https://journals.threws.com/index.php/IJSCS <p><strong>International Journal of Statistical Computation and Simulation</strong></p> <p><strong>Scope:</strong></p> <p>The International Journal of Statistical Computation and Simulation is a peer-reviewed scholarly publication dedicated to advancing the field of statistical computation and simulation. This journal serves as a platform for researchers, academics, and practitioners to disseminate their innovative contributions and engage in meaningful discourse regarding statistical methods, computational techniques, and simulation applications.</p> <p><strong>Key Focus Areas:</strong></p> <ol> <li> <p><strong>Statistical Methods:</strong> The journal covers a wide array of statistical methods, from classical techniques to modern approaches. Topics include, but are not limited to, regression analysis, time series analysis, Bayesian statistics, and multivariate analysis.</p> </li> <li> <p><strong>Computational Techniques:</strong> This journal explores computational methods and algorithms used in statistical analysis. It embraces the latest advancements in numerical and computational tools, including software packages, high-performance computing, and parallel computing for statistical applications.</p> </li> <li> <p><strong>Simulation Studies:</strong> Researchers and practitioners are encouraged to submit papers related to simulation studies, encompassing Monte Carlo methods, agent-based modeling, and discrete-event simulation. This area delves into the design, analysis, and interpretation of simulation experiments.</p> </li> <li> <p><strong>Statistical Software Development:</strong> The journal welcomes contributions related to the development of statistical software, packages, and tools that facilitate statistical computation and analysis. It offers a platform for sharing open-source resources and fostering collaboration among software developers.</p> </li> <li> <p><strong>Applications:</strong> The journal acknowledges the importance of real-world applications of statistical computation and simulation. It welcomes articles that apply statistical techniques and simulations in various domains, such as economics, engineering, social sciences, and healthcare.</p> </li> <li> <p><strong>Data Analytics:</strong> The scope of the journal extends to data analytics, including big data analytics and data mining. It explores the role of statistical methods and simulations in uncovering meaningful insights from large and complex datasets.</p> </li> <li> <p><strong>Computational Statistics Education:</strong> Contributions pertaining to the pedagogy of computational statistics and simulation in academic and professional settings are encouraged. This includes innovative teaching methods, curriculum development, and educational resources.</p> </li> </ol> <p><strong>Aims and Objectives:</strong></p> <ul> <li>To provide a global platform for the exchange of knowledge and ideas in statistical computation and simulation.</li> <li>To facilitate collaboration among researchers, practitioners, and educators in the field of statistics.</li> <li>To foster innovation and advancements in statistical methods and computational techniques.</li> <li>To promote the development of open-source statistical software and tools.</li> <li>To encourage the application of statistical computation and simulation in solving real-world problems across diverse domains.</li> <li>To contribute to the growth and improvement of statistical education and training worldwide.</li> </ul> <div><strong><em><br /></em> <em>IJSCS </em> </strong>does not consider applications of statistics to other fields, except as illustrations of the use of the original statistics presented.</div> <div> </div> <div>Accepted papers should ideally appeal to a wide audience of statisticians and provoke real applications of theoretical constructions.</div> <div> </div> <div> <div align="left"><strong>Impact Factor </strong></div> <div align="left"> </div> <div align="left"><strong>International Journal of Statistical Computation and Simulation is a double-blind peer-reviewed journal indexed in several databases like google scholar, Wos, Dooj, ESCI </strong></div> <div align="left"> </div> <div align="left"> <p>JCR Impact Factor: 4.6 (2019)</p> <p>JCR Impact Factor: 5.6 (2020)</p> <p>JCR Impact Factor: 5.9 (2021)</p> <p>JCR Impact Factor : 6.1 (2022)</p> <p>JCR Impact Factor : Under Evaluation (2023)</p> </div> </div> <div align="left"> </div> <div align="left"><strong>Peer Review Policy</strong></div> <div align="left"><br />All submitted manuscripts are subject to initial appraisal by the Editors. If found suitable for further consideration, papers are subject to peer review by independent, anonymous expert referees, under the guidance of a team of expert Associate Editors. All peer-review is double-blind and submissions can be made online via the Submission Portal.