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Traffic flow prediction, which predicts the future flow using historic flows, is an important task in intelligent transportation systems (ITS). Efficient and accurate models for traffic flow prediction greatly contribute to the development of ITS. In this paper, we adopt the Gaussian process dynamical model (GPDM) to a fourth-order GPDM, which is more suitable for modeling traffic flow data. Specifically,...
Fuzzy Time series (FTS) has been widely applied to handle non-linear problems, such as enrollment estimation, weather prediction and stock index forecasting. FTS predicted values on the basis of an equal interval, which is determined the early stages of forecasting in the model. In this paper, we employed Genetic Algorithms (GA) to optimize the interval at first. Based on this, then Rough Set (RS)...
Adverse drug events (ADEs) are grossly under-reported in electronic health records (EHRs). This could be mitigated by methods that are able to detect ADEs in EHRs, thereby allowing for missing ADE-specific diagnosis codes to be identified and added. A crucial aspect of constructing such systems is to find proper representations of the data in order to allow the predictive modeling to be as accurate...
Electronic health records (EHRs) provide a potentially valuable source of information for pharmacovigilance. However, adverse drug events (ADEs), which can be encoded in EHRs with specific diagnosis codes, are heavily under-reported. To provide more accurate estimates for drug safety surveillance, machine learning systems that are able to detect ADEs could be used to identify and suggest missing ADE-specific...
This paper proposes a novel method to locate crowd behavior instability spatio-temporally using a velocity-field based social force model. Considering the impacts of velocity field on interaction force between individuals, we establish an improved social force model by introducing collision probability in view of velocity distribution. As compared with commonly-used social force model, which defines...
Provenance is becoming an important issue as a reliable estimator of data quality. However, provenance collection mechanisms in the reservoir engineering domain often result in missing provenance information. In this paper, we address the problem of predicting missing provenance information in reservoir engineering. Based on the observation that data items with specific semantic "connections"...
Using both qualitative and quantitative analysis, a set of relatively integrated evaluation indexes was developed to analyze the urban planning process in Guanzhong urban agglomeration. Key impact factors of coordinated development obtained from literature analysis were used as input, and the degree of coordinated development during 1988~2008 calculated by principal component analysis and the coordinated...
In this paper, we propose an improved combined forecasting model integrates the merits of data pretreatment, combined model and Markov chain, known as Markov combined model. The moving average is used for the data pretreatment or determination of trend, combined model is designed for the trend forecasting, and the Markov chain is employed for modifying the forecasting results of combined model. The...
Software-Intensive Equipment is the system which includes software and hardware. In this paper, we analyze the characteristics of software-intensive equipment and propose a non-parametric system reliability model to study the failure data with time series technique. The model uses fuzzy neural network and a wavelet function as the membership function to adjust the shape on line so that the model has...
City scientific and technological progress level classification and promotion play a central role in spurring city income growth and reducing poverty. Based on the Chinese city data availability, this paper built evaluation index system on the level of city scientific and technological progress. According to the city scientific and technological progress data which is large scale and imbalance, this...
Innovation system efficiency analysis and prediction play an important role in regional innovation systems development and improve benefit of innovative capacity for country. According to the county innovation system data which is large scale and imbalance, this paper presented a support vector machine model to predict county innovation system efficiency. The method was compared with artificial neural...
Customer churn analysis and prediction play an important role in customer relationship management and improve benefit of enterprise. According to the bank's customer churn data which is large scale and imbalance, this paper presented a support vector machine model to predict customer churn. The method was compared with artificial neural network, decision tree, logistic regression and naive Bayesian...
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