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Radio-frequency identification (RFID) readers are powered RF devices that communicate with tags (whether mobile or fixed) and read necessary information to be processed. A mobile RFID tag is detected by an RFID antenna. In a mobile RFID where the RFID tag is attached to a mobile object such as a vehicle, a human, or an animal, information is more difficult to detect than in the case where the tag is attached to a stationary object. Currently, deployment engineers and researchers use trial-and-error approaches to decide on the best conditions of the tag detection influence factors which affect tag detectability (detection rate). As expected, these approaches are time consuming. Even though mobile RFID systems have become widely used in industry and tag detection problems are crucial at deployment, very few researches on them have been conducted so far. Thus, a quick and simple method for finding tag detectability is needed to improve the traditional time consuming trial-and-error method. In this paper, we propose a unique approach ldquothe intelligent prediction method of tag detection rate using support vector machine (SVM).rdquo The intelligent method predicts the mobile RFID tag detectability instead of the trial-and-error experimental procedures. The simulation results of the proposed method are very comparable to the trial-and-error experimental approach. The proposed intelligent method gives a very high accuracy of mobile RFID tag detectability prediction and proves to be superior to the current method in time as well cost savings. The predicted tag detectability results can be used for analyzing mobile RFID tag detection influence factors and their conditions.