Each parameter Tensor (params) has a corresponding Tensor of the same size for gradients w.r.t. parameters (gradParams). When using momentum learning, another Tensor is added for each parameter Tensor (momGradParams). This method should be called before updateParameters as it affects the ...
Repeating a gate sequence multiple times amplifies systematic errors coherently, making it a useful tool for characterizing quantum gates. However, the precision of such an approach is limited by low-frequency noise, while its efficiency is hindered by t
Some commonly used data-driven techniques are statistical process control (SPC), machine learning, artificial neural networks (ANN), and time series analysis. The degradation of an asset does not happen instantly, it is a slow process that occurs over a period of time. Abdul Wahid et al. ...
There is still insufficient data on the behavior of tubed-reinforced concrete columns (TRCCs) under the eccentric compression. Thus, this research work comprehensively examines the eccentric compression behavior of TRCCs using nonlinear finite element modeling and machine learning (ML). To do this, ...
A statistical theory of solid solution hardening. Phys. Status Solidi 41, 659–669 (1970). Article Google Scholar Nabarro, F. R. N. Theory of solution hardening. Philos. Mag. 35, 613–622 (1977). Article CAS ADS Google Scholar Okamoto, N. L. et al. Size effect, critical resolved...
Stock market prediction is the practice of predicting the performance of a specific stock or the market as a whole using statistical and machine learning approaches. Stock market forecasting is to give investors a better knowledge of the prospective risks and benefits of purchasing or selling a ...
They can also analyze them in modulation, code, frequency, time, and statistical domains. This Learning Module covers the basics of Spectrum Analyzers, including their functions and operation.2. ObjectivesUpon completion of this module, you will be able to:...
Based on the gathered data, we continually eliminate orderings with bad performance using a statistical test. We treat T x as a random variable, and approximate it by the normal distribution with an unknown mean and variance. Our goal is to pick from the set of candidate orderings O the ...
Given the known advantages of authentic learning but the extremely limited access, this work seeks to understand the ways in which students perform element sequencing tasks when using AR to simulate the physical interactions of authentic learning with the low cost of traditional design communication, ...
Wind energy has been acknowledged as one of the most intriguing renewable energy resources [1]. Wind turbine design is demanding in terms of both expense and time. Based on this, the engineering approach known as blade element momentum (BEM) was extensively employed in wind turbine blade design...