</div> <p><br /><strong>Publishing Ethics</strong></p> <div align="left">The Journal adheres to the highest standards of publishing ethics, with rigorous processes in place to ensure this is achieved. We are member of the Committee of Publications Ethics (COPE) and utilizes CrossCheck for all Journals. </div> The research world en-US International Journal of Statistical Computation and Simulation https://journals.threws.com/index.php/IJSCS/article/view/341 <p>Transportation is a significant contributor to carbon emissions and environmental degradation. This paper explores sustainable transportation solutions, focusing on electric vehicles (EVs), hydrogen fuel cells, public transportation systems, and bike-sharing initiatives. It evaluates the potential of green mobility technologies to reduce carbon footprints, improve air quality, and promote urban sustainability. The paper also discusses the role of government policies, infrastructure investments, and behavioral change in fostering widespread adoption of sustainable transportation systems.</p> Prof. Anu Sharma Copyright (c) 2025 2025-01-09 2025-01-09 17 1 https://journals.threws.com/index.php/IJSCS/article/view/342 <p>Biodiversity is essential for maintaining ecosystem health, providing vital services such as clean air, water, and food production. This paper explores the importance of biodiversity conservation in the context of global sustainability, focusing on the threats posed by habitat loss, climate change, and overexploitation of natural resources. It discusses strategies for protecting biodiversity, including ecosystem restoration, conservation policies, and community-based approaches. The paper also examines the role of corporations, governments, and individuals in safeguarding ecosystems for the benefit of future generations.</p> Prof. Ramesh Kumar Copyright (c) 2025 2025-01-10 2025-01-10 17 1 https://journals.threws.com/index.php/IJSCS/article/view/382 <p>In today's rapidly evolving digital landscape, ensuring the security and resilience of databases in cloud environments is paramount. Traditional methods of database security and disaster recovery are often insufficient to address the growing sophistication of cyber threats and system failures. This paper explores AI-driven approaches to enhancing database security and disaster recovery processes. By leveraging machine learning, predictive analytics, and automation, organizations can proactively detect security vulnerabilities, mitigate threats, and recover from disasters more efficiently. AI algorithms can identify anomalous patterns in database activity, predict potential failures, and automate recovery actions, reducing downtime and minimizing the impact of security breaches. This paper discusses the role of AI in strengthening database resilience, the integration of AI with existing security frameworks, and the application of intelligent disaster recovery strategies to ensure business continuity in the face of unforeseen events.</p> Sanjay Bauskar Copyright (c) 2025 2025-02-14 2025-02-14 17 1 1 15 https://journals.threws.com/index.php/IJSCS/article/view/384 <p>Digital twins have revolutionized predictive analytics, but their adaptability and cognitive capabilities remain limited. This paper introduces <strong data-start="2946" data-end="2991">Neuro-Evolutionary Cognitive Twins (NECT)</strong>, a novel AI-driven digital twin framework that integrates neuro-symbolic reasoning with evolutionary optimization. NECT continuously learns from real-time sensor data, self-adapting to dynamic changes in complex industrial and healthcare systems. Our results demonstrate that NECT outperforms traditional digital twin models in accuracy, resilience, and decision-making efficiency. This research lays the groundwork for intelligent, autonomous digital twins capable of self-learning and predictive evolution.</p> Prof. Chan chu Copyright (c) 2025 2025-01-07 2025-01-07 17 1 https://journals.threws.com/index.php/IJSCS/article/view/385 <p>Existing optimization techniques for autonomous systems often struggle with balancing adaptability and efficiency. This paper introduces <strong data-start="3769" data-end="3787">HoloGenetic AI</strong>, a novel holomorphic genetic algorithm that merges quantum-inspired holomorphic functions with evolutionary computing. HoloGenetic AI dynamically adapts optimization strategies based on environmental variations, significantly improving decision-making in autonomous vehicles, robotics, and smart grids. Benchmark evaluations demonstrate superior convergence speed and adaptability over traditional genetic algorithms, offering a new frontier in adaptive AI-driven optimization.</p> Prof. Ramesh Kumar Copyright (c) 2025 2025-01-14 2025-01-14 17 1