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Wireless local networks (WLANs) that contain a high-density of access points (APs) are being deployed rapidly all around the world, where large numbers of idle APs exist. In this paper, a optimization for the deployment and transmitting power of AP is proposed in order to save energy and reduce frequency interference. It includes green AP clustering where Fuzzy K-mean algorithm is used, AP's second...
As a very popular positioning system, WLAN positioning attracts widely researches and investigations throughout the world. It implements the fingerprint technique to realize indoor navigation. The fingerprinting technique which employs the KNN algorithm has to make use of RSS (Received Signal Strength) from the Access Points (APs) without any classification. However, not all of the APs provide the...
This paper expands the standard pronunciation space (SPS) to include pronunciation errors for automatic pronunciation error detection (APED), uses HMMs to represent the different distributions of pronunciation errors, proposes an adaptive unsupervised clustering of pronunciation errors based on the similarity measures between two HMMs, and then refines more detailed acoustic models for APED within...
This paper proposes an ANFIS indoor positioning system based on improved genetic algorithm (GA). In the offline phase, fuzzy rules are abstracted by means of subtractive clustering algorithm with training data, generating the structure of each ANFIS positioning subsystem in X and Y directions. Then each positioning subsystem is trained with improved-GA. In this training algorithm, BP algorithm acts...
As a fingerprint match method, k-nearest neighbors (KNN) has been widely applied for indoor location in Wireless Local Area Networks (WLAN), but its performance is sensitive to number of neighbors k and positions of reference points (RPs). So fuzzy c-means (FCM) clustering algorithm is applied to improve KNN, which is the KNN-FCM hybrid algorithm presented in this paper. In the proposed algorithm,...
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