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Linear Models

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Making Group Decisions within the Framework of a Probabilistic Hesitant Fuzzy Linear Regression Model.

Sensors (Basel, Switzerland)
A fuzzy set extension known as the hesitant fuzzy set (HFS) has increased in popularity for decision making in recent years, especially when experts have had trouble evaluating several alternatives by employing a single value for assessment when work...

IoT and Satellite Sensor Data Integration for Assessment of Environmental Variables: A Case Study on NO.

Sensors (Basel, Switzerland)
This paper introduces a novel approach to increase the spatiotemporal resolution of an arbitrary environmental variable. This is achieved by utilizing machine learning algorithms to construct a satellite-like image at any given time moment, based on ...

Estimation of the Mixed Layer Depth in the Indian Ocean from Surface Parameters: A Clustering-Neural Network Method.

Sensors (Basel, Switzerland)
The effective estimation of mixed-layer depth (MLD) plays a significant role in the study of ocean dynamics and global climate change. However, the methods of estimating MLD still have limitations due to the sparse resolution of the observed data. In...

A Machine Learning Model to Predict Citation Counts of Scientific Papers in Otology Field.

BioMed research international
One of the most widely used measures of scientific impact is the number of citations. However, due to its heavy-tailed distribution, citations are fundamentally difficult to predict but can be improved. This study was aimed at investigating the facto...

Linear and Machine Learning modelling for spatiotemporal disease predictions: Force-of-Infection of Chagas disease.

PLoS neglected tropical diseases
BACKGROUND: Chagas disease is a long-lasting disease with a prolonged asymptomatic period. Cumulative indices of infection such as prevalence do not shed light on the current epidemiological situation, as they integrate infection over long periods. I...

Predicting Divorce Prospect Using Ensemble Learning: Support Vector Machine, Linear Model, and Neural Network.

Computational intelligence and neuroscience
A divorce is a legal step taken by married people to end their marriage. It occurs after a couple decides to no longer live together as husband and wife. Globally, the divorce rate has more than doubled from 1970 until 2008, with divorces per 1,000 m...

Application of image processing and soft computing strategies for non-destructive estimation of plum leaf area.

PloS one
Plant leaf area (LA) is a key metric in plant monitoring programs. Machine learning methods were used in this study to estimate the LA of four plum genotypes, including three greengage genotypes (Prunus domestica [subsp. italica var. claudiana.]) and...

Causal Discovery in Linear Non-Gaussian Acyclic Model With Multiple Latent Confounders.

IEEE transactions on neural networks and learning systems
Causal discovery from observational data is a fundamental problem in science. Though the linear non-Gaussian acyclic model (LiNGAM) has shown promising results in various applications, it still faces the following challenges in the data with multiple...

Neural Granger Causality.

IEEE transactions on pattern analysis and machine intelligence
While most classical approaches to Granger causality detection assume linear dynamics, many interactions in real-world applications, like neuroscience and genomics, are inherently nonlinear. In these cases, using linear models may lead to inconsisten...

Comparative Analysis of Major Machine-Learning-Based Path Loss Models for Enclosed Indoor Channels.

Sensors (Basel, Switzerland)
Unlimited access to information and data sharing wherever and at any time for anyone and anything is a fundamental component of fifth-generation (5G) wireless communication and beyond. Therefore, it has become inevitable to exploit the super-high fre...