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Precipitation prediction, such as short-term rainfall prediction, is a very important problem in the field of meteorological service. In practice, most of recent studies focus on leveraging radar data or satellite images to make predictions. However, there is another scenario where a set of weather features are collected by various sensors at multiple observation sites. The observations of a site...
Link prediction is a fundamental problem in social systems, including the prediction of user interaction and the links between users and items, which is also referred to as recommendation. Previous works mainly focus on the prediction task independently, which predict either the links between users or the links between users and items. However, these two prediction tasks are always coupled with each...
The man-hour costing is the largest cost in the chemical plant design companies because the design processes are undertaken by the staff. The accurate man-hour forecasting can facilitate the design process control and the human resources scheduling optimization so as to cut the costs. This paper presents a framework, combining the Back Propagation (BP) Artificial Neural Network (ANN) and Genetic Algorithm...
A multivariate discrete grey forecasting model is proposed to solve the problem that the qualitative relative factors can't be employed in traditional models. Firstly, a new model is constructed though introducing dummy drivers. Then, the parameters estimation method and recursive function of the model are discussed. Furthermore, dummy driver setting, pre and posttest methods of dummy drivers are...
The prediction of T-cell epitopes is of great help for facilitating vaccine design and understanding the immune system. In the bioinformatics, the MHC-binding peptides are defined as the T-cell epitopes, which will trigger the immune response to the antigens. However, binding peptides cannot necessarily activate the immune response, namely non-immunogenic. Until now, little attention has been paid...
Inventory control plays an important role in production and supply chains management. As the cycle of productions becomes shorter and customer demand becomes more unstable than before, the ordinary inventory control method can not deal well with the problem. Adaptive inventory control method receives attention of both academicians and practitioners. But none analytical solutions to safety stock is...
A random simulation method is proposed to improve the grey forecasting model. This method is enlightened by Monte Carlo simulation method. It can compare the model error between different grey forecasting models, even between grey model and other forecasting methods. The experiments are used to demonstrate the proposed method, and the results show that this method is effective.
Base bleed propellant is an important component of the increasing rang projectile using base bleed technology. Unsteady strongly combustion leads to extinguish, reignition or critical state which produce an effect on rang dispersion. The burning behavior is determined by the initial pressure of combustion chamber and the maximum pressure decay rate, which was investigated by simulation experimental...
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...
For the problem of soil moisture prediction, existing approaches in literature [M. Kashif et al., 2006; Y. Shao et al., 1997] usually utilize as many decision factors as possible, e.g. rainfall, solar irradiance, drainage, etc. However, the redundancy aspect of the decision factors has not been studied rigorously. Previous research work in data mining has shown that removing redundant features improves...
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