An elicitation process to quantify Bayesian networks for dam failure analysis

rodbar dam slope stability analysis using neural networks

در این تحقیق شبکه عصبی مصنوعی برای پیش بینی مقادیر ضریب اطمینان و فاکتور ایمنی بحرانی سدهای خاکی ناهمگن ضمن در نظر گرفتن تاثیر نیروی اینرسی زلزله ارائه شده است. ورودی های مدل شامل ارتفاع سد و زاویه شیب بالا دست، ضریب زلزله، ارتفاع آب، پارامترهای مقاومتی هسته و پوسته و خروجی های آن شامل ضریب اطمینان می شود. مهمترین پارامتر مورد نظر در تحلیل پایداری شیب، بدست آوردن فاکتور ایمنی است. در این تحقیق ...

An Introduction to Inference and Learning in Bayesian Networks

Bayesian networks (BNs) are modern tools for modeling phenomena in dynamic and static systems and are used in different subjects such as disease diagnosis, weather forecasting, decision making and clustering. A BN is a graphical-probabilistic model which represents causal relations among random variables and consists of a directed acyclic graph and a set of conditional probabilities. Structure...

Building Bayesian Networks : Elicitation , Evaluation , and Learning

Elicitation for Bayesian Phylogeny

Phylogeny provides important information for evolutionary relationships and is useful in applications. Bayesian phylogenetic inference developed quickly because of its computational feasibility. However, the vague priors usually used in Bayesian phylogenetics do not capture knowledge available from non-genetic sources such as studies of physiology and development. This thesis gives a practical ...

Knowledge Elicitation for Predictive Maintenance Modelling with Bayesian Networks

Predictive maintenance is closely connected to condition monitoring, health and usage monitoring systems (HUMS), prognostic modeling and condition-based maintenance (CBM). It is concerned with identifying what maintenance actions should be chosen and when, based on the predicted state of the item of interest over time. It can be viewed as a logical development of CBM. The authors of this paper ...