Path Loss Prediction Based on Machine Learning Methods for Aircraft Cabin Environments

Rule-based Machine Learning Methods for Functional Prediction

We describe a machine learning method for predicting the value of a real-valued function, given the values of multiple input variables. The method induces solutions from samples in the form of ordered disjunctive normal form (DNF) decision rules. A central objective of the method and representation is the induction of compact, easily interpretable solutions. This rule-based decision model can b...

Knowledge-based machine learning methods for macromolecular 3D structure prediction

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Path Loss Prediction by Robust Regression Methods

Identification Psychological Disorders Based on Data in Virtual Environments Using Machine Learning

Introduction: Psychological disorders is one of the most problematic and important issue in today's society. Early prognosis of these disorders matters because receiving professional help at the appropriate time could improve the quality of life of these patients. Recently, researches use social media as a form of new tools in identifying psychological disorder. It seems that through the use of...

Operating Comfort Prediction Model of Human-Machine Interface Layout for Cabin Based on GEP

In view of the evaluation and decision-making problem of human-machine interface layout design for cabin, the operating comfort prediction model is proposed based on GEP (Gene Expression Programming), using operating comfort to evaluate layout scheme. Through joint angles to describe operating posture of upper limb, the joint angles are taken as independent variables to establish the comfort mo...