Write in a clean editor, then format for Advances in Data Science and Adaptive Analysis in one click — DocuGuru applies the official World Scientific template with superscript references and exports a submission-ready PDF plus the editable LaTeX source. Free to start.
Advances in Data Science and Adaptive Analysis is a peer-reviewed journal published by World Scientific, covering Machine Fault Diagnosis Techniques, Structural Health Monitoring Techniques, Image and Signal Denoising Methods.
| Publisher | World Scientific |
|---|---|
| Reference style | Superscript numbered (World Scientific) Superscript — small raised numerals in the text 1. Smith, A., Jones, B. & Lee, C. A representative article title. Advances in Data Science and Adaptive Analysis 12, 45–58 (2023).
Formats any DOI in the closest standard style — Advances in Data Science and Adaptive Analysis has no published style definition, so this is an approximation. No sign-up. |
| Publishes research in | Machine Fault Diagnosis Techniques Structural Health Monitoring Techniques Image and Signal Denoising Methods EEG and Brain-Computer Interfaces Imbalanced Data Classification Techniques |
| ISSN | 2424-922X |
| Citation impact (2-yr) | 4.63 |
| h-index | 11 |
| i10-index | 15 |
| Total citations | 596 |
| Top institutions publishing here | San Diego State University |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Accurate anticipation of fluctuations in commodity valuations is critical for diverse stakeholders, encompassing policymakers, investors, and supply chain entities, to ensure informed decision-making within volatile markets. As a staple edible oil, peanut oil exhibits pronounced price volatility, necessitating robust predictive frameworks to mitigate economic risks. This study leverages a decade-long weekly wholesale price index data…
Empirical mode decomposition (EMD) provides an adaptive, data-driven approach to time–frequency analysis, yielding components from which local amplitude, phase, and frequency content can be derived. Since its initial introduction to electroencephalographic (EEG) data analysis, EMD has been extended to enable phase synchrony analysis and multivariate data processing. EMD has been integrated into a wide range…
In every educational institution, predicting pupils’ performance is a vital responsibility. Due to this, a variety of data mining techniques, such as clustering, classification, and regression, are applied to anticipate the learner’s study behavior. By Machine Learning’s arrival, it has become vital to forecast students’ academic achievement, and this study attracts significant attention within the…
For a considerable amount of time, many market participants have placed great importance on price forecasts for major metal commodities. To tackle the problem, our study looks at the price of copper recorded on a daily basis. The sample under inquiry spans more than 10 years, from 01/02/2014 to 04/12/2024, and the price series under…
The commonly used index for measuring pavement roughness is the International Roughness index (IRI). Traditional method for collecting road surface information is expensive and as such researchers over the years have resorted to other cheaper ways of collecting data. This study focuses on developing a deep learning model to quickly and accurately determine the IRI…
