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This paper introduces an improved user-based movie recommendation algorithm based on the user-based recommendation algorithm, which rewrites usersimilarity by merging users' ages and genders into users' preference values on items. The RMSE (Root Mean Square Error) then is provided to indicate that the proposed algorithm is more accurate that the original one.
The research in the field of web information extraction technology has made some progress in the past few years, but the extraction performance of the system still needs a lot of improvement. To solve this problem, a new intelligent framework for web information extraction is proposed in this paper. The framework provides a mechanism for automatic generation of Web information extraction rules, and...
With the in-depth development of the mobile terminal system, the extendibility of application has become a basic demand. Mobile terminal system urgently needs a mechanism which can load the APP module in the running state dynamically. This paper presents an intelligent dynamic loading mechanism and discusses the realization of the mechanism. Experiments show that this mechanism has the advantages...
In this paper, a face detection algorithm based on AdaBoost algorithm combined with Haar classifier depth cascade about OpenCV is proposed. In order to solve the problem that the training depth of AdaBoost algorithm is not enough and the Haar classifier is not accurate because of the lack of depth cascade classification. Before the face feature extraction, AdaBoost algorithm is used to train the face...
Based on the model of Chinese soil loss equation (CSLE), this paper puts forward a model to calculate the large scale data automatically. At present, the domestic use of this model to calculate the soil loss modulus methods are mostly used in the existing calculation tools, manual calculation of a basin or county soil erosion modulus. However, the data collected from the first national water resources...
To overcome the defects of partial multi-objective constrained optimization evolutionary algorithms especially in getting local optimal solutions, poor diversity and robustness, a hybrid algorithm which is named NCCMOEA (Non-dominated Clonal Constrained Multi-objective Optimization Evolutionary Algorithm) is proposed in this paper. This new algorithm combines the Pareto constrained-dominance, improved...
To date, with the rapid development of information society, it has great significance to video websites that using the existing relationship between users and items to analyze users' behavior and find the correlation of information, which can mine users' preferences deeply and provide the optimal recommendations to users. This paper explores an improved item-based movie recommendation algorithm based...
Inadequate crawling behavior of the crawler will have a very serious impact on the site, so anti crawling mechanism is an important function for the website. Most of the existing anti crawling methods are non real time detection, and the recognition accuracy is low. By analyzing the characteristics of Crawler, a real-time crawler detection method based on sliding time window is proposed, which improves...
The identification of user travel pattern has important research value for intelligent transportation. Intelligent terminal can supply GPS, acceleration sensors, pressure sensors data which can provide data base for the identification of user travel patterns. This paper research on a user travel pattern decision model based on the sensor data. The decision algorithm adopts decision tree algorithm...
For traditional RBAC access control model is not a good solution for user access control in different regions, this paper analysis and research on the traditional model, we propose a control model RBAC-RB based on different areas of authority. According to this model, which realize the access control that users in different regions of the data-level permissions. And the model successfully used in...
It is significant to make a short-term power output forecast for the solar photovoltaic power station. On the one hand it helps guarantee power grid security, on the other hand it can increase the efficiency of power generation. This paper designs a high concentrated photovoltaic output power prediction model based on the Fuzzy Clustering and Radial Basis Function (RBF) neural network, uses the meteorological...
High concentration photovoltaic is a new type of solar power generation mode, which has better photoelectric conversion rate but is more vulnerable to weather factors. Therefore, accurate and efficient forecasting methods have important significance of increasing the security and stability of the solar power station. This paper focuses on the short-term forecasting method which aims at forecasting...
The accurate power output forecasting is advantageous to improving the reliability of power system. This paper presents a new power forecasting model based on grey neural network and Markov chain. In grey neural network, it gains the power at the corresponding time as the forecasting result. As getting the relative prediction residual errors of the forecasting sample data with grey neural network,...
Through analyzing in the data characteristic of SCADA system and the demand of integrating lots of distributed power station data to analyze, propose a solution to build a high-performance parallel computing platform in process data of power station based on cloud computing technology. First, it presents a detailed description of the problems encountered in SCADA system, and an overview of the characteristics...
The power generation of solar power station has close relationship with the weather and environmental factors such as temperature, humidity, irradiation, etc. so prediction of power generation is very important for the intelligent power control. BP neural network is an effective tool to predict task, but too many parameters will cause the BP network converging difficultly. This article uses the principal...
The parallel database system (PDS) owns high performance and high availability and is suitable for mass data storing and processing. However, data loading performance is a bottleneck in PDS. To improve the data loading performance, this paper proposes an optimized load algorithm based on cloud platform which can promote the speed of load process. The paper gives the algorithm description, elaborates...
Cloud computing environment for the efficient resources allocation is an important issue in the field of cloud computing. The resources in Cloud computing application platform are distributed widely and with great diversity. User demands of real-time dynamic change are very difficult to predict accurately. The heuristic ant colony algorithm could be used to solve this kind of problems, but the algorithm...
The influence of an individual in the social network is a both subjective and objective matter, which depends on the quality of his web pages and the altitudes of the others. But there is still much that can be said objectively about the relative influence of every individual in the social network. This paper describes SocialRank, a method for measuring the influence of an individual objectively and...
Based on the research of the 863 program “Generation and Applications of Global Products of Essential Land Variable”, the paper proposes an ontology-based production model of parameter products of satellite remote sensing data, which describes the design of satellite ontology, remote sensing data ontology and parameter products ontology. And based on the ontology model, production system architecture...
The development of Internet and the appearance of the Web2.0 have dramatically changed the communication habits of the people. The network communications based on social relationships and interests are more and more popular. It has great significance for dissemination and utilization of information to research the community structure formed by the user group who uses these communication modes. In...
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