Thus, for example, in the case of 12 questions, negative scores will be obtained when 10, 11, or 12 of the answers to the questions are incorrect. Likewise, the balance will be zero points when nine answers are incorrect and three correct; in the rest of the cases, the score will be...
As an example of its practical engineering application, the workload of road systems can be changed by controlling the density and speed of passing vehicles. Moreover, the stopping method in multi-attempt missions based on degradation is still under-explored. Multiple attempts of missions can ...
Then, the change in the 𝛉θ parameter estimate can be directly expressed as a function of model deviations 𝒓r using the weighted least squares regression formula [38]. Let ΩΩ be the diagonal matrix containing weights 𝜔ℎωh in the diagonal. Let 𝑨A be the design matrix that ...
As we have seen, each response includes some reasoning, and the option to ask follow-up questions enables the user to have a more comprehensive understanding of the concept rather than simply one answer output. Das et al., 2023 [28] reported that ChatGPT scored an accuracy of about 80% ...
The ordinary least squares estimator for a linear regression model, for example, maximizes the likelihood when all observed outcomes are assumed to have normal distributions with the same variance. In certain circumstances, the first-order requirements of the likelihood function may be analytically ...
The clear compartmentalization of functionalities within interfaces facilitates more straightforward and efficient regression testing. When changes are made to a particular module, only the tests associated with that module need to be rerun to verify that no existing functionalities have been broken. This...
The ordinary least squares estimator for a linear regression model, for example, maximizes the likelihood when all observed outcomes are assumed to have normal distributions with the same variance. In certain circumstances, the first-order requirements of the likelihood function may be analytically ...
A classical calibration example would be the fitting of the hyper-parameters to the observation of bond prices and derivatives, both with different maturities, at a fixed time 𝑡0. The Gaussian process regression hence also provides a suitable approach for this task. We refer to De Spiegeleer...
Shi et al. introduced a novel model to evaluate the risk of line tripping caused by wildfires in high-voltage power line corridors using remote sensing and logic regression techniques [23]. Zhang et al. developed a mid–short-term risk reliability assessment methodology for power systems that ...
To address this issue, we propose a novel transfer subspace learning method called multiple distribution-adapted regression (MDAR) to bridge the gap between speech samples from different corpora. Specifically, MDAR aims to learn a projection matrix to build the relationship between the source speech ...