ENBIS-22 Trondheim Conference

Session

CONTRIBUTED Modelling 5 + Design of Experiment 5

28 Jun 2022, 16:30

EL6

Conveners

CONTRIBUTED Modelling 5 + Design of Experiment 5

• Hendry Raharjo (Chalmers University)

86. Statistical Machine Learning for defining the Design Space

Mr Joan Borràs-Ferrís (Universitat Politècnica de València)

28/06/2022, 16:30

Modelling

The ICH Q8 guideline [1] emphasized the Quality by Design (QbD) approach, according to which quality should be built into the product since its conception. A key component of the QbD paradigm is the definition of the Design Space (DS), defined as the multidimensional combination and interaction of inputs variables that have been demonstrated to provide assurance of quality. Besides, Rozet et...

105. Threshold tuning methods in predictive monitoring

Paulina von Stackelberg (University of Amsterdam)

28/06/2022, 16:50

Modelling

Predictive monitoring techniques produce signals in case of a high probability of an undesirable event, such as machine failure, heart attacks, or mortality. When using these predicted probabilities to classify the unknown outcome, a decision threshold needs to be chosen in statistical and machine learning models. In many cases, this is set to 0.5 by default. However, in a high number of...

118. Electricity load forecasting using singular spectrum analysis, fuzzy systems, and neural networks

Prof. Paulo Canas Rodrigues (Federal University of Bahia, Brazil)

Modelling

Hybrid methodologies have become popular in many fields of research as they allow researchers to explore various methods, understand their strengths and weaknesses and combine them into new frameworks. Thus, the combination of different methods into a hybrid methodology allows for overcoming the shortcomings of each singular method. This paper presents the methodology for two hybrid methods...