Usage of machine learning methods for cause-effect graph feasibility prediction
Cause-effect graphs (CEGs) are usually applied for black-box testing of complex industrial
systems. The specification process is time-consuming and can result in many errors. In this …
systems. The specification process is time-consuming and can result in many errors. In this …
Usage of cause‐effect graphs for reliability analysis of an embedded IoT alarm software system
Software is a part of most complex systems used for different purposes in today's world. The
reliability of these systems must be verified before putting them to use, because their …
reliability of these systems must be verified before putting them to use, because their …
An Empirical Approach of Developing Domain Based Ontology in the Field of Bioinformatics
D Suresh, EA Banu, R Karthikeyan… - 2024 4th …, 2024 - ieeexplore.ieee.org
From a macro viewpoint, it is essential to comprehend the similarities across human
illnesses in order to identify underlying mechanisms at the microscopic level. Previous …
illnesses in order to identify underlying mechanisms at the microscopic level. Previous …
[HTML][HTML] ETF-RI-CEG-Advanced: A graphical desktop tool for black-box testing by using cause–effect graphs
Researchers and domain experts usually require the help of software packages for black-
box testing complex systems using cause–effect graphs. However, there are only a few …
box testing complex systems using cause–effect graphs. However, there are only a few …