Güldem Yıldız | Mathematics | Best Paper Award

Published on by Best Achievements

Best Paper Award

Güldem Yıldız
Nigde Omer Halisdemir University

Güldem Yıldız
Affiliation Nigde Omer Halisdemir University
Country Turkey
Article Title Solving the Gardner Equation Through the Sardar Sub-Equation Method and a Hybrid Artificial Neural Network Model
Scopus ID 55735455100
Article Type Research Article
Article Views 192
Reference Count 40
Award Category Best Paper Award
Event Global Best Achievements Awards
ORCID 0000-0002-8120-3525

Güldem Yıldız of Nigde Omer Halisdemir University, Turkey, is associated with the 2026 research article Solving the Gardner Equation Through the Sardar Sub-Equation Method and a Hybrid Artificial Neural Network Model, published by MDPI. The study concerns the Mathematics subject area and combines an analytical sub-equation technique with a hybrid artificial neural network framework. The supplied publication record reports 192 article views and 40 references. The research is presented in connection with the Best Paper Award category of the Global Best Achievements Awards.

Abstract

This article presents the academic recognition of Güldem Yıldız for research on solving the Gardner equation through the Sardar Sub-Equation Method and a hybrid artificial neural network model. The work addresses an analytical and computational treatment of a nonlinear mathematical equation, combining a sub-equation approach with neural-network-based modeling. Such a hybrid framework connects symbolic solution techniques with data-driven approximation, offering a structured basis for examining nonlinear wave equations and related mathematical behavior. The research was published by MDPI in 2026 and is associated with the Mathematics subject area. This page summarizes the researcher, scientific context, methodology, contributions, and recognition academically.

Keywords

Keywords: Gardner equation; Sardar Sub-Equation Method; artificial neural networks; hybrid computational model; nonlinear equations; mathematical physics; analytical solutions; Mathematics.

Introduction to the Research Topic

The Gardner equation is a nonlinear partial differential equation studied in mathematical physics. Analytical methods can provide explicit solution forms, while computational learning approaches can approximate relationships. The reported study combines the Sardar Sub-Equation Method with a hybrid artificial neural network model, linking analytical and computational perspectives in nonlinear research. [1]

Research Profile

Güldem Yıldız is affiliated with Nigde Omer Halisdemir University, Turkey, and is represented in Scopus by Author ID 55735455100 and in ORCID by 0000-0002-8120-3525. The supplied research record identifies Mathematics as the subject area, with six documents, seventeen citations, and an h-index of one at the time of this profile. [2] [3]

Scientific Background

The Gardner equation extends nonlinear wave models by incorporating nonlinear effects, making its solution structure relevant to applied mathematics and mathematical physics. Sub-equation methods seek tractable analytical forms, whereas artificial neural networks provide computational approximation. Combining these perspectives can support comparison between explicit solutions and learned representations for nonlinear research. [1]

Methodology

The approach uses the Sardar Sub-Equation Method to construct analytical solutions of the Gardner equation, followed by a hybrid artificial neural network model computationally. The methodology connects symbolic derivation with numerical or learning-based approximation. The article title establishes this methodological combination, while implementation should be verified in the published article. [1]

Key Findings

The study addresses the Gardner equation through a sub-equation solution method and a hybrid artificial neural network model. This combination indicates an emphasis on complementary analytical and computational treatment rather than one technique. Solution families, numerical results, training procedures, and error measures should be taken directly from the article carefully. [1]

Scientific Contributions

The contribution described by the title is the integration of the Sardar Sub-Equation Method with a hybrid artificial neural network framework for the Gardner equation. This approach connects established analytical solution techniques with computational learning. The work provides context for comparing symbolic formulations and model-based approximations in nonlinear mathematical analysis. [1]

Conclusion

The recognized research focuses on a hybrid treatment of the Gardner equation that combines an analytical sub-equation method with artificial neural network modeling. Its publication in 2026 places the work within current mathematical research. Further assessment of solution accuracy, generalization, and comparative performance requires consultation of the complete published study. [1]

References

    1. MDPI. (2026). Solving the Gardner Equation Through the Sardar Sub-Equation Method and a Hybrid Artificial Neural Network Model. Symmetry.
      https://doi.org/10.3390/sym18091479
    2. Elsevier. (n.d.). Scopus author details: Güldem Yıldız, Author ID 55735455100. Scopus.
      https://www.scopus.com/authid/detail.uri?authorId=55735455100
    3. ORCID. (n.d.). Güldem Yıldız, ORCID iD 0000-0002-8120-3525. ORCID.
      https://orcid.org/0000-0002-8120-3525

Bo You | Mathematics | Best Researcher Award

Published on by Best Achievements

Prof. Bo You | Mathematics | Best Researcher Award

Prof. Bo You, Xi’an Jiaotong University, China.

