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GIS-based design and analysis of preventive health management system for vehicles using ANFIS

机译:基于GIS的ANFIS车辆预防性健康管理系统设计与分析。

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The health of a vehicle gets affected by different parameters having uncertainties such as past running hours, vehicle operating condition, the consumption rate of fuel, etc. which in turn influence the health of a transportation system as a whole. In this work, a geographical information system (GlS)-based adaptive neuro fuzzy inference system (ANFIS) has been utilised for the advanced prognostic and health management strategy of the vehicle to assess the condition of the vehicle from a precautionary preservation perspective, so as to enhance the ability of credentials of proactive malfunction circumstances. The case study corroborates the effectiveness of the proposed ANFIS technique. It provides the proposal of safeguarding the operation for pragmatic applications with consideration of all uncertainties, the domino effect on the health of the transportation system.
机译:车辆的健康会受到不同参数的影响,这些参数具有不确定性,例如过去的行驶时间,车辆的运行状况,燃料的消耗率等,这些参数反过来会影响整个运输系统的健康。在这项工作中,基于地理信息系统(GlS)的自适应神经模糊推理系统(ANFIS)已用于车辆的高级预后和健康管理策略,以从预防性保护的角度评估车辆的状况,从而增强主动发生故障情况的凭证能力。案例研究证实了所提出的ANFIS技术的有效性。它提出了在考虑所有不确定性以及对运输系统健康的多米诺骨牌效应的情况下,保护务实应用程序运行的建议。

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