Research And Implementation Of Moving Objects Query Technology Based On ELM Classification

Recently,with the rapid development of wireless communication technologies, positioning technologies and smart mobile devices, Location Based Service (LBS) is widely used on fields like health care, material flow, traffic, military, etc. LBS can provide personalized service for users according to moving objects’location information. LBS uses effective indexing technology in spatial and temporal to process query request service. In such environment, moving objects send their current location information to the server, then the server provides users service in the form of spatial-temporal query, such as range query, nearest/farthest neighbor query, etc. Such kinds of queries rely heavily on the maintenance of the current locations of the mobile objects. Aiming to these queries, providing effective spatial-temporal index structure is of curial importance.Moving objects index structure should effectively support update operation as well as effective query operation. Due to the frequent change of abundant of moving objects’location information, it causes the bad indexing efficiency of moving objects. How to reduce the update frequency of index structure caused by the change of moving objects’location has become the new research topic. One of the main jobs is proposing several strategies to enhancing the update efficiency of moving objects. Firstly, the entire region is divided into lots of girds, then we combine the statistic information of regions with mobile objects into feature vector. Secondly, we propose a novel index structure for mobile object, called index structure on moving objects based on ELM. In such index structure, R tree is used to index occupied regions instead of the mobile objects themselves and Extreme Learning Machine(ELM) is used to classify the regions. Thirdly, the paper provides an update algorithm on mobile objects based on region classification using ELM, and then presents several update strategies. Lastly, by analysis of comparing experiments, we verify that the proposed index structure and update strategies better reduce update efficiencyThe research about the relevant location based query and the corresponding processing technology is one of the current hot topics, but the current query technique still can’t satisify user. Based on such consideration, our paper presents a state query style among moving objects, such as asymptotic query, etc.We then proposes naive algorithm about the state query on moving objects, which can calculate state information among mobile objects. Becoming of the lowness of efficiency of execution on naive algorithm, the fastness of classification speed on ELM, the paper makes the distances between moving objects as feature values, then uses ELM to classify state among mobile objects; Lastly, by contrastive experiment between naive algorithm and query algorithm using ELM classification, the state query algorithm among moving objects based on ELM can largely improve the performance efficiency of query.