Professor. Bo You is a Full Professor at Xi’an Jiaotong University since 2022. He earned his Ph.D. in Mathematics from Lanzhou University in 2012. His research interests include Nonlinear Functional Analysis, Nonlinear PDEs, and Infinite Dimensional Dynamical Systems. Professor You has secured multiple NSFC grants and organized various international workshops. He actively teaches courses on Mathematical Physics, Real Analysis, and Functional Analysis, while also supervising PhD and MSc students in their research.

Professional Profile

SCOPUS ID

🎓 Education

Bo You completed his PhD in Mathematics from Lanzhou University (2007–2012), laying the foundation for his distinguished academic career. Prior to that, he earned his Bachelor of Science degree from Lanzhou University in 2007. His academic journey has focused on advancing the field of Nonlinear Functional Analysis and Partial Differential Equations, culminating in a rich body of research that has contributed significantly to these areas.

🔬Research Contributions  On Mathematics

Professor. Bo You’s research has significantly advanced the fields of nonlinear functional analysis and partial differential equations (PDEs). His work on infinite-dimensional dissipative dynamical systems and the controllability and stabilization of PDEs has provided valuable insights for both theoretical and applied mathematics. Notably, his research on global Carleman estimates and continuous data assimilation has made a lasting impact on the mathematical community, influencing the study of complex systems in various scientific disciplines.

💼Professional Background 

Professor. Bo You has made significant contributions to Mathematics through his roles as a Full Professor at Xi’an Jiaotong University since 2022. Previously, he served as an Associate Professor and Assistant Professor at the same institution. He also held a Visiting Scholar position at Florida State University. Bo’s expertise spans Nonlinear Functional Analysis, Partial Differential Equations, and Dynamical Systems, supported by various research grants and notable conference talks worldwide. 🧑‍🏫

📚 Teaching Contributions

  • Carleman Estimates and Its Applications, XJTU (2023-2024)
  • Equations of Mathematical Physics, XJTU (2023-2024)
  • Real Analysis, XJTU (2022–2024)
  • Nonlinear Analysis, XJTU (2018–2022)

💰 Research Grants

  • NSFC (01/2019–12/2022)
  • NSBRP (01/2018–12/2019)
  • NSFC (01/2015–12/2017)

🛠️ Activities Organized

  • Workshops on Nonlinear Analysis and PDEs, XJTU-TENCENT (08/2023)
  • Summer School on Nonlinear Functional Analysis, XJTU-TENCENT (07/2023)
  • Workshops on Infinite Dimensional Dynamical Systems, XJTU-ZOOM (07/2020)

🏅 Impact And Honor 🏅

Professor. Bo You has significantly contributed to the fields of Nonlinear Functional Analysis and Partial Differential Equations, advancing theoretical research and practical applications. His groundbreaking work has earned him prestigious research grants and recognition globally. With numerous key conference talks and workshops organized, his influence extends across academia and industry, shaping the future of mathematics. His leadership in guiding PhD and MSc students has earned him immense respect and honor in the academic community. 🌍📚

Conclusion

Professor Bo You has made significant contributions to mathematics and nonlinear analysis. His work on partial differential equations and dynamical systems has garnered global recognition. Through his leadership in research, teaching, and supervising future scholars, he continues to inspire and advance the field with dedication and excellence. 🧑‍🏫

📚Publication Top Notes

📝 Global Attractor of the Euler-Bernoulli Equations with a Localized Nonlinear Damping

Li, F., You, B.
Journal: Discrete and Continuous Dynamical Systems, 2024
Access: Open Access

🌊 Continuous Data Assimilation for the Three-Dimensional Planetary Geostrophic Equations of Large-Scale Ocean Circulation

You, B.
Journal: Zeitschrift fur Angewandte Mathematik und Physik, 2024

🔄 A Discrete Data Assimilation Algorithm for the Three-Dimensional Planetary Geostrophic Equations of Large-Scale Ocean Circulation

You, B.
Journal: Journal of Dynamics and Differential Equations, 2024: 0

💉 Optimal Distributed Control for a Cahn-Hilliard Type Phase Field System Related to Tumor Growth

You, B.
Journal: Mathematical Control and Related Fields, 2024

🧬 Optimal Control of a Phase Field Tumor Growth Model with Chemotaxis and Active Transport

You, B.
Journal: Mathematical Control and Related Fields, 2024
Citations: 0

 

Nur Alam | Mathematics | Best Researcher Award

Published on by Best Achievements

Prof. Dr. Md.  Nur Alam | Mathematics | Best Researcher Award

Prof. Dr.  Md. Nur Alam, Pabna University of Science and Technology,  Bangladesh.

Prof. Dr. Md. Nur Alam is a distinguished academic and researcher in the field of computational mathematics. He is currently a Professor in the Department of Mathematics at Pabna University of Science and Technology, Bangladesh. He completed his B.Sc. (Hons.) and M.Sc. (Thesis) in Mathematics from Rajshahi University, achieving top honors. He went on to earn an M.Phil. in mathematical physics and a Ph.D. in Computational Mathematics under the prestigious CAS-TWAS Scholarship at the University of Science and Technology of China (USTC). Recognized among the top 2% of scientists worldwide by Elsevier and Stanford University in 2022, 2023, and 2024, Prof. Alam has made significant contributions to fields like subdivision schemes, geometric modeling, and computational fluid dynamics. With over 130 published articles and a remarkable h-index of 31, his research is highly cited, reflecting his impact in applied mathematics and engineering.

