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Our proposed algorithm minimizes the weighted squared error sum instead of the squared error sum, and the weighting matrix in the proposed algorithm counteracts the adverse effects of the LOS/NLOS mixture sensor.
In 4D-var data assimilation, a minimization algorithm is used to find the set of control variables which minimizes the weighted least squares distance between model predictions and observations over the assimilation window.
The objective function of the model minimizes the weighted sum of transportation cost in regular situation and the expected transportation cost following a hub failure.
Under the cutoff priority discipline, the optimal prioritized channel allocation problem is formulated, which minimizes the weighted average blocking probability of handoff calls while ensuring the prespecified grade of service for new calls and the co-channel interference constraints.
Using prior information on the sparse signal, projection matrix design is formulated as an optimization problem that minimizes the weighted Frobenius distance between the Gram matrix and the identity matrix.
Consideration on the performance of an estimator for the control value includes the difference of the expected response E yi) from its corresponding target value Ti for each component and the optimal value of control point, say x0, is defined to be the one which minimizes the weighted sum of squares of those standardized differences within the range of x.
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We combined an epidemic model with an objective function to minimize the weighted sum of people with excess weight and the cost of a medication and surgical intervention in the population.
Once the optimal feature and its threshold are found by minimizing the weighted error, the next step is to update the weights.
The objective function is to minimize the weighted sum of the travel time plus overtime penalties.
The target is to minimize the weighted residual function (cost function) of the ODEs.
The target is to minimize the weighted residual function (error function) of the ODEs.
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