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Antigen-antibody binding mechanism-oriented generative behavior rule base construction method

A technology of antigen antibody and construction method, which is applied in the fields of instruments, computing, and electrical digital data processing, etc., can solve the problems of low precision of intelligent modeling, achieve the effect of improving behavioral intelligence, enriching knowledge modeling, and improving expression efficiency

Inactive Publication Date: 2019-12-27
SHAANXI NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem of low intelligent modeling accuracy caused by the existing behavior rule library construction method in the prior art, the present invention proposes a generative behavior rule library construction method oriented to the antigen-antibody binding mechanism

Method used

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  • Antigen-antibody binding mechanism-oriented generative behavior rule base construction method
  • Antigen-antibody binding mechanism-oriented generative behavior rule base construction method
  • Antigen-antibody binding mechanism-oriented generative behavior rule base construction method

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Embodiment 1

[0038] A method for constructing a generative behavioral rule library oriented to the binding mechanism of antigens and antibodies. Antigens represent marine environment, underwater static and moving targets, and combat mission characteristics; antibody lymphocytes represent UUV;

[0039] Step 1: If image 3 As shown, according to the immune recognition mechanism of the biological immune system and the knowledge expression principle of the generation rule, the basic form of the autonomous behavior generation rule IF-THEN is established, where IF represents the condition part, and THEN represents the conclusion part;

[0040] Step 2: UUV encapsulates complete fine-grained knowledge base information, that is, determines the environment, tasks, goals, status and other information of the IF condition part, and the IF condition part adopts the design of object-oriented modeling;

[0041] Step 3: Determine the conclusion part of THEN, including behavioral strategies and actions incl...

Embodiment 2

[0059] Taking UUV underwater obstacle avoidance as an example, construct a generative behavior rule library oriented to the mechanism of antigen-antibody binding. In the underwater space of 10000m×10000m, the sound field is stable, the ocean current is 0.8m / s, and the healthy UUV is abstracted as two 3D moving particle, with an initial heading of 45°, a speed of 2.5m / s, and a detection range of 1000m, from the initial position (0,0) to autonomously avoid underwater obstacles and move to the target position (10000m, 10000m), where the underwater static obstacle area is : Obstacle #1: Radius(1150m), Position(3000m, 3150m), Obstacle #2: Radius(800m), Position(8000m, 7700m), Obstacle #3: Radius(800m), Position(1800m, 7500m), Obstacle #4: radius (1300m), location (5200m, 6600m), obstacle #5: radius (800m), location (4200m, 4500m), obstacle #6: radius (800m), location (8500m, 2500m).

[0060] Step 1: Inspired by the immune recognition mechanism, establish the basic form of autonomou...

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Abstract

The invention belongs to the field of underwater unmanned system modeling and simulation, and particularly relates to an antigen-antibody binding mechanism-oriented generative behavior rule base construction method. The method comprises: establishing a behavior rule form of an IF-THEN structure by analyzing an immune recognition process of a biological immune system and referring to a bonding relationship between antibodies and knowledge expression of a production rule; designing environment, mission, target and state object classes convenient for inheritance and expansion by adopting an object-oriented modeling idea, constructing behavior strategies and actions including motion control and firepower control information, and designing an autonomous behavior rule base on the basis of the behavior strategies and actions; and designing a behavior rule matching algorithm for antibody and antigen affinity calculation, so that expression and reasoning of autonomous behavior rules of the UUVunder combat situation conditions are realized, and the intelligent modeling precision of the UUV is greatly improved.

Description

technical field [0001] The invention belongs to the field of underwater unmanned system modeling and simulation, and in particular relates to a method for constructing a generative behavior rule library oriented to an antigen-antibody combination mechanism. Background technique [0002] Military UUV, as a new type of underwater weapon after torpedoes and mines, is an underwater unmanned system that integrates environmental perception, dynamic planning, behavior control, and energy adaptation. Submarine defense and network detection are responsible for more important underwater combat tasks. In order to adapt to the profound changes in weapons and equipment, war forms, and battlefield environments caused by the wave of naval information technology, UUVs continue to develop toward long-range, large-depth, and especially UUV intelligence. my country's deep-sea strategy is constantly being strengthened. [0003] The intelligence of the underwater unmanned system is reflected in...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06N5/02
CPCG06N5/025
Inventor 梁洪涛强宁
Owner SHAANXI NORMAL UNIV
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