storage filling. The function itself can be scaled with a constant factor (A) for each time step, which summarizes all further dependencies as product.		Thus, for each function dependent on the storage rate, there is a linearized course along the storage filling. The function itself can be scaled with a constant factor (A) for each time step, which summarizes all further dependencies as product.

Ferrao: Die Seite wurde neu angelegt: „After linearization, a straight line equation can be set up for each sampling function, which is only dependent on the memory content. The gradient "m" of the…“

2020-11-17T15:03:19Z

Die Seite wurde neu angelegt: „After linearization, a straight line equation can be set up for each sampling function, which is only dependent on the memory content. The gradient "m" of the…“

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After linearization, a straight line equation can be set up for each sampling function, which is only dependent on the memory content. The gradient "m" of the line changes from interpolation point to interpolation point.
Thus, for each function dependent on the storage rate, there is a linearized course along the storage filling. The function itself can be scaled with a constant factor (A) for each time step, which summarizes all further dependencies as product.