Author

Mandar K. Mokashi

Department of Computer Science and Engineering (Artificial Intelligence & Analytics), School of Computing, (Artificial Intelligence and Analytics), MIT-ADT University, Pune, Maharashtra, 412201, India

Published papers: 2
Citations: 0
Views: 541
Downloads: 287

Publications

2 papers

Open Access Research Article·pp. 587–596·Vol. 29, Issue 3Mar 2026

Efficient solving of partial differential equations with new numerical methods

Ravi Yadav, Tanveer Ahmad Wani, Mandar K. Mokashi, Shirish Jaysing Navale, Egambergan Khudaynazarov, Swati V. Khidse

Published Online: 18 Mar 2026DOI: 10.47974/JIM-2493

In this paper: Partial Differential Equations (PDEs) play a very significant role in the life of scientists and engineers who wish to model complex physical processes. However, standard solutions to math have a hard...

Abstract References Full Text PDF (476 KB)Views: 255Downloads: 123Citations: 0

Open Access Research Article·pp. 693–700·Vol. 29, Issue 3Mar 2026

Fractional calculus applications in deep learning architectures

Chandrakant Deelip Kokane, Anjali S. More, Harsha Jitendra Sarode, Mandar K. Mokashi, Sonali Prashant Bhoite, Mahesh Ashok Bhandari

Published Online: 18 Mar 2026DOI: 10.47974/JIM-2504

In this paper: The study investigates the application of the concept of the addition of a deep learning system to fractional calculus (FC) in order to accelerate and generalize the learning process. We propose a dif...

Abstract References Full Text PDF (488 KB)Views: 286Downloads: 164Citations: 0