%0 Journal Article
%T An Algorithm for Mining of Association Rules for the Information Communication Network Alarms Based on Swarm Intelligence
%A Yang Wang
%A Guocai Li
%A Yakun Xu
%A Jie Hu
%J Mathematical Problems in Engineering
%D 2014
%I Hindawi Publishing Corporation
%R 10.1155/2014/894205
%X Due to the centralized management of information communication network, the network operator have to face these pressures, which come from the increasing network alarms and maintenance efficiency. The effective analysis on mining of the network alarm association rules is achieved by incorporating classic data association mining algorithm and swarm intelligence optimization algorithm. From the related concept of the information communication network, the paper analyzes the data characteristics and association logic of the network alarms. Besides, the alarm data are preprocessed and the main standardization information fields are screened. The APPSO algorithm is proposed on the basis of combining the evaluation method for support and confidence coefficient in the Apriori (AP) algorithm as well as the particle swarm optimization (PSO) algorithm. By establishing a sparse linked list, the algorithm is able to calculate the particle support thus further improving the performance of the APPSO algorithm. Based on the test for the network alarm data, it is discovered that rational setting of the particle swarm scale and number of iterations of the APPSO algorithm can be used to mine the vast majority and even all of the association rules and the mining efficiency is significantly improved, compared with Apriori algorithm. 1. Introduction The operation and maintenance management of information communication network mainly refers to timely discovery, locating and handling of any network fault to ensure smooth and efficient operation as well as guarantee in major emergencies pertinent to network operation, complaints about network quality from customers, assessment and analysis of network quality, prediction of planning, construction, and so forth. The time consumed during fault location and judgment in the application layer of a large-scale network accounts for 93% of its total time for failure of recovery [1]. The huge network structure and multifunctional device types also bring about large amounts of alarm data due to such characteristics of the information communication network as topological structure densification, network device microminiaturization, communication board precision, and so forth. Therefore, the foundation of the network operation and maintenance is the effective management of the network alarms. As an important supporting means for network operation and maintenance management, network management system directly influences the quality of service which the information communication network provides to its customers [2]. The network management
%U http://www.hindawi.com/journals/mpe/2014/894205/