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Advanced Mathematical Techniques in Science and Engineering [Kõva köide]

Edited by (Graphic Era University, Uttarakhand), Edited by
  • Formaat: Hardback, 248 pages, kõrgus x laius: 234x156 mm, kaal: 498 g
  • Ilmumisaeg: 31-Jan-2018
  • Kirjastus: River Publishers
  • ISBN-10: 8793609345
  • ISBN-13: 9788793609341
Teised raamatud teemal:
Advanced Mathematical Techniques in Science and EngineeringSuurem pilt
  • Formaat: Hardback, 248 pages, kõrgus x laius: 234x156 mm, kaal: 498 g
  • Ilmumisaeg: 31-Jan-2018
  • Kirjastus: River Publishers
  • ISBN-10: 8793609345
  • ISBN-13: 9788793609341
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9788793609341.html
In recent years, mathematical techniques applied to novel disciplines within science and engineering have experienced extraordinary growth. Advanced Mathematical Techniques in Science and Engineering focuses 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.
Preface xi
Acknowledgements xiii
List of Contributors xv
List of Figures xvii
List of Tables xxiii
List of Abbreviations xxv
1 Analysis of Consensus-Building Time in Social Groups Based on the Results of Statistical Modeling 1(32)
Aronov Iosif Zinovievich
Maksimova Olga Vladimirovna
Grigoryev Vadim Iosifovich
1.1 Introduction and Purpose of the Study
2(1)
1.2 Description of the Model for Consensus Based on Regular Markov Chains
3(2)
1.3 Specific Cases in the Model of Attaining Consensus in the Work of TC
5(1)
1.3.1 Domination
5(1)
1.3.2 Presence of Several Leaders
5(1)
1.3.3 Global Domination
6(1)
1.3.4 Responsibility Shift
6(1)
1.3.5 Coalitions
6(1)
1.4 Analysis of the General Case in the Consensus Model
6(4)
1.5 Management of the TCs by the National Standardization Body
10(2)
1.6 The Quality of Consensus
12(1)
1.7 Consensus-Building Model Description Based on Cellular Automata Methodology
13(4)
1.8 Study of Consensus-Building Model Based on Cellular Automata Methodology
17(11)
1.9 Conclusions and Results Interpretation
28(2)
References
30(3)
2 Classification and Modeling of Intersystem Accidents in Critical Infrastructure Systems 33(24)
Valery V. Lesnykh
Vladislav S. Petrov
Tatiana B. Timofeeva
2.1 Introduction
33(4)
2.2 Examples of Intersystem Failures
37(2)
2.3 Classification of Intersystem Failures
39(3)
2.4 Simulation of Intersystem Failures
42(7)
2.4.1 Gas Transmission Network Model
43(3)
2.4.2 Electric Network Model
46(1)
2.4.3 Interaction Model
47(2)
2.5 Results of Calculations
49(2)
2.6 Perturbance Propagation Functions
51(2)
2.7 Conclusion
53(1)
References
54(3)
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 57(44)
Yuriy V. Kostyuchenko
Maxim Yuschenko
Ivan Kopachevsky
3.1 Introduction
57(5)
3.1.1 Case Study: The Conflict
59(3)
3.2 Methodological Notes: Approach to Data Analysis
62(6)
3.2.1 Big Data Classification Approach
64(2)
3.2.2 Multisource Data Regularization and Optimization Approach
66(2)
3.3 Population Dynamics Assessment in the Crisis Area Using Multisource Data
68(6)
3.3.1 Population Assessment in Rural Areas
69(1)
3.3.2 Population Assessment in Urban Areas
70(1)
3.3.3 Satellite Observations and Data Integration Approach
71(3)
3.4 Assessment of the Economic Dynamics in the Crisis Area Using Multisource Data
74(7)
3.4.1 Analysis of Land-Use Structure Change: Markov's Chains Modeling of Satellite Data
74(4)
3.4.2 Satellite Data for Analysis of Land-Use Efficiency and Crop Structure Dynamics
78(1)
3.4.3 Data Integration Algorithm and Satellite Based Approach to Economic Activity Variations
79(2)
3.5 Assessment of Number and Dynamics of Illegal Armed Groups Using Big Data
81(3)
3.6 Assessment of Combatant and Non-Combatant Losses Using Multisource Data
84(3)
3.7 On the Model of Population Dynamics under the Conflict
87(5)
3.8 Concluding Remarks
92(3)
References
95(6)
4 Modeling and Performance Evaluation of Computational DoS Attack on an Access Point in Wireless LANs 101(20)
