The phrase "allocation weight" is correct and usable in written English.
It can be used in contexts related to finance, resource management, or data analysis, where it refers to the proportion or percentage assigned to a particular resource or investment.
Example: "The allocation weight for each asset in the portfolio was carefully calculated to optimize returns while minimizing risk."
Alternatives: "distribution weight" or "resource weight".
Previously, the risk priority number or the criticality number was used to consider the failure effect in the allocation weight.
In this paper, we identify the limitations of the previous approach and propose a new allocation weight based on the subsystem failure severity and its relative frequency.
A reliability allocation weight is used during the early design stage of a system to apportion the system reliability requirement to its individual subsystems.
Since some failures have serious effects on public safety, cost and environmental issues especially in a mission critical system, the failure effect must be considered as one of the important factors in determining the allocation weight.
A block design with allocation weight of 1 1 will be used to generate treatment allocation.
A permuted block design with allocation weight of 1 1 1 1 will be used to generate the treatment assignments.
So should you be out of stocks now? A. You should have a lower weight in stocks, around 35 or 40percentt, compared to a normal allocation of 60percentt.
Reproductive allocation (RA) per plant was defined by dividing seed weight with the biomass.
Optimal allocation weights for one year found using estimates from each model are carried to the subsequent year and the realized Sharpe ratio is computed to assess portfolio performance.
where the power normalization parameter β is set such that G RZF satisfies the power constraint in (8) and P is a fixed diagonal matrix whose diagonal elements are power allocation weights for each user.
The adjacent list size depends on the frequency bands available which are identified with a number from zero to n that represents a pre-allocation weight for each attribute or parameter, and hence, helping to identify the shortest path.
