A novel neural network adaptive filter algorithm is proposed to address the challenge of weak spectral signals and low accuracy in micro-spectrometer detection. This ...
In this project it is used a Machine Learning model based on a method called Extreme Learning, with the employment of L2-regularization. In particular, a comparison was carried out between: (A1) which ...
Risk assessment is critical to ensure the safe operation of oil and gas pipeline systems. The core content of such risk assessment is to determine the failure probability of the pipelines ...
Abstract: Training end-to-end unrolled iterative neural networks for single-photon emission computerized tomography (SPECT) image reconstruction requires a memory-efficient forward–backward projector ...
Abstract: This study solves the problems of insufficient objectivity and a large amount of calculation in traditional regional economic development level evaluation methods. The conventional Back ...
This study presents a parameter selection strategy developed for the Stretch-Blow Molding (SBM) process to minimize the weight of preforms used. The method is based on a predictive model developed ...
Andrew's class may be the common sense among ML practitioners. I don't want to fool myself. Even I have read some api doc of sklearn and know how to call them, I don't know the soul of machine ...
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