Case-based Mobile Phone Failure Similarity Matching Algorithm

With the development of technology, Mobile phones have more complexstructure. The functions were more perfect and high degree of intelligence. The statusof mobile phones in people’s lives has become increasingly important. So oncemobile phone appears faults will greatly affect people’s use. In case of Mobile phonefailure, the failure point relied on artificial search, it often appears misdiagnosis ormissed diagnosis, the accuracy needs to be further improved. Case-based reasoningtechnology is an emerging field of artificial intelligence problem solving methods.This method is applied to fault diagnosis in the field of mobile phones and it canimprove diagnostic capabilities. Therefore, study the mobile phone fault diagnosistechnology based on case-based reasoning, to accurately determine fault point has avery important role.In this paper, based on case-based reasoning, we put forward a kind of mobilephone fault case retrieval algorithm CRE (Case matching algorithm based onRough-sets and Euclidean distance) in case matching problem in the cloudenvironment. First, cloud computing platform to collect phone fault parameters,according to the parameters set constructed rough set information table, using Roughset and information table to get weight values of characteristic parameters andcombined with the expert experience to obtain the finally attribute weights. Finally,use this weight values and Euclidean distance to calculate the similarity between thecases, identify the most similar cases with new cases. These algorithms are on thebasis of the date and experience, avoiding the disadvantage of being overly dependenton artificial expertise. These algorithms are on the basis of the date and experience,avoiding the disadvantage of being overly dependent on artificial expertise. Thesimulation shows the effectiveness of the algorithm.Innovation point of this paper is to introduce rough set theory to the process ofcase-based reasoning, using rough set is from the perspective of existing case to calculate the value of the properties characteristic parameters of each case, after thecombined with the expert experience to get an integrated weight value and thencalculate the similarity between cases, so that the final result is more accuratesimilarity.Phone plays an important role in the mobile Internet, its future status will bemore important. Mobile phone fault diagnosis in the cloud environment is also facingmany challenges. In this paper, on the basis of existing research results, the artificialintelligence in the field of case-based reasoning is introduced into the fault diagnosisof a mobile phone and tentatively proposes the CER, has certain theoretical value andpractical significance.