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Intelligent Transportation Systems (ITS) plays a significant role in the traffic management, i.e. traffic jam prediction, route guidance. Due to the hardware failure or data transformation failure, some traffic observation data may be occasionally missed, which seriously affect intelligent transportation information service. So, the completion of traffic observation data has now become an issue that...
To effectively integrate distributed and heterogonous open data now is an essential problem of Web research community. Due to rapidly development of open data, e.g. geographic, track, dynamic geospatial data, governments are required to release more and more data for academics and industry. The ubiquitous data are in various types and formats, e.g. number, graphic or specific format provided by different...
In this paper, we focus on student study quality evaluation in the educational system. To achieve a better performance on the teaching thinking of the students and improve teaching efficiency and learning quality, we proposed a new method based on the cloud model. The results of the experiments show that the new method is effective and operable. The application of the cloud model in the personalized...
Simulation modeling is an increasingly popular and effective tool for analyzing transportation problems that are not amendable to study by other means. For any simulation study, model calibration and validation is a crucial step to obtaining any results from analysis. This paper proposed a systematic, practical procedure for microscopic simulation model calibration and validation. The validity of...
The size of data sets being collected and analyzed in the industry for business intelligence is growing rapidly, making traditional warehousing solutions prohibitively expensive. Hadoop is a popular open-source map-reduce implementation which is being used in companies like Yahoo, Facebook etc. to store and process extremely large data sets on commodity hardware. However, the map-reduce programming...
This paper provides a neural network model to address the problem of travel time prediction. A single segment model based on the state space neural network is used for modeling traffic flow on one single signalized segment. Thus, modelling a longer arterial covering several controlled intersections is conducted by assembling each individual segment models. This reduces significantly the amount of...
Inductive Logic Programming (ILP) is one of the main approaches to relational learning, with the stronger expressive power and the ease of using background knowledge. However, compared with the traditional attribute-value learning methods, it is much less mature for ILP to deal with imperfect data. This paper applies the Tolerance Rough Set to ILP to further extend the RS-ILP model. We first investigate...
This study presented a new diagnosis system with integrating 12-lead ECG data into a density model for increasing accuracy rate and flexibility of diseases detection. A hybrid system with HMMs and GMMs was employed for data classification. For myocardial infarction, data of lead-V1, V2, V3 and V4 were selected and HMMs were used not only to find the ECG segmentations but also to calculate the log-likelihood...
Ontology theory is a scientific methodology which standardizes the description of knowledge and concept by computer language, organizes knowledge, and does knowledge service. Knowledge management is official management for knowledge in order to make it convenient to produce, access and re-use knowledge. The key ontology technologies applied in the knowledge management field are studied in the paper...
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