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Designing a Battlefield Fire Support System Using Adaptive Neuro-Fuzzy Inference System Based Model

机译:基于模型的自适应神经模糊推理系统设计战场火力保障系统

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Fire support of the maneuver operation is a continuous process. It begins with the receiving the task by the maneuver commander and continues until the mission is completed. Yet it is a key issue in combat in the way gain success. Therefore, a real-time mannered solution to fire support problem is a vital component of tactical warfare to the sequence that auxiliary forces or logistic support arrives at the theatre. A new method for deciding on combat fire support is proposed using adaptive neuro-fuzzy inference system (ANFIS) in this paper. This study addresses the design of an ANFIS as an efficient tool for real-time decision-making in order to produce the best fire support plan in battlefield. Initially, criteria that are determined for the problem are formed by applying ANFIS method. Then, the ANFIS structure is built up by using the data related to selected criteria. The proposed method is illustrated by a sample fire support planning in combat. Results showed us that ANFIS is valid especially for small unit fire support planning and is useful to decrease the decision time in battlefield.
机译:机动操作的火力支援是一个连续的过程。它从机动指挥官接收任务开始,一直持续到任务完成为止。然而,这是获得成功的战斗中的关键问题。因此,对于辅助部队或后勤支援到达剧院的顺序而言,实时,有针对性地解决火力支援问题的解决方案是战术战争的重要组成部分。提出了一种利用自适应神经模糊推理系统(ANFIS)确定作战火力支援的新方法。这项研究致力于将ANFIS设计为一种实时决策的有效工具,以便在战场上制定最佳的火力支援计划。最初,通过使用ANFIS方法来形成确定问题的标准。然后,通过使用与选定标准相关的数据来构建ANFIS结构。作战中的示例火力支援计划说明了所提出的方法。结果表明,ANFIS特别适用于小型单位的火力支援计划,并有助于减少战场上的决策时间。

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