AIMC Topic: Least-Squares Analysis

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A least square generative network based on invariant contrastive feature pair learning for multimodal MR image synthesis.

International journal of computer assisted radiology and surgery
PURPOSE: During MR-guided neurosurgical procedures, several factors may limit the acquisition of additional MR sequences, which are needed by neurosurgeons to adjust surgical plans or ensure complete tumor resection. Automatically synthesized MR cont...

Global-local least-squares support vector machine (GLocal-LS-SVM).

PloS one
This study introduces the global-local least-squares support vector machine (GLocal-LS-SVM), a novel machine learning algorithm that combines the strengths of localised and global learning. GLocal-LS-SVM addresses the challenges associated with decen...

Stock market prediction using Altruistic Dragonfly Algorithm.

PloS one
Stock market prediction is the process of determining the value of a company's shares and other financial assets in the future. This paper proposes a new model where Altruistic Dragonfly Algorithm (ADA) is combined with Least Squares Support Vector M...

Rapid quantification of royal jelly quality by mid-infrared spectroscopy coupled with backpropagation neural network.

Food chemistry
Royal jelly is rich in nutrients but its quality is greatly affected by storage conditions. To determine the quality of royal jelly accurately and quickly, a qualitative discrimination model was established based on the fusion of conventional paramet...

Machine Learning for Prediction, Classification, and Identification of Immobilized Enzymes for Biocatalysis.

Pharmaceutical research
BACKGROUND: Enzyme immobilization is a beneficial component involved in biocatalytic strategies. Understanding and evaluating the enzyme immobilization system plays an important role in the successful development and implementation of the biocatalysi...

Hybrid Feature Fusion-Based High-Sensitivity Fire Detection and Early Warning for Intelligent Building Systems.

Sensors (Basel, Switzerland)
High-sensitivity early fire detection is an essential prerequisite to intelligent building safety. However, due to the small changes and erratic fluctuations in environmental parameters in the initial combustion phase, it is always a challenging task...

Quantitative Mass Spectrometry Imaging Using Multivariate Curve Resolution and Deep Learning: A Case Study.

Journal of the American Society for Mass Spectrometry
In the present contribution, a novel approach based on multivariate curve resolution and deep learning (DL) is proposed for quantitative mass spectrometry imaging (MSI) as a potent technique for identifying different compounds and creating their dist...

Rapid simultaneous analysis of anti human immunodeficiency virus drugs in pharmaceutical formulation by smart spectrophotometry based on multivariate calibration and least squares support vector machine methods.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this study, two chemometrics methods, including partial least squares regression (PLS) and least squares support vector machine (LS-SVM) were applied for the simultaneous determination of zidovudine (ZDV) and lamivudine (LMV) in synthetic mixtures...

A deep learning method for predicting lead content in oilseed rape leaves using fluorescence hyperspectral imaging.

Food chemistry
The purpose of this study was to develop a deep learning method involving wavelet transform (WT) and stacked denoising autoencoder (SDAE) for extracting deep features of heavy metal lead (Pb) detection of oilseed rape leaves. Firstly, the standard no...

A soft sensing method of billet surface temperature based on ILGSSA-LSSVM.

Scientific reports
It is difficult to measure the surface temperature of continuous casting billet, which results in the lack of important feedback parameters for further scientific control of the billet quality. This paper proposes a sparrow search algorithm to optimi...