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Publish a Book Chapter in "Advances in Mathematical and Statistical Modelling (Volume - 2)"


Call for Book Chapters: Submissions Now Open

978-3-96492-348-6
Invited Topics

  1. Nonlinear Optimization Algorithms for Model Calibration
  2. Optimal Control in Engineering and Economics
  3. Multi‑Objective Optimization in Applied Models
  4. Global Optimization in High‑Dimensional Spaces
  5. Variational Methods in Modelling and Simulation
  6. Constraint Handling in Complex Optimization Problems
  7. Heuristic and Meta‑Heuristic Optimization Techniques
  8. Optimization under Uncertainty
  9. Real‑Time Control in Dynamic Systems
  10. Game‑Theoretic Approaches to Optimal Decision Models
  11. Generalized Linear Models in Applied Research
  12. Bayesian Statistical Modelling and Computation
  13. Mixture Models for Heterogeneous Data
  14. Random Effects and Mixed Model Frameworks
  15. Hidden Markov Models in Time Series
  16. Functional Data Analysis for Complex Signals
  17. Spatial Statistics and Geostatistical Modelling
  18. Survival Analysis and Reliability Modelling
  19. Causal Inference in Statistical Models
  20. Advanced Regression Techniques and Variable Selection
  21. Stochastic Differential Equations in Finance
  22. Time Series Forecasting with ARIMA and Beyond
  23. Long‑Memory Processes and Fractional Brownian Models
  24. Markov Chain Models in Epidemiological Modelling
  25. Point Processes for Event Modelling
  26. Random Walk Models and Anomalous Diffusion
  27. State‑Space Modelling for Dynamic Systems
  28. Bayesian Time Series Models
  29. Change‑Point Detection in Stochastic Processes
  30. Stochastic Simulation and Monte Carlo Methods
  31. Efficient Algorithms for Large‑Scale Modelling
  32. Parallel Computing in Mathematical Simulations
  33. Finite Element Methods for Physical Modelling
  34. Grid and Mesh Generation Strategies for PDE Solvers
  35. Machine Learning Assisted Numerical Modelling
  36. Model Reduction Techniques for Complex Systems
  37. GPU‑Accelerated Modelling Frameworks
  38. Data Assimilation Methods for Dynamic Models
  39. Uncertainty Quantification in Numerical Solutions
  40. Algorithmic Differentiation for Sensitivity Studies
  41. Integrating Statistical Models with Machine Learning
  42. Predictive Modelling for Big Data Analytics
  43. Data‑Centric Modelling for Engineering Systems
  44. Hybrid Physics–Data Models for Climate Systems
  45. Surrogate Models for Expensive Simulations
  46. Deep Learning Models for Time Series Prediction
  47. Feature Extraction for High‑Dimensional Data
  48. Data Fusion Techniques in Multi‑Domain Modelling
  49. Model Calibration Using Data Streams
  50. Unsupervised Learning in Statistical Model Discovery
  51. Modelling Infectious Disease Dynamics with Compartmental Models
  52. Ecological Systems and Population Interactions
  53. Cardiovascular Modelling in Biomedical Engineering
  54. Neural Network Models in Cognitive Neuroscience
  55. Bio‑chemical Reaction Network Modelling
  56. Environmental Change and Ecosystem Response Models
  57. Soil and Water Resource Modelling
  58. Climate System Modelling and Predictive Tools
  59. Modelling Genetic Regulatory Networks
  60. Pharmacokinetic and Pharmacodynamic Models
  61. Structural Reliability and Safety Modelling
  62. Heat Transfer and Fluid Dynamics Models
  63. Traffic Flow Modelling and Transportation Systems
  64. Wireless Network Modelling and Optimization
  65. Energy Systems and Smart Grid Models
  66. Signal Processing Models for Communication Systems
  67. Control System Design Using Mathematical Models
  68. Robotics and Motion Planning Models
  69. Industrial Process Modelling and Quality Control
  70. Computational Electromagnetics and Wave Modelling
  71. Modelling Social Systems and Human Behavior
  72. Economic Modelling under Uncertainty and Risk
  73. Financial Risk Modelling with Statistical Techniques
  74. Network Science in Social & Technological Systems
  75. Ethical Considerations in Data Modelling Practice
  76. Policy Modelling for Sustainable Development
  77. Educational Models for Learning Analytics
  78. Cyber‑Physical System Modelling and Resilience
  79. Digital Twins and Real‑World Model Integration
  80. Future Directions in Mathematical and Statistical Modelling

 Cover page of Advances in Mathematical and Statistical Modelling, edited book on mathematics
Chief Editor

Prof. Himanshu Pandey, editor of edited book on mathematics
Prof. Himanshu Pandey
Professor, Department of Mathematics and Statistics, D.D.U. Gorakhpur University, Gorakhpur, Uttar Pradesh, India

Book Scope

  • Deterministic Model
  • Probabilistic Model
  • Bayesian Analysis
  • Fuzzy Model
  • Decision Making
  • Sampling Theory
  • Multivariate Model
  • Net Work Model
  • Inventory Model
  • Queueing Modal
  • Reliability
  • Differential Geometry
  • Tensor
  • Dynamics
  • Summability
  • Fourier
  • Population Model
  • Medical Science
  • Social Sciences
  • Mathematical modelling techniques
  • Statistical analysis methods
  • Predictive modelling
  • Stochastic models
  • Deterministic models
  • Regression analysis
  • Time series modelling
  • Multivariate statistics
  • Bayesian modelling
  • Optimization methods
  • Computational mathematics


Author Guidelines

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Submit Chapter

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OR

Send your chapter on weserbooks@gmail.com


Deadline

28nd Feb 2026