The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Due to significant industrial demands toward flight safety and airplane maintenance quality, improving airplane's reliability in usage stage has become an important activity and the research domain is rapidly evolving. In this paper eighteen years' field data, gathered from the maintenance phase of a Boeing 737 aircraft, is prepared as time-to-failure series. Then automatic processing models based...
This paper proposes a med-long term runoff forecasting model based on the principal component analysis (PCA) and the improved BP Neural Network. PCA was utilized to eliminate the relevance between input data, reducing input dimension and effectively reducing the model's structural complexity, improving the model's learning efficiency and forecast performance. The proposed model was predicted and verified...
This research aimed at integrating data from remote sensing resources and machine learning for developing a forecasting model of successful royal rainmaking operation in the upper north provinces of Thailand. The Support Vector Machine (SVM), neuron network method, and decision tree (C4.5) were used for data integration and forecast modeling. The data were collected between 1 January 2012 to 31 December...
With the continuous development of cloud computing, virtual desktop solutions are becoming more sophisticated. But the virtual desktop transmission system is still unable to guarantee the quality of remote video transmission service which has the characteristics of real-time and continuous. In order to improve the performance of remote video transmission system, an adaptive control mechanism for video...
A recent study namely software defect prediction model based on Local Linear Embedding and Support Vector Machines (LLE-SVM) has indicated that Support Vector Regression (SVR) has an interesting potential in the field of software defect prediction. However, the parameters optimization of LLE-SVM model is computationally expensive by using the grid search algorithm, resulting in a lower efficiency...
This paper presents an unbiased grey-Markov chain method to forecast the total retirement assets and the value of assets in 401(k) accounts, along with other defined contribution (DC) saving plans within years from 2015 to 2019. The prediction method integrates the unbiased grey model GM(1,1) and Markov chain method with fuzzy classification. This method takes advantage of the prediction power of...
Statistics and modeling is gaining more and more attention as the time for big data is coming. Variable choosing plays a significant role during modeling. The traditional methods like OLS and ridge regression could not satisfy interpretability and prediction accuracy at the same time. Tibshirani. R prompted Lasso and the new method could not only solve the above problem but also decrease the complexity...
There are some poor accuracy problems of grain yield prediction. GM (1, 1) prediction model and ARIMA (1,1,1) prediction model were established according to Jilin Province 1998–2011 grain yield data. In the same training sample, 2 kinds of methods were used to forecast grain yield. The average error is 7.88% and 12.32%, the average precision accuracy is 92.12% and 87.68% respectively. The test results...
In this paper, a new model combining neural networks with genetic algorithm is proposed to solve the problem of waste water discharge optimization. Firstly we apply resilient backpropagation(RPROP) neural networks to water quality daily data prediction based on water quality and waste water discharge history data, then through genetic algorithm process concerning water quality influence and economic...
Reliability and safety are two important issues in the manufacturing industry. In order to ensure the reliable operation of complex products, it is necessary to detect the delitescent faults in earliest time. A new Markov model of reliability assurance and failure prediction is put forward based on computer network technology in this paper. Firstly, the business processes for failure prediction using...
In order to obtain an effective prediction method about premixed water jet shot peening surface roughness, 2A11 aluminum alloy which always exist in project is used as the experimental material. When we do jet peening strengthen experiment, the pressure, nozzle scanning speed and the target distance are as the influencing parameters, to get experimental data about the influence of parameters on the...
With rapid development of microblog, more and more people are going to use microblog to transmit information and express their opinions. Therefore, predicting and monitoring the online hot-event tendency has become a significant support for our national security and development of society. Traditional prediction model tends to have a non-liner and unstable performance in time series. As a result,...
The recent boost in the usage of high-performance computing systems in small research environments, such as those found at many universities, stipulates the need of small-scale distributed systems. Owning to the rapid growth in both computing power and heat, development of proper thermal and resource management becomes crucial concern of the research community along with the vendors to ensure efficiency...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.