AIMC Topic: Least-Squares Analysis

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A Temperature Compensation Method for aSix-Axis Force/Torque Sensor Utilizing Ensemble hWOA-LSSVM Based on Improved Trimmed Bagging.

Sensors (Basel, Switzerland)
The performance of a six-axis force/torque sensor (F/T sensor) severely decreased when working in an extreme environment due to its sensitivity to ambient temperature. This paper puts forward an ensemble temperature compensation method based on the w...

Raman spectroscopy for on-line monitoring of botanical extraction process using convolutional neural network with background subtraction.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Aqueous extraction is the most common and cost-effective means of obtaining active ingredients from medicinal plants. However, botanical extracts generally contain high pigment content and complex chemical composition posing a challenge for the proce...

Empirical analyses and simulations showed that different machine and statistical learning methods had differing performance for predicting blood pressure.

Scientific reports
Machine learning is increasingly being used to predict clinical outcomes. Most comparisons of different methods have been based on empirical analyses in specific datasets. We used Monte Carlo simulations to determine when machine learning methods per...

Least square support vector machine-based variational mode decomposition: a new hybrid model for daily river water temperature modeling.

Environmental science and pollution research international
Machines learning models have recently been proposed for predicting rivers water temperature (T) using only air temperature (T). The proposed models relied on a nonlinear relationship between the T and T and they have proven to be robust modelling to...

Deep Cross-Output Knowledge Transfer Using Stacked-Structure Least-Squares Support Vector Machines.

IEEE transactions on cybernetics
This article presents a new deep cross-output knowledge transfer approach based on least-squares support vector machines, called DCOT-LS-SVMs. Its aim is to improve the generalizability of least-squares support vector machines (LS-SVMs) while avoidin...

Probing 1D convolutional neural network adapted to near-infrared spectroscopy for efficient classification of mixed fish.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Salmon and Cod are economically significant world-class fish that have high economic value. It is difficult to accurately sort and process them by appearance during harvest and transportation. Conventional chemical detection means are time-consuming ...

Machine Learning-Based Boosted Regression Ensemble Combined with Hyperparameter Tuning for Optimal Adaptive Learning.

Sensors (Basel, Switzerland)
Over the past couple of decades, many telecommunication industries have passed through the different facets of the digital revolution by integrating artificial intelligence (AI) techniques into the way they run and define their processes. Relevant da...

ECG classification system based on multi-domain features approach coupled with least square support vector machine (LS-SVM).

Computer methods in biomechanics and biomedical engineering
Developing a robust authentication and identification method becomes an urgent demand to protect the integrity of devices data. Although the use of passwords provides an acceptable control and authentication, it has shown much weakness in terms of sp...

The Usage of ANN for Regression Analysis in Visible Light Positioning Systems.

Sensors (Basel, Switzerland)
In this paper, we study the design aspects of an indoor visible light positioning (VLP) system that uses an artificial neural network (ANN) for positioning estimation by considering a multipath channel. Previous results usually rely on the simplistic...

Multimedia Security Situation Prediction Based on Optimization of Radial Basis Function Neural Network Algorithm.

Computational intelligence and neuroscience
Aiming at the problem of prediction accuracy in network situation awareness, a network security situation prediction method based on a generalized radial basis function (RBF) neural network is proposed. This method uses the K-means clustering algorit...