AIMC Topic: Least-Squares Analysis

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Study on the identification of resistance of rice blast based on near infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Rice Blast is the most devastating rice disease which poses a serious threat to the safe production of rice. The most effective way to prevent rice blast is to cultivate the rice varieties that have resistance to the disease, however, traditional res...

On the Prediction of Biogas Production from Vegetables, Fruits, and Food Wastes by ANFIS- and LSSVM-Based Models.

BioMed research international
This study is aimed at modeling biodigestion systems as a function of the most influencing parameters to generate two robust algorithms on the basis of the machine learning algorithms, including adaptive network-based fuzzy inference system (ANFIS) a...

Neural networks for parameter estimation in microstructural MRI: Application to a diffusion-relaxation model of white matter.

NeuroImage
Specific features of white matter microstructure can be investigated by using biophysical models to interpret relaxation-diffusion MRI brain data. Although more intricate models have the potential to reveal more details of the tissue, they also incur...

The assessment of emerging data-intelligence technologies for modeling Mg and SO surface water quality.

Journal of environmental management
The concentration of soluble salts in surface water and rivers such as sodium, sulfate, chloride, magnesium ions, etc., plays an important role in the water salinity. Therefore, accurate determination of the distribution pattern of these ions can imp...

Baseline Correction of Acceleration Data Based on a Hybrid EMD-DNN Method.

Sensors (Basel, Switzerland)
Measuring displacement response is essential in the field of structural health monitoring and seismic engineering. Numerical integration of the acceleration signal is a common measurement method of displacement data. However, due to the circumstances...

Feature selection of infrared spectra analysis with convolutional neural network.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Data-driven deep learning analysis, especially for convolution neural network (CNN), has been developed and successfully applied in many domains. CNN is regarded as a black box, and the main drawback is the lack of interpretation. In this study, an i...

Health Evaluation and Fault Diagnosis of Medical Imaging Equipment Based on Neural Network Algorithm.

Computational intelligence and neuroscience
In recent years, high-precision medical equipment, especially large-scale medical imaging equipment, is usually composed of circuit, water, light, and other structures. Its structure is cumbersome and complex, so it is difficult to detect and diagnos...

Chemometric quality assessment of Paracetamol and Phenylephrine Hydrochloride with Paracetamol impurities; comparative UV-spectrophotometric implementation of four predictive models.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Spectrophotometric data analysis using multivariate approaches has many useful applications. One of these applications is the analysis of active ingredients in presence of impurities. Four chemometric-assisted spectrophotometric methods, namely, prin...

Verified the rapid evaluation of the edible safety of wild porcini mushrooms, using deep learning and PLS-DA.

Journal of the science of food and agriculture
BACKGROUND: How to quickly identify poisonous mushrooms is a worldwide problem, because poisonous mushrooms and edible mushrooms have very similar appearances. Even some edible mushrooms must be processed further before they can be eaten. In addition...

Early pregnancy diagnosis of rabbits: A non-invasive approach using Vis-NIR spatially resolved spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Pregnancy diagnosis is essential for rabbit's reproductive management. The early identification of non-pregnant rabbits allows for earlier re-insemination, increases the service rate, and reduces the laboring interval in commercial operations. The ob...