6 papers
Addressing Challenges in Time Series Forecasting: A Comprehensive Comparison of Machine Learning Techniques
Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang
The explosion of Time Series (TS) data, driven by advancements in technology, necessitates sophisticated analytical methods. Modern management systems increasingly rely on analyzin…
Physics-Informed Neural Networks with Unknown Partial Differential Equations: an Application in Multivariate Time Series
Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang, Ali Mohammad-Djafari
A significant advancement in Neural Network (NN) research is the integration of domain-specific knowledge through custom loss functions. This approach addresses a crucial challenge…
Signed Rank Chart For Tied Observations: An Application of Deep Learning Models
Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang
Shewhart Control Charts (SCC)s are constructed under the assumption of normality and are widely recognized in statistical quality control by numerous researchers. Problems arise wh…
A historical view on the maximum entropy
Seyedeh Azadeh Fallah Mortezanejad
How to find unknown distributions is questioned in many pieces of research. There are several ways to figure them out, but the main question is which acts more reasonably than othe…
Dependence control chart using maximum copula entropy
Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang, Gholamreza Mohtashami Borzadaran +1
Statistical quality control methods are noteworthy to producing standard production in manufacturing processes. In this regard, there are many classical manners to control the proc…
Profile control chart based on maximum entropy
Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang, Gholamreza Mohtashami Borzadaran +2
Monitoring a process over time is so important in manufacturing processes to reduce the waste of money and time. Some charts as Shewhart, CUSUM, and EWMA are common to monitor a pr…