Professional Profile:

Summary of Suitability for Best Researcher Award:

Prof. Dr. Md. Nur Alam is a distinguished academic in the field of Computational Mathematics, with notable expertise spanning subdivision schemes, geometric modeling, bilinear neural networks, and computer-aided geometric design (CAGD). He is currently a Professor at the Department of Mathematics, Pabna University of Science and Technology (PUST), Bangladesh, and has consistently demonstrated academic excellence and significant research impact.

🎓 Education:

Prof. Dr. Md. Nur Alam has a robust academic background rooted in mathematics and computational science. He earned his B.Sc. (Hons.) and M.Sc. in Mathematics from Rajshahi University, Bangladesh, where he graduated with top academic honors. He pursued an M.Phil. in Mathematical Physics, further solidifying his expertise in advanced mathematical theories. Driven by a passion for computational mathematics, he completed his Ph.D. at the University of Science and Technology of China (USTC) through the prestigious CAS-TWAS Scholarship. His doctoral research focused on developing innovative computational techniques, providing significant advancements in geometric modeling and subdivision schemes.

💼Work Experience:

Prof. Dr. Md. Nur Alam has extensive experience in academia and research. He currently serves as a Professor at the Department of Mathematics, Rajshahi University, Bangladesh, where he also leads various research initiatives in computational mathematics. Prof. Alam has held visiting researcher positions at renowned institutions like the University of Science and Technology of China (USTC). His work spans multiple disciplines, including geometric modeling, subdivision schemes, and applied mathematics. He has supervised numerous postgraduate students and contributed to several international collaborative projects, publishing extensively in high-impact journals and advancing mathematical research globally.

🌍 Research Skills: 

Prof. Alam is an expert in a range of computational and applied mathematics areas, including subdivision schemes, geometric modeling, and computational fluid dynamics. His skills encompass both theoretical and practical aspects of mathematics, with proficiency in numerical analysis, mathematical modeling, and algorithm development. His research also extends to differential equations, applied mechanics, and mathematical software, with an emphasis on solving real-world engineering problems. Proficient in MATLAB, Mathematica, and other computational tools, Prof. Alam is adept at simulating complex mathematical models to derive innovative solutions.

🥇Award and Honors:

Prof. Dr. Md. Nur Alam is a highly acclaimed researcher recognized for his outstanding contributions to the field of mathematics. He has been listed among the top 2% of scientists worldwide by Elsevier and Stanford University consecutively in 2022, 2023, and 2024. His excellence in research has been acknowledged with multiple national and international awards, highlighting his innovative work in computational mathematics. With over 130 published research articles and a remarkable h-index of 31, he has gained significant recognition in both academic and professional circles. Prof. Alam’s work continues to inspire and drive advancements in mathematical and computational sciences.

Conclusion:

Prof. Dr. Md. Nur Alam’s outstanding research contributions, academic leadership, and international recognition highlight his profound impact in the domain of computational mathematics. His continuous pursuit of academic excellence, demonstrated by numerous prestigious awards and significant research outputs, makes him a highly deserving candidate for the Best Researcher Award. His dedication to both research and education exemplifies a remarkable career, aligning perfectly with the award’s criteria for recognizing outstanding scholarly achievements.

📖 Publication Top Notes

A novel (G’/G)-expansion method and its application to the Boussinesq equation

  • Authors: MN Alam, MA Akbar, Syed Tauseef Mohyud-Din
  • Journal:  Chin. Phys. B
  • Year:  2014
  • Cited: 149

Traveling wave solutions for some important coupled nonlinear physical models via the coupled Higgs equation and the Maccari system

  • Authors: MG Hafez, Md N Alam, MA Akbar
  • Journal:  Journal of King Saud University-Science
  • Year:  2015
  • Cited: 113

New computational results for a prototype of an excitable system

  • Authors: H Ahmad, MN Alam, M Omri
  • Journal:  Results in Physics
  • Year:  2021
  • Cited: 77

Traveling wave solutions of the nonlinear Drinfel’d-Sokolov-Wilson equation and modified Benjamin-Bona-Mahony equations

  • Authors: K Khan, MA Akbar, MN Alam
  • Journal:  Journal of Egyptian Mathematical Society.
  • Year:  2013
  • Cited: 74

An analytical method for solving exact solutions of the nonlinear Bogoyavlenskii equation and the nonlinear diffusive predator–prey system

  • Authors: MN Alam, Cemil Tunc
  • Journal:  Alexandria Engineering Journal
  • Year:  2016
  • Cited: 68