Journal Overview

In the era of big data analysis, stochastic modeling tools play a pivotal role. JADAMSM focuses on research that bridges theoretical/conceptual foundations and practical execution. We emphasize papers delivering new algorithms and actionable solutions to complex business and scientific problems through data processing, modeling, analysis, and interpretation.

Additionally, the journal serves as a key venue for theoretical advances in stochastic differential and integro-differential equations (of both integer and fractional order derivatives), probability theory, and general mathematical analysis.

Core Focus & Technical Scope

JADAMSM considers manuscripts covering a broad spectrum of quantitative techniques and applied sciences, with particular interest in:

• Mathematical Analysis & Applied Probability Theory
• Stochastic Differential and Integro-Differential Equations
• Fractional and Integer Order Derivatives
• Big Data Analytics & High-Dimensional Data Processing
• Algorithmic Solutions for Complex Business Problems
• Stochastic Modeling & Generalization Methods

Peer Review & Quality Control

• Review Model: Double-blind peer review (both author and reviewer identities remain strictly anonymous).
• Expert Assessment: Every qualifying submission is assigned to a minimum of 3 expert reviewers specializing in the subject area.
• Plagiarism Prevention: All manuscripts undergo automated similarity checks via Turnitin prior to formal evaluation and publication.

Open Access & Licensing Framework

• Access Policy: Fully Open Access. All published content is immediately and permanently accessible online to readers worldwide without subscription fees or paywalls.
• Copyright & Licensing: Articles are published under the Creative Commons Attribution 4.0 International License (CC BY 4.0). Authors retain copyright while permitting anyone to share, adapt, and build upon the work (including commercial uses), provided proper attribution is given to the original authors.
• AI Policy: JADAMSM permits the ethical use of Generative AI (GenAI) as supportive tools to assist research design and data processing, strictly adhering to high standards of academic transparency and originality.

Indexing & Abstracting

JADAMSM is committed to broad global visibility and content discoverability across recognized databases: