Representing Time Series Data in Intelligent Training Systems
نویسندگان
چکیده
منابع مشابه
Missing data imputation in multivariable time series data
Multivariate time series data are found in a variety of fields such as bioinformatics, biology, genetics, astronomy, geography and finance. Many time series datasets contain missing data. Multivariate time series missing data imputation is a challenging topic and needs to be carefully considered before learning or predicting time series. Frequent researches have been done on the use of diffe...
متن کاملRepresenting Time in Multimedia Systems
As multimedia systems deal with a variety of temporally interrelated media items, synchronization is an important issue in those systems. One part of synchronization is the representation of temporal information. In contrast to traditional computing tasks, multimedia imposes new requirements on the representation of time. Specifically, a fine-grained and a flexible temporal model is required. T...
متن کاملIntelligent clinical training systems.
Clinical medicine is one of the most chal lenging areas for education. The develop ment of clinical competence requires the assimilation of large amounts of knowl edge combined with acquisition of clinical skills and clinical problem-solving ability. Clinical skills include the technical skill in implementing a procedure as well as skill in patient consultation and physical exami nation. Clinic...
متن کاملIntelligent Analysis Techniques for Diabetes Data Time Series
We present a set of techniques to deal with data coming from home-monitoring of patients aaected by Insulin Dependent Diabetes Mellitus. The large amount and low quality of the data motivate the search for analysis and interpretation methods able to exploit the available knowledge on the problem domain. Through the use of probabilistic learning techniques we extract high-level descriptors of bo...
متن کاملModeling Time Series Data of Real Systems
Dynamics of complex systems is studied by first considering a chaotic time series generated by Lorenz equations and adding noise to it. The trend (smooth behavior) is separated from fluctuations at different scales using wavelet analysis and a prediction method proposed by Lorenz is applied to make out of sample predictions at different regions of the time series. The prediction capability of t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The International FLAIRS Conference Proceedings
سال: 2021
ISSN: 2334-0762
DOI: 10.32473/flairs.v34i1.128508