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Allocation of Forces, Fires, and Effects Using Genetic Algorithms [Mīkstie vāki]

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  • Formāts: Paperback / softback, 74 pages, height x width x depth: 281x220x6 mm, weight: 240 g, col. Illustrations
  • Izdošanas datums: 23-Jun-2008
  • Izdevniecība: RAND
  • ISBN-10: 0833044796
  • ISBN-13: 9780833044792
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  • Mīkstie vāki
  • Cena: 33,90 €
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Allocation of Forces, Fires, and Effects Using Genetic AlgorithmsPalielināt
  • Formāts: Paperback / softback, 74 pages, height x width x depth: 281x220x6 mm, weight: 240 g, col. Illustrations
  • Izdošanas datums: 23-Jun-2008
  • Izdevniecība: RAND
  • ISBN-10: 0833044796
  • ISBN-13: 9780833044792
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9780833044792.html
Keywords:
Decisionmaking within the Future Battle Command structure will demand an increasing ability to comprehend and structure information on the battlefield. Decision aids must be modified accordingly. Using information about friendly and enemy forces and the terrain, a RAND-developed model that incorporates a genetic algorithm (1) determines preferred Blue routes around Red forces and (2) allocates forces to these routes.
Preface iii
Figures
vii
Tables
ix
Summary xi
Abbreviations xv
Introduction
1(8)
Algorithms Considered
2(4)
Neural Networks
3(1)
Bayesian Belief Networks
3(1)
Fuzzy Logic
4(1)
A* and Other Greedy Algorithms
5(1)
Genetic Algorithms
5(1)
Model Overview
6(3)
Modeling Enemy Capability and Effects
9(8)
Expected Effect
10(1)
The Effect Function
11(2)
Explicit Expression for Expected Effect
13(1)
Relating Expected Effect to Route Fitness
14(1)
Summary
15(2)
Generating Blue AoAs: The Phase One Genetic Algorithm
17(12)
Initialization
17(1)
Mating and Niching
17(4)
The Need for Niching
18(1)
The Niching Algorithm
19(2)
The Mating Procedure
21(1)
Mutation
21(1)
Red Behavior Model
22(3)
Red Intent
23(1)
Red Intelligence and Adaptability
24(1)
Determining Route Fitness
25(2)
Summary
27(2)
Generating Blue Allocations: The Phase Two Genetic Algorithm
29(8)
The Niching Algorithm
30(1)
The Mating and Mutation Procedures
31(1)
Defining a Field of Red Allocations
32(1)
Fitness of a Blue Allocation
33(1)
Summary
34(3)
Modeling Terrain
37(6)
Impassibility
37(1)
Inhospitableness
38(1)
Shadowing
39(1)
A Terrain Example
39(1)
Summary
40(3)
Proof-of-Principle Examples
43(16)
A Simple Scenario
44(6)
The Case of High Uncertainty
45(1)
The Case of Moderate Uncertainty
46(1)
The Case of Low Uncertainty
47(1)
Final AoAs
48(1)
Fitness Evolution
49(1)
Terrain Effect on AoA Selection
50(2)
Effect of Red Behavior Model on AoA Selection
52(4)
Effect of Red's Adaptability
52(3)
Effect of Red's Intelligence
55(1)
Red Activity Knowledge Affects Blue Allocations
56(1)
Summary
57(2)
Conclusions and Future Extensions
59(2)
References 61