Applied Mechanics and Materials Vols. 687-691

Abstract: With the speedy development of Internet, information technology has provided an unmatched amount of information resources. To help people to find helpful information, electronic commerce personalized recommendation technique emerges. Collaborative filtering is one successful personalized recommendation technology, and is widely used in many fields. But traditional collaborative filtering recommendation algorithm has the problem of sparsity, which will influence the efficiency of prediction. User context information is rarely considered in the recommendation process, especially in the collaborative filtering. In this paper, a new electronic commerce collaborative filtering recommendation algorithm is given which applies the user context information. This method combines the rating similarity and the user context similarity in the electronic commerce recommendation process to improve the prediction accuracy by efficiently managing the problem of data sparsity.

Abstract: A solution to improve the flexibility of simulation under the circumstance of SoS (System-of-Systems) combat has been provided in this paper. A CAS (Complex Adaptive System) based modeling method is used in this method after analyzing the military multi-layer architecture and surveying the modeling method, by joining CAS and MRM(Multi-Resolution Modeling), a military system is modeled in several resolution and some key technology are probed into and discussed in this paper. The analysis results show that method has great current significance and reference value for modeling combat system.

Abstract: Partially missing or blurring attribute values make data become incomplete during collecting data. Generally we use inputation or discarding method to deal with incomplete data before clustering. In this paper we proposed an a new similarity metrics algorithm based on incomplete information system. First algorithm divided the data set into a complete data set and non complete data set, and then the complete data set was clustered using the affinity propagation clustering algorithm, incomplete data according to the design method of the similarity metric is divided into the corresponding cluster. In order to improve the efficiency of the algorithm, designing the distributed clustering algorithm based on cloud computing technology. Experiment demonstrates the proposed algorithm can cluster the incomplete big data directly and improve the accuracy and effectively.

Abstract: With the development of information technology and data collection capabilities improve, the amount of data accumulated increase, missing data problems are more and more obvious. Traditional clustering methods can not cluster data set which contained missing data directly. In this paper, we proposed a novel missing data measurement method based on the incomplete information system theory and designed the similarity measure criterion for the discrete and successive of attributes separately. The experiment uses K-means clustering to test algorithm accuracy from different missing data rate and different amount of data two aspects, results demonstrate that the method can cluster missing data set efficiently and accurately.

Abstract: With the application of information science in research fields, the effective use of information has been a hot topic among researchers all over the world. As an effective way to improve the utilization of information, special database has been applied to many research fields by researchers. The paper researched on the construction of emergency special database for there are few researches on the topic. With the quality control theory, the paper proposed methods and process to construct emergency special database so as to improve the effective utilization of emergency information.

Abstract: Traffic state index (TSI) is a quantitative indicator to evaluate the degree of traffic congestion. Accurate prediction of the TSI can effectively ease the traffic pressure. This paper presents a prediction model based on the hybrid intelligent method. Firstly, use the cross operator and mutation operator to generate the particles and use the simulated annealing algorithm (SA) to prevent the particles falling into local optimum for the basic particle swarm algorithm (PSO). Secondly, use the improved PSO algorithm to optimize the weights and thresholds of the BP neural network (BPNN). Finally, Train the BPNN to obtain the optimal solution. The hybrid intelligent methods prediction model, named IPSOBP, is verified by using the actual data. The results show that the prediction model has higher accuracy to predict TSI compared with BPNN improved by genetic algorithm (GA) and BPNN improved by PSO.

Abstract: Earthquake prediction is one of the most difficult problems in modern natural science. Undoubtedly, various seismic parameters included in broadband radiated energy catalogue of NEIC is very important data source of investigate correlation between different earthquake within specific time space scope. In the paper, a fitting mode of seismic energy based on Support Vector Machine is established, using which we can fill the absent energy filed in the broadband radiated energy catalogue.

Abstract: In Mineral resource economics, a large amount of data stored in Excel files usually need to be shown in various charts for analyzing. Excel VBA provides a fast and easy way to create charts. This paper illustrates how to create batched combination charts of several mineral resources and their annual increments based on Excel VBA. Every step of creating process is illustrated in details and the Excel VBA codes are analyzed carefully. And the resulting combination charts are displayed to emphasize the different chart types and to prove the effectiveness of Excel VBA.

Abstract: The purpose of this paper is to propose an efficient numerical method for solving Volterra-type integro-differential equation of the second kinds. This method based on Legendre-Gauss-Radau collocation, which is easy to be implemented especially for nonlinear and possesses high accuracy. Also, the method can be done by proceeding in time step by step. Illustrative examples have been discussed to demonstrate the validity and applicability of the technique, and the results have been compared with the exact solution.

Abstract: Post evaluation is necessary for assess the success degree of a new system. A vessel traffic system project post evaluation method based on cloud model is presented. Firstly, we created the post evaluation index system and weight; Secondly, the expert scored the indexes and then cloud models were achieved; Thirdly, the comprehensive cloud algorithm calculated the result; Finally, the forward cloud generator restore the droplets distribution. The experimental result shows that the method is effective and intuitive.