In this research paper, the proposed method introduced an optimized cost-efficient localization mechanism based on the KNN algorithm specifically tailored for underwater node localization. The key objectives of our proposed algorithm are to tackle the multifaceted challenges associated with underwater locali...
Taking Yanqing-Chongli highway for Beijing Winter Olympic Games as an example, we adopt a method of using photogrammetry and artificial intelligence rock structure parameter to identify working face. In this method, seven index parameters system are established. We use the KNN intelligent algorithm ...
Solved Jump to solution I am trying to use kdtree_knn_classification to do a 2d k-nearest neighbour search on in-memory data. However i am getting an unhandled exception in the algorithm.compute() function. Attached is my code snippet. Is something wrong with my usage?...
Directorymodelsis a link to a repository directory that contains an already pre-trained linear model in the RankLib format. NMSLIB can use this model to compute the non-metric similarity/distance function. Note that NMSLIB can useonly linearRankLib models produced by the coordinate ascent algorithm....
2. The KNN algorithm, consisting of the prediction and learning steps. Inside KNN predict, the set TxK represents the K-nearest neighbors of x in the dataset T , where distance is measured by Euclidean (or Manhattan) distance in the input vector space. F req(TxK ) is the most frequent ...
Solved Jump to solution I am trying to use kdtree_knn_classification to do a 2d k-nearest neighbour search on in-memory data. However i am getting an unhandled exception in the algorithm.compute() function. Attached is my code snippet. Is something wrong with my usage?...
Determine whether the algorithm reaches the maximum number of iterations; if so, the loop ends and outputs the optimal SABO location [𝑘,𝛼][k,α] and optimal fitness value; if not, return to Step 2. 3.2. SABO–VMD–WMH–KNN Model After obtaining the IMF components through the SABO–...
To improve the performance of roller bearing fault diagnosis, this paper proposes an algorithm based on subtraction average-based optimizer (SABO), variational mode decomposition (VMD), and weighted Manhattan-K nearest neighbor (WMH–KNN). Initially, the SABO algorithm uses a composite objective funct...