AIMC Topic: Least-Squares Analysis

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Comfort Prediction of Office Chair Surface Material Based on the ISSA-LSSVM.

Sensors (Basel, Switzerland)
This study serves the purpose of assisting users in selecting a comfortable seat surface material for office chairs and enhancing users' comfort while using office chairs. To address the issue that the selection of traditional seat surface material i...

Several machine learning techniques comparison for the prediction of the uniaxial compressive strength of carbonate rocks.

Scientific reports
In engineering practices, it is critical and necessary to either measure or estimate the uniaxial compressive strength (UCS) of the rock. Measuring the UCS of rocks requires comprehensive studies in the field and in the laboratory for the rock block ...

Identification of agricultural quarantine materials in passenger's luggage using ion mobility spectroscopy combined with a convolutional neural network.

Analytical methods : advancing methods and applications
As economic globalization intensifies, the recent increase in agricultural products and travelers from abroad has led to an increase in the probability of invasive alien species. A major pathway for invasive alien species is agricultural quarantine m...

Neural network ensemble model for prediction of erythrocyte sedimentation rate (ESR) using partial least squares regression.

Scientific reports
The erythrocyte sedimentation rate (ESR) is a non-specific blood test for determining inflammatory conditions. However, the long measurement time (60 min) to obtain ESR is an obstacle for a prompt evaluation. In this study, to reduce the measurement ...

A Connection Between Pattern Classification by Machine Learning and Statistical Inference With the General Linear Model.

IEEE journal of biomedical and health informatics
A connection between the general linear model (GLM) with frequentist statistical testing and machine learning (MLE) inference is derived and illustrated. Initially, the estimation of GLM parameters is expressed as a Linear Regression Model (LRM) of a...

Reducing Data Complexity Using Autoencoders With Class-Informed Loss Functions.

IEEE transactions on pattern analysis and machine intelligence
Available data in machine learning applications is becoming increasingly complex, due to higher dimensionality and difficult classes. There exists a wide variety of approaches to measuring complexity of labeled data, according to class overlap, separ...

Prediction of textile pilling resistance using optical coherence tomography.

Scientific reports
This paper describes a new method of textile pilling prediction, based on multivariate analysis of the spatial layer above the surface. The original idea of the method is the acquisition of 3D fabric image using optical coherence tomography (OCT) wit...

Development and comparative analysis of ANN and SVR-based models with conventional regression models for predicting spray drift.

Environmental science and pollution research international
As monitoring of spray drift during application can be expensive, time-consuming, and labor-intensive, drift predicting models may provide a practical complement. Several mechanistic models have been developed as drift prediction tool for various typ...

Application of Deep-Learning Algorithm Driven Intelligent Raman Spectroscopy Methodology to Quality Control in the Manufacturing Process of Guanxinning Tablets.

Molecules (Basel, Switzerland)
Coupled with the convolutional neural network (CNN), an intelligent Raman spectroscopy methodology for rapid quantitative analysis of four pharmacodynamic substances and soluble solid in the manufacture process of Guanxinning tablets was established....

Modeling consolidation of soft clay by developing a fractional differential constitutive model in conjunction with an intelligent displacement inversion method.

PloS one
Studying the constitutive relation of soft clays is of critical importance for fundamentally understanding their complex consolidation behavior. This study proposes a fractional differential constitutive model in conjunction with an intelligent displ...