In order to solve the defect in the spatial outlier mining algorithm that the spatial objects may be affected by their surrounding abnormal neighbors, a Based K-Nearest Neighbor (BKNN) algorithm was proposed based on the working principle of KNN Graph, which could effectively identify the spatial outliers by using cutting edge strategies. The core idea of BKNN is to calculate the dissimilarity ...

Maintenance for wind turbines has been transformed using supervised machine learning techniques. This method of automatic and autonomous can identify, monitor, detect electrical mechanical components predict, detect, anticipate their degeneration. Using a classifier frequency analysis, we simulate two failure states caused by bearing vibrations. Implementing KNN facilitates efficient monitoring...

The standard kNN algorithm suffers from two major drawbacks: sensitivity to the parameter value k, i.e., the number of neighbors, and the use of k as a global constant that is independent of the particular region in which the example to be classified falls. Methods using weighted voting schemes only partly alleviate these problems, since they still involve choosing a fixed k. In this paper, a n...

This paper presents a new algorithm for human action recognition in videos. This algorithm is based on a combination of two different feature types extracted from Aligned Motion Images (AMIs). The AMI is a method for capturing the motion of all frames in a human action video in one image. The first feature is a contourbased type and is employed to grasp boundary details of the AMI. It relies on...

Support vector machine (SVM) is one of the most powerful supervised learning algorithms in gene expression analysis. The samples intermixed in another class or in the overlapped boundary region may cause the decision boundary too complex and may be harmful to improve the precise of SVM. In the present paper, hybridized k-nearest neighbor (KNN) classifiers and SVM (HKNNSVM) is proposed to deal w...

Activity recognition is one of the most important technology behind many applications such as medical research, human survey system and it is an active research topic in health care and smart homes. Smart phones are equipped with various built-in sensing platforms like accelerometer, gyroscope, GPS, compass sensor and barometer, we can design a system to capture the state of the user. Activity ...

The k-Nearest Neighbor (kNN) classification approach is conceptually simple – yet widely applied since it often performs well in practical applications. However, using a global constant k does not always provide an optimal solution, e. g., for datasets with an irregular density distribution of data points. This paper proposes an adaptive kNN classifier where k is chosen dynamically for each ins...

The k-nearest neighbour (kNN) rule, which naturally handles the possible non-linearity of data, is introduced to solve the fault detection problem of gas sensor arrays. In traditional fault detection methods based on the kNN rule, the detection process of each new test sample involves all samples in the entire training sample set. Therefore, these methods can be computation intensive in monitor...