Rajeev Singh
Teek Parval Sharma
4.1 Introduction
102(2)
4.2 Review of Key Hiding Communication (KHC) Scheme
104(1)
4.3 Network Model
105(3)
4.3.1 Simulation Topology
106(1)
4.3.2 Simulation Parameters
107(1)
4.3.3 Performance Evaluation Metrics
108(1)
4.4 Results and Discussion
108(8)
4.5 Conclusion
116(1)
References
117(4)
5 Development of Computation Algorithm and Ranking Methods for Decision-Making under Uncertainty 121(34)
Alexander V. Bochkov
Nikolay N. Zhigirev
5.1 Trough-Ranking Method for a Regulate Lists Objects of Different Types by Partial Expert Comparisons
123(18)
5.1.1 Literature Review
123(1)
5.1.2 Algorithm Description
124(7)
5.1.3 Case Study
131(10)
5.2 The Analytic Hierarchy Process Modification for Decision Making under Uncertainty
141(10)
5.2.1 Introduction
141(1)
5.2.2 Literature Review
142(1)
5.2.3 Problem Statement
143(1)
5.2.4 Methodology Description
144(3)
5.2.5 Case Study
147(4)
5.3 Conclusion
151(1)
References
152(3)
6 Understanding Time Delay Based Modeling and Diffusion of Technological Products 155(10)
Mohini Agarwal
Adarsh Anand
Deepti Aggrawal
Rubina Mittal
6.1 Introduction
155(2)
6.2 Research Methodology
157(3)
6.2.1 Notations
157(3)
6.3 Research Results and Findings
160(1)
6.4 Discussion
161(1)
6.5 Conclusion
162(1)
References
162(3)
7 Role of Soft Computing in Science and Engineering 165(20)
Preeti Malik
Lata Nautiyal
Mangey Ram
7.1 Introduction
165(3)
7.1.1 Why Soft Computing Approach?
167(1)
7.2 Soft Computing Techniques
168(9)
7.2.1 Machine Learning
169(3)
7.2.1.1 Notation of dataset
170(1)
7.2.1.2 Training data and test data
170(1)
7.2.1.3 Relationships with other disciplines
170(1)
7.2.1.4 Basic concepts and ideals of machine learning
171(1)
7.2.1.5 The categorization of machine learning algorithms
171(1)
7.2.2 Fuzzy Logic
172(1)
7.2.3 Evolutionary Algorithms
172(1)
7.2.3.1 Implementation
173(1)
7.2.3.2 Types
173(1)
7.2.4 Genetic Algorithms
173(2)
7.2.4.1 Initialization
174(1)
7.2.4.2 Selection
174(1)
7.2.4.3 Genetic operators
174(1)
7.2.4.4 Termination
175(1)
7.2.5 Bayesian Network
175(1)
7.2.6 Neural Network
175(1)
7.2.7 Particle Swarm Optimization
176(1)
7.3 Applications
177(3)
7.4 Conclusion
180(1)
References
180(5)
8 Complex System Reliability Analysis and Optimization 185(16)
Anuj Kumar
Sangeeta Pant
Mangey Ram
8.1 Introduction
185(4)
8.1.1 Reliability Measuring Parameters
186(1)
8.1.2 Stochastic Processes
187(1)
8.1.3 Copula Method
187(1)
8.1.4 Reliability Optimization
188(1)
8.2 Review of Literature
189(1)
8.3 Material and Methods
190(3)
8.3.1 Supplementary Variable Technique
190(1)
8.3.2 Birth-Death Processes
191(1)
8.3.3 Multi-objective Particle Swarm Optimization
192(1)
8.3.4 Mathematical Model and Reliability Block Diagram
193(9)
8.3.4.1 Complex bridge system
193(1)
8.4 Results and Discussion
193(2)
8.5 Conclusion and Summary
195(1)
References
196(5)
9 Tree Growth Models in Forest Ecosystem Modeling-A Tool for Development of Tree Ring Width Chronology and Climate Reconstruction 201(18)
Rajesh Joshi
Rupesh Dhyani
9.1 Introduction
202(5)
9.1.1 Notion of Ecosystem Modeling
202(5)
9.1.1.1 Growth and yield models
204(1)
9.1.1.2 Succession models
205(1)
9.1.1.3 Biogeochemical-mechanistic models
206(1)
9.1.1.4 Hybrid models
206(1)
9.2 Tree Growth Models
207(1)
9.2.1 General Linear Aggregate Model
207(1)
9.2.2 Growth Curve for Detrending Tree Growth Time Series
208(1)
9.3 Deterministic Curves
208(2)
9.3.1 Negative Exponential Curve
208(1)
9.3.2 Linear Regression Curve
209(1)
9.3.3 Hugershoff Growth Curve
209(1)
9.4 Stochastic Curves
210(1)
9.4.1 The Smoothing Spline Curve
210(1)
9.4.2 Friedman's Super Smoother
210(1)
9.5 Empirical Curves
211(1)
9.5.1 Regional Curve Standardization Method
211(1)
9.6 Application of Tree Ring Growth Models-An Example from A Case Study
212(2)
9.7 Conclusion
214(1)
References
215(4)
Index 219(2)
About the Editors 221
Mangey Ram, João Paulo Davim