Research on short-term wind power Prediction of GRU based on similar days

As the proportion of wind power generation continues to increase, accurate forecasting of wind power output is of great significance to the smooth operation of the entire power grid. However, due to the greater impact of environmental factors, wind power generation has strong randomness, and it becomes difficult to accurately predict the power generation. Thus, a new hybrid model for wind power generation prediction combining GRU neural networks and similar days’ characters analysis is proposed to address solve this problem. The prediction method employs grey relation analysis to screen similar days, which not only reduces the amount of data required to train the model, reduces the computational complexity, and improves the training speed, but also improves the prediction accuracy based on the selected datasets. In addition, this method also filters and processes the data through box-plot analysis and linear smoothing, which further improves the prediction accuracy of the model. The results show that compared with a single GRU network, the MAE of this method has dropped by 1.89, RMSE has dropped by 1.9, and MAPE has dropped by 11.07%. Obviously, the prediction model based on similar days extraction has obvious advantages.

Converting from the Montreal Cognitive Assessment to the Mini-Mental State Examination-2

Objective The Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination-2 (MMSE-2) are useful psychometric tests for cognitive screening. Many clinicians want to predict the MMSE-2 score based on the MoCA score. To facilitate the transition from the MoCA to the MMSE-2, this study developed a conversion method. Methods This study retrospectively examined the relationship between the MoCA and MMSE-2. Overall, 303 participants were evaluated. We produced a conversion table using the equipercentile equating method with log-linear smoothing. Then, we evaluated the reliability and accuracy of this algorithm to convert the MoCA to the MMSE-2. Results MoCA scores were converted to MMSE-2 scores according to a conversion table that achieved a reliability of 0.961 (intraclass correlation). The accuracy of this algorithm was 84.5% within 3 points difference from the raw score. Conclusions This study reports a reliable and easy conversion algorithm for transforming MoCA scores into converted MMSE-2 scores. This method will greatly enhance the utility of existing cognitive data in clinical and research settings.

Item Parameter Estimation in Multistage Designs: A Comparison of Different Estimation Approaches for the Rasch Model

There is some debate in the psychometric literature about item parameter estimation in multistage designs. It is occasionally argued that the conditional maximum likelihood (CML) method is superior to the marginal maximum likelihood method (MML) because no assumptions have to be made about the trait distribution. However, CML estimation in its original formulation leads to biased item parameter estimates. Zwitser and Maris (2015, Psychometrika) proposed a modified conditional maximum likelihood estimation method for multistage designs that provides practically unbiased item parameter estimates. In this article, the differences between different estimation approaches for multistage designs were investigated in a simulation study. Four different estimation conditions (CML, CML estimation with the consideration of the respective MST design, MML with the assumption of a normal distribution, and MML with log-linear smoothing) were examined using a simulation study, considering different multistage designs, number of items, sample size, and trait distributions. The results showed that in the case of the substantial violation of the normal distribution, the CML method seemed to be preferable to MML estimation employing a misspecified normal trait distribution, especially if the number of items and sample size increased. However, MML estimation using log-linear smoothing lea to results that were very similar to the CML method with the consideration of the respective MST design.

Noise Cancellation of Helicopter Blade Deformations Measurement by Fiber Bragg Gratings

The work presents data treatment methods aimed at eliminating the noise in the strain sensor data induced by vibrations of the helicopter blade in flight conditions. The methods can be applied in order to enhance the metrological performance of the helicopter weight estimation system based on the deformation measurement of the main rotor blades. The experimental setup included a composite plate fixed to the vibrating stand on the one end, with six fiber-optic strain sensors attached to its surface. In this work, the procedure of the optimal linear smoothing (POLS) and 3D-invariant methods were used to obtain monotone calibration curves for each detector, thereby making it possible to distinguish the increase of load applied to the free end of the plate with an increment of 10 g. The second method associated with 3D invariants took into account 13 quantitative parameters defined as the combination of different moments and their intercorrelations up to the fourth-order inclusive. These 13 parameters allowed the calculation of the 3D surface that can serve as a specific fingerprint, differentiating one set of initial data from another one. The combination of the two data treatment methods used in this work can be applied successfully in a wide variety of applications.

Norms and equivalences for MoCA-30, MoCA-22, and MMSE in the oldest-old

Background Cognitive screening is important for the oldest-old (age 90 +). This age group is the fastest growing and has the highest risk of dementia. However, norms and score equivalence for screening tests are lacking for this group. Aims To provide norms and score equivalence for commonly used cognitive screening tests for the oldest-old. Methods Data on 157 participants of the Center for Healthy Aging Longevity Study aged 90 + were analyzed. First, we derived norms for (1) subtests and cognitive domains of the in-person Montreal Cognitive Assessment having a maximum score of 30 (MoCA-30) and (2) the total MoCA-22 score, obtained from the in-person MoCA-30 by summing the subtests that do not require visual input to a maximum score of 22. These norms were derived from 124 participants with a Mini-Mental State Examination (MMSE) ≥ 27. Second, we derived score equivalences for MMSE to MoCA-30 and MoCA-22, and MoCA-30 to MoCA-22 using equipercentile equating method with log-linear smoothing, based on all 157 participants. Results MoCA-22 total score norms are: mean = 18.3(standard deviation = 2.2). An MMSE score of 27 is equivalent to a MoCA-30 score of 22 and a MoCA-22 score of 16. Discussion and conclusions Subtest, domain and MoCA-22 norms will aid in evaluation of the oldest-old who cannot complete the MoCA-30 or are tested over the phone. The equivalences of the three cognitive tests (MMSE, MoCA-30, MoCA-22) in the oldest-old will facilitate continuity of cognitive tracking of individuals tested with different tests over time and comparison of the studies that use different cognitive tests.

A Modified Cell-Based Strain Smoothing for Material Nonlinearity

This work presents a linear smoothing scheme over high-order triangular elements in the framework of a cell-based strain smoothed finite element method for two-dimensional nonlinear problems. The main idea behind the proposed linear smoothing scheme for strain-smoothed finite element method (S-FEM) is no subdivision of finite element cells to sub-cells while the classical S-FEM needs sub-cells. Since the linear smoothing function is employed, S-FEM is able to use quadratic triangular or quadrilateral elements. The modified smoothed matrix obtained node-wise is evaluated. In the same manner with the computation of the strain-displacement matrix, the smoothed stiffness matrix and deformation graident are obtained over smoothing domains. A series of benchmark tests are investigated to demonstrate validity and stability of the proposed scheme. The validity and accuracy are confirmed by comparing the obtained numerical results with the standard FEM using 2nd-order triangular element and the exact solutions.