Title Advanced Mathematical Techniques in Science and Engineering
Subtitle (River Publishers Series in Management Sciences and Engineering)
Author Mangey Ram, João Paulo Davim
ISBN 9788793609341
List price USD 132.00
Price outside India Available on Request
Original price
Binding Hardbound
No of pages 200
Book size 152 X 235 mm
Publishing year 2018
Original publisher River Publishers (Eurospan Group)
Published in India by .
Exclusive distributors Viva Books Private Limited
Sales territory India, Sri Lanka, Bangladesh, Pakistan, Nepal, .
Status New Arrival
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Description:

In recent years, mathematical techniques applied to novel disciplines within the science and engineering have experienced extraordinary growth. Advanced Mathematical Techniques in Science and Engineering focusses on a detailed range of mathematics applied within various fields of science and engineering for different tasks. Topics of focus include:

  • Analysis of Consensus-Building Time in Social Groups
  • Modeling of intersystem accidents in critical infrastructure systems
  • Stochastic approaches to analysis and modeling of multi-sources and big data
  • Performance evaluation of computational DoS attack on access point in Wireless LANs
  • Ranking methods for decision-making under uncertainty
  • Understanding time delay based Modeling & Diffusion of technological products
  • Role of soft computing in science and engineering
  • Complex system reliability analysis and optimization
  • Tree growth models in forest ecosystems modelling

This research book can be used as a reference for students in a final year undergraduate engineering course, such as mechanical, mechatronics, industrial, computer science, information technology, etc. Furthermore, the book can serve as a valuable reference for academics, engineers and researchers in these and related subject areas.


Contents:

Preface

Acknowledgements

List of Contributors

List of Figures

List of Tables

List of Abbreviations

Chapter 1. Analysis of Consensus-Building Time in Social Groups Based on the Results of Statistical Modeling (Aronov losif Zinovievich, Maksimova Olga Vladimirovna and Grigoryev Vadim losifovich) • Introduction and Purpose of the Study • Description of the Model for Consensus Based on Regular Markov Chains • Specific Cases in the Model of Attaining Consensus in the Work of TC • Domination • Presence of Several Leaders • Global Domination • Responsibility Shift • Coalitions • Analysis of the General Case in the Consensus Model • Management of the TCs by the National Standardization Body • The Quality of Consensus • Consensus-Building Model Description Based on Cellular Automata Methodology • Study of Consensus-Building Model Based on Cellular Automata Methodology • Conclusions and Results Interpretation • References

Chapter 2. Classification and Modeling of Intersystem Accidents in Critical Infrastructure Systems (Valery V. Lesnykh, Vladislav S. Petrov and Tatiana B. Timofeeva) • Introduction • Examples of Intersystem Failures • Classification of Intersystem Failures • Simulation of Intersystem Failures • Gas Transmission Network Model • Electric Network Model • Interaction Model • Results of Calculations • Perturbance Propagation Functions • Conclusion • References

Chapter 3. Stochastic Approaches to Analysis and Modeling of Multi-Sources and Big Data in Tasks of Homeland Security: Socio-Economic and Socio-Ecological Crisis Control Tools (Yuriy V. Kostyuchenko, Maxim Yuschenko and Ivan Kopachevsky) • Introduction • Case Study: The Conflict • Methodological Notes: Approach to Data Analysis • Big Data Classification Approach • Multisource Data Regularization and Optimization Approach • Population Dynamics Assessment in the Crisis Area Using Multisource Data • Population Assessment in Rural Areas • Population Assessment in Urban Areas • Satellite Observations and Data Integration Approach • Assessment of the Economic Dynamics in the Crisis Area Using Multisource Data • Analysis of Land-Use Structure Change: Markov’s Chains Modeling of Satellite Data • Satellite Data for Analysis of Land-Use Efficiency and Crop Structure Dynamics • Data Integration Algorithm and Satellite Based Approach to Economic Activity Variations • Assessment of Number and Dynamics of Illegal Armed Groups Using Big Data • Assessment of Combatant and Non-Combatant Losses Using Multisource Data • On the Model of Population Dynamics under the Conflict • Concluding Remarks • References

Chapter 4.• Modeling and Performance Evaluation of Computational DoS Attack on an Access Point in Wireless LANs (Rajeev Singh and Teek Parval Sharma) • Introduction • Review of Key Hiding Communication (KHC) Scheme • Network Model • Simulation Topology • Simulation Parameters • Performance Evaluation Metrics • Results and Discussion • Conclusion • References

Chapter 5. Development of Computation Algorithm and Ranking Methods for Decision-Making under Uncertainty (Alexander V. Bochkov and Nikolay N. Zhigirev) • Trough-Ranking Method for a Regulate Lists Objects of Different Types by Partial Expert Comparisons • Literature Review • Algorithm Description • Case Study • The Analytic Hierarchy Process Modification for Decision Making under Uncertainty • Introduction • Literature Review • Problem Statement • Methodology Description • Case Study • Conclusion • References

Chapter 6. Understanding Time Delay Based Modeling and Diffusion of Technological Products (Mohini Agarwal, Adarsh Anand, Deepti Aggrawal and Rubina Mittal) • Introduction • Research Methodology • Notations • Research Results and Findings • Discussion • Conclusion • References

Chapter 7. Role of Soft Computing in Science and Engineering (Preeti, Lata Nautiyal and Mangey Rain) • Introduction • Why Soft Computing Approach? • Soft Computing Techniques • Machine Learning • Notation of dataset • Training data and test data • Relationships with other disciplines • Basic concepts and ideals of machine learning • The categorization of machine learning algorithms • Fuzzy Logic • Evolutionary Algorithms • Implementation • Types • Genetic Algorithms • Initialization • Selection • Genetic operators • Termination • Bayesian Network • Neural Network • Particle Swarm Optimization • Applications • Conclusion • References

Chapter 8. Complex System Reliability Analysis and Optimization (Anuj Kumar, Sangeeta Pant and Mangey Ram) • Introduction • Reliability Measuring Parameters • Stochastic Processes • Copula Method • Reliability Optimization • Review of Literature • Material and Methods • Supplementary Variable Technique • Birth—Death Processes • Multi-objective Particle Swarm Optimization • Mathematical Model and Reliability Block Diagram • Complex bridge system • Results and Discussion • Conclusion and Summary • References

Chapter 9. Tree Growth Models in Forest Ecosystem Modeling — A Tool for Development of Tree Ring Width Chronology and Climate Reconstruction (Rajesh Joshi and Rupesh Dhyani) • Introduction • Notion of Ecosystem Modeling • Growth and yield models • Succession models • Biogeochemical-mechanistic models • Hybrid models • Tree Growth Models • General Linear Aggregate Model • Growth Curve for Detrending Tree Growth Time Series • Deterministic Curves • Negative Exponential Curve • Linear Regression Curve • Hugershoff Growth Curve • Stochastic Curves • The Smoothing Spline Curve • Friedman’s Super Smoother • Empirical Curves • Regional Curve Standardization Method • Application of Tree Ring Growth Models — An Example from A Case Study • Conclusion • References

Index

About the Editors


About the Editors:

Mangey Ram, Graphic Era University, India.

João Paulo Davim, University of Aveiro, Portugal.


Target Audience:

This research book can be used as a reference for students in a final year undergraduate engineering course, such as mechanical, mechatronics, industrial, computer science, information technology, etc.

 

 
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