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ANFIS-based Self-learning Expert System for Weapon Target Assignment Problem

Published: 22 October 2021 Publication History

Abstract

In this paper, we propose an efficient algorithm to solve the weapon target assignment (WTA) problem combining the advantages of rule-based with that of traditional optimization methods. The main ideal of the proposed algorithm is building an adaptive neuro-fuzzy inference system (ANFIS) to obtain an original assignment scheme, and then the original scheme is used to initialize particles in discrete particle swarm optimization (DPSO). With the original assignment scheme provided by ANFIS, it can solve the problem of converging to local optimum with random initialization in DPSO efficiently. At last, a numerical simulation is proposed to illustrate the efficiency of the method in this paper.

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              cover image ACM Other conferences
              CCRIS '21: Proceedings of the 2021 2nd International Conference on Control, Robotics and Intelligent System
              August 2021
              278 pages
              ISBN:9781450390453
              DOI:10.1145/3483845
              Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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              Published: 22 October 2021

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              Author Tags

              1. Self-learning
              2. Weapon target assignment
              3. discrete particle swarm optimization
              4. neuro-fuzzy inference system

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