Blazingprojects Mobile App
📚 Over 50,000 Research Thesis
📱 100% Offline: No internet needed
📝 Over 98 Departments
🔍 Thesis-to-Journal Publication
🎓 Undergraduate/Postgraduate Thesis
📥 Instant Whatsapp/Email Delivery
Mathematics
Showing 1-30 of 459 Thesis
A Unified Framework for Multiscale Spectral Graph Signal Theory...
This study addresses the fragmentation between discrete and continuous perspectives in spectral graph signal theory and proposes a unified multiscale framework ...
Optimal Transport in Municipal Transit Routing for City of Adelaide...
This study investigates how optimal transport theory can enhance municipal transit routing in the City of Adelaide to improve service reliability, reduce travel...
Comparative Study of Numerical Methods for Sparse Linear Systems ...
Incomputational science routinely solves large sparse linear systems arising from discretized partial differential equations and data-intensive applications; ho...
Efficient Graph Neural Networks for Real-Time IoT Anomaly Detection...
The rapid expansion of Internet of Things (IoT) ecosystems across critical sectors, including manufacturing, healthcare, and smart cities, has intensified the d...
Empirical Analysis of Numerical Methods in Real-World PDE Problems...
The accurate solution of partial differential equations (PDEs) arising in engineering and physics hinges on the reliability and efficiency of numerical methods ...
Design and Evaluation of Sparse Matrix Factorization Algorithms for Big Data...
The rapid growth of high-dimensional data arising from network analytics, recommender systems, and scientific simulations has intensified the need for scalable ...
A Unified Framework for Nonlinear Spectral Stability in Networked Systems...
This study addresses the challenge of ensuring robust stability in nonlinear dynamics across complex networked systems, where traditional linear spectral method...
Topology-informed risk assessment in a power grid microgrid network...
This study addresses the escalating risk exposure of contemporary microgrid networks within urban distribution systems, where topology-driven connectivity and o...
Comparative Analysis of Numerical Methods for Stochastic Differential Equations...
Stochastic differential equations (SDEs) provide a foundational framework for modeling systems influenced by random fluctuations across finance, physics, and en...
Graph Neural Networks for Dynamic Network Topology Optimization...
The rapid evolution of communication and sensor networks has intensified the need for adaptive network topologies that can respond to dynamic traffic patterns, ...
Empirical Analysis of Numerical Methods for Large-Scale PDE Solvers ...
This study addresses the practical performance and reliability of numerical methods used for solving large-scale partial differential equations (PDEs) in scient...
Efficient Numerical Methods for Large-Scale Sparse Linear Systems ...
This study addresses the challenge of solving large-scale sparse linear systems efficiently, a problem central to simulations in scientific computing, engineeri...
A Unified Framework for Fractional-Order Dynamical System Stability Analysis...
Fractional-order dynamical systems (FODS) offer a versatile modeling framework for intrinsic memory effects and anomalous diffusion across engineering, physics,...
Optimal Transport in Urban Logistics: A City Municipality Case Study...
Urban freight logistics in metropolitan areas faces rising congestion, emissions, and delivery delays, threatening service levels and urban livability. This stu...
Comparative Analysis of Spectral Methods for PDEs on Irregular Domains...
This study investigates the comparative performance of spectral methods for solving partial differential equations (PDEs) on irregular domains, addressing a gap...
Deep Learning Accelerated Numerical Methods for PDEs in Engineering Simulations...
This study investigates the use of deep learning surrogates to accelerate numerical solutions of partial differential equations (PDEs) in complex engineering si...
Empirical Analysis of Random Walks in Financial Market Microstructure...
This study investigates whether stock price movements in contemporary financial markets exhibit random-walk characteristics within the microstructure context, a...
Data-driven spectral methods for sparse PDE solvers: design, implement, evaluate...
The increasing demand for efficient and scalable solvers for sparse partial differential equations (PDEs) in high-dimensional and time-dependent problems motiva...
A Dual-Scale Framework for Nonlinear Spectral Graph Theory Analysis...
This study addresses the limitations of classical linear spectral methods in capturing nonlinear geometric and functional properties of large-scale graphs, wher...
Quantitative Risk Modelling in Renewable Energy Grids: A Case Study...
The rapid integration of intermittent renewable energy sources into modern power grids has heightened exposure to operational and market risks, challenging grid...
Comparative Analysis of Graph Neural Networks for Dynamics Prediction ...
Graph neural networks (GNNs) have emerged as powerful tools for modeling complex dynamical systems by exploiting relational structures in data. Despite rapid pe...
Optimizing Network Traffic Routing Using Deep Reinforcement Learning Algorithms...
The rapid expansion of digital communication networks has accentuated the critical need for efficient and adaptive traffic routing mechanisms to enhance network...
Analyzing the Impact of Real-World Data on Nonlinear Optimization Techniques...
The increasing availability of complex and high-dimensional real-world data has significantly influenced the development and application of nonlinear optimizati...
Design and Implementation of Numerical Methods for Solving Nonlinear Differential Eq...
Nonlinear differential equations (NDEs) are fundamental to modeling complex phenomena across diverse scientific and engineering disciplines, yet their analytica...
A Novel Framework for Multiscale Fractal Analysis in Complex Networks...
The complexity inherent in modern networks, such as social, biological, and technological systems, necessitates advanced analytical frameworks to capture their ...
Optimizing Inventory Management in Manufacturing Using Variational Inequalities...
Effective inventory management remains a critical challenge for manufacturing organizations seeking to minimize costs while maximizing operational efficiency. F...
Comparative Analysis of Numerical Methods for Solving Nonlinear Differential Equatio...
In the realm of mathematical modeling, nonlinear differential equations serve as fundamental tools for describing complex dynamical systems across sciences and ...
Deep Learning-Based Optimization of Network Routing Protocols for Smart Cities...
The rapid proliferation of interconnected devices and data-intensive applications in urban environments has accentuated the critical need for efficient, adaptiv...
Assessing the Impact of Mathematical Models on Urban Traffic Flow Optimization...
Urban traffic congestion remains a persistent challenge for city planners and transportation authorities worldwide, leading to increased travel times, environme...
Design and Implementation of a Numerical Solver for Nonlinear Differential Equations...
The efficient and accurate numerical solution of nonlinear differential equations remains a critical challenge in applied mathematics, with broad implications a...
