Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses

Abstract

Monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used impeding the required consistent positioning of the temperature sensors during donning and doffing. Predicting the in-socket residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. In this work, we propose to implement an adaptive neuro fuzzy inference strategy (ANFIS) to predict the in-socket residual limb temperature. ANFIS belongs to the family of fused neuro fuzzy system in which the fuzzy system is incorporated in a framework which is adaptive in nature. The proposed method is compared to our earlier work using Gaussian processes for machine learning. By comparing the predicted and actual data, results indicate that both the modeling techniques have comparable performance metrics and can be efficiently used for non-invasive temperature monitoring.

Deep learning and regression modelling of cloudless downward longwave radiation

“…The low computational deficiency of FL is compensated for by neural networks, and on the other hand, the reasoning ability of FL compensates the backpropagation fast learning schemes of NN [4,53,62,68]. More information on the fundamentals and applications of ANFIS abound in specialised publications [1,19].…”

“…Seemingly, the state of the art for estimating global solar radiation is the use of expert systems such as neural networks, support vector regression (SVR) and adaptive neuro-fuzzy inference system (ANFIS), including hybrids [4,68,73,91]. Depending on the applied technique, any of them can perform better than the others.…”

SISTEM CERDAS PENDUGAAN SALINITAS AIR LAUT BERDASARKAN CITRA LANDSAT MENGGUNAKAN METODE Adaptive Neuro Fuzzy Inference System ( ANFIS )

“…Arsitektur ANFIS dapat digunakan mempekerjakan untuk model fungsi Non-Linear dan tidak teratur, serta dapat mengidentifikasi komponen Non-Linear dalam Sistem. Implementasi sistem inferensi fuzzy ini terdiri dari lima layer (Mathur, Glesk, & Buis, 2016):…”

Prediction of Financial Distress, Using Metaheuristic Models

“…The tender method is compared to our earlier work using Gaussian processes for machine learning. By comparing the forecasted and actual data, results show that both the modelling techniques have similar performance metrics and can be efficiently used for non-invasive temperature supervision (Mathur and et (Mathur and et al,2016).…”