Machine Learning for Time Series Analysis
Deadline for manuscript submissions: closed (15 July 2023) | Viewed by 16264
Interests: AI/ML; cybersecurity; information security; blockchain technology; intelligent vehicles; big data analysis
Interests: AI; IoT; smart city; e-healthcare; blockchain; connected vehicles; wireless communication
Special Issues, Collections and Topics in MDPI journals
We invite you to submit your latest research in the area of time series analysis. Data acquired from a smart environment (accommodated with smart devices and sensors) over a uniform period of time is acknowledged as time-series data. Each data point is attributed to time fixed point of time arranged in chronological order like temperature over time, acceleration data per sec, etc. Further to attain meaningful information from time-series data and perform an action based on the same information, one needs to perform statistical analysis. Time series learning is a subfield of machine learning which are mathematically designed to compute sequential data. Time series machine learning can be deployed in various applications concerned with pattern detection, future trends, and prediction based on past data. Machine learning on time series data has superiority over simple traditional statistical analysis because of the advancements in its algorithmic models and improved time series forecasting technology. It has tremendous potential for business operations, day-to-day forecast requirements, and also for other various pattern prediction facilities.
Dr. Madhusudan Singh
Dr. Dhananjay Singh
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- sequential data
- irregular data
- pattern analysis
- future prediction
- time series forecasting
- trend analysis
- unsupervised and semi-supervised learning
- hidden markov model
- recurrent neural network
- ARIMA- autoregressive integrated moving average
- STD- seasonal trend decomposition
- ARCH- auto-regressive conditionally heteroscedastic