Aiming at this problem and based on the true data of a certain company,the time series prediction by periods-model and case-based nearest neighbor algorithm was proposed,then their results are compared.

Based on the K nearest neighbor algorithm,an improved method was proposed for selecting genes-related documents from biology literature,and then automatically annotating and classifying.

The convergence analysis of an approximate proximal point algorithm for monotone variational inequalities

Proximal point algorithms(PPA) arc attractive methods solving monotone variational inequalities(VI).

An approximate proximal point algorithm for solving monotone variational inequalities is constructed,and the convergence of the algorithm is proved under the condition that any indirect step is not required.

Conventional KNN(K-nearest Neighbor) algorithm requires large computational consumption when training samples are large.

It is a deterministic algorithm, with its time complexity the same as the nearest neighbor algorithm, that is, O(n2), where n is the number of cities.

The decline of recommending quantity resulted in the extreme sparsity of user data was dealt with,based on nearest neighbor algorithm and the combination of selective sampling and lookahead framework for recommendation system,with the purpose of improving the accuracy of recommendation.