Multi-objective optimization of double primary tubular permanent magnet synchronous linear motor in wide temperature range environment based on Pareto front …
Z Hao, W Zhou, T Ji, X Huang, C Zhang - IEEE Access, 2020 - ieeexplore.ieee.org
In order to improve the thrust density of the electric actuator in aircraft, a double primary
tubular permanent magnet synchronous linear motor is designed. By establishing the …
tubular permanent magnet synchronous linear motor is designed. By establishing the …
Machine learning based simulation for design space exploration
Design of software in the automotive domain often involves simulation to allow early
software parametrization. Modeling complex systems or components impacted by the …
software parametrization. Modeling complex systems or components impacted by the …
Machine Learning Based Simulation for Wear Estimation in Commercial Vehicle Applications
Progress in commercial vehicle technology leads to higher numbers of built-in sensors, high-
speed in-vehicle networks, bigger data storages and therefore a higher availability of …
speed in-vehicle networks, bigger data storages and therefore a higher availability of …
Simultaneous knowledge discovery and development of smart neuro-fuzzy surrogates for online optimization of computationally expensive models
This work aims at enabling online optimization and control of computationally expensive
models by employing Adaptive Neuro Fuzzy Inference System (ANFIS) as surrogates. ANFIS …
models by employing Adaptive Neuro Fuzzy Inference System (ANFIS) as surrogates. ANFIS …
Novel sample size determination methods for parsimonious training of black box models
The problem of sample size determination (SSD) for any black box model is addressed in
this work. Four novel SSD algorithms namely HC, SOOP, HC+ SOOP and V-SOOP, based …
this work. Four novel SSD algorithms namely HC, SOOP, HC+ SOOP and V-SOOP, based …
A Proposal for Parameter-Free Surrogate Building Algorithm Using Artificial Neural Networks
Surrogate models, capable of emulating the robust first principle based models, facilitate the
online implementation of computationally expensive industrial process optimization …
online implementation of computationally expensive industrial process optimization …