A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
J. V. Kadam, W. Marquardt Lehrstuhl für Prozesstechnik, RWTH Aachen University, Turmstr. 46, 52064 Aachen, Germany B. Srinivasan, D. Bonvin Laboratoire d’Automatique, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland Optimization of T ...
An analysis of unsupervised neural network models and the use of self-organizing maps in the real-time monitoring of power transformers was carried out. The application of genetic algorithms in a complex optimization problem, the allocation and parameters ...
Exergetic analysis is derived from the First and Second Laws of thermodynamics is shown to be an excellent tool to analyse and characterize industrial processes. A coherent link to pinch technology is shown which allows the designer to extend design consid ...
In spite of many success stories in various domains, genetic algorithms and genetic programming still suffer from some significant pitfalls. Those evolved programs often lack important properties such as robustness, comprehensibility, transparency, modifia ...
The presented paper deals with a constrained optimisation technique for the calibration of elasto-plastic model parameters in a rational and objective manner. The procedure consists in finding a set of model parameters which minimise the difference between ...
This report presents a new methodological approach for the optimal design of energy integrated batch processes. The main emphasis is put on indirect and, to some extend, on direct heat exchange networks with the possibility of introducing closed or open st ...
Matching Pursuit is a greedy algorithmthat decomposes any signal into a linear expansion of waveforms taken from a redundant dictionary. Computing the projection of the signal on every element of the basis has a high computational cost. To reduce this comp ...
This paper introduces a multi-objective EA, termed the Clustering Pareto Evolutionary Algorithm (CPEA). The CPEA finds and retains many local Pareto- optimal fronts, rather than just the global front as is the case of most multi- objective EAs found in the ...
We present a new approach that is able to produce an increased fault tolerance in bio-inspired electronic circuits. In order to do so, we designed hardware-friendly genetic regulatory networks based on a bio-inspired hardware architecture called POEtic tis ...
This paper presents a genetic algorithm to seek the optimal location of multi-type FACTS devices in a power system. The optimizations are performed on three parameters: the location of the devices, their types and their values. The system loadability is ap ...