Applied Mechanics and Materials Vols. 543-547

Abstract: Heating saving energy is important in the study of saving energy. CAN is a high-performance and high-reliability build bus, transmission distance is very long, it can hang node on optional position in availability distance, the nodes are connected in parallel, and do not interfere with each other. By using the CAN bus technology, the control center connects CAN module, and the CAN module connects temperature sensor and valve controller. The temperature sensor gleans information that the control center controls heating valve according to the temperature information, and make room automatic control. The experimental results show that the system can stable operation. The system has been installed in our university.

Abstract: Given the issue that most of the parking lot intellectualized degree and management level is relatively low, this paper focuses on the function design based on Zigbee wireless sensor network, puts forward an intelligent parking lot management system based on Internet of things. This system mainly adopted CC2530 chip as the core of the Zigbee information processing unit to realize the short distance, low power wireless transmission. The intelligent parking lot management system this paper introduced can detect in individual's use of the parking space in the parking lot, and the number of vehicles in the parking lot.

Abstract: This paper discusses photovoltaic radar target simulator using NN, which provides a virtual simulation test environment for photovoltaic radar. A description of the controller architecture and associated stability analysis is given, followed by a more in-depth look at its application to a tiltrotor aircraft. Finally, it is proved that the control process of the photovoltaic simulator has superior performance and expected effect.

Abstract: In order to improve the level of production management and information development of textile industry, firstly the paper analyzed the hardware and software structure of jet loom monitoring system, then carried out related research on the information management of textile industry, introduced the related techniques, implemented the real-time monitoring and control based on CAN bus, data gathering and Winsock technology. The practice has proved that the loom network monitoring information system based on the industrial Ethernet has improved greatly the efficiency of production, and building network is simple, the development and maintenance are easy, and the performance is good and so on, which can provide better realistic instructions on realizing the standardization of communication, automation and information of the textile industry.

Abstract: There are many mathematical models in GPS height conversion fitting algorithms, such as polynomial surface fitting, Multi-surface fitting function, BP neural network and so on. The paper is focused on the fitting algorithms and summary of these kinds of GPS height conversion approaches and something useful is concluded.

Abstract: Particle swarm optimization (PSO) is a new optimization algorithm based on swarm intelligence. Firstly, the paper briefly introduces the origin of the PSO, the basic algorithm and the basic model, but an overview on the basic principle of the algorithm and its improved algorithm is also provided. Then, the research status and the current application of the algorithm as well as the development direction in the future are reviewed.

Abstract: In terms of the issue of the geographical annotation estimation on the condition of network map service environment, the content of traditional geographic annotation with the unstructured text formation is extended in this paper; meanwhile an extensive geographic annotation is defined. The emplacement process is applied to model the geographic annotation behavior. First and foremost, according to the frequency class, need confirm the geographic annotation text classification need confirming and establishing a quantitative convergence description about the spatial self-correlation in the emplacement adjacency based on Voronoi k order vicinity relationship. Proceeding further, an emplacement algorithm for the types of geographical annotation and transformative type is built in combination with the geographic text annotation and the de facto geographical annotation neighborhood. Lastly, through empirical results, in the practical situation of two typological geographic annotation sets having been known already, emplacement algorithm can come to be effective appraisal about the newly augmented geographic annotation in a practicable way.

Abstract: The concept of Gel'fand width plays an important role in the theory of information complexity and compressed sensing. In this paper, we study the approximation problems on the generalized Besov classesB^Ω_Ρ,θ in the norm of Lq by the Gel'fand methods in the deterministic and the Monte Carlo settings. Applying the Maiorov's discretization technique and some properties of pseudo-s-scale, we determine the asymptotic orders of this problem for some values of parameters p, q, θ.

Abstract: For the problem about a large number of irrelevant and redundant features may reduce the performance of data classification in massive data sets, a method of feature automatic selection based on mutual information and fuzzy clustering algorithm is proposed. The method is carried out as follows: The first is to work out the feature correlation based on mutual information, and to group the data according to the feature of the maximum correlation. The second is to automatically determine the optimal number of feature and compression features dimension by fuzzy c-means clustering algorithm in the data groups. The theoretical analysis and the experiment indicate that the method can obtain higher efficiency in data classification.

Abstract: The spatial information service system have the characteristics of a large amount of massive data and a large number of users, so the compression algorithm for statistical data will affects the system performance of spatial data services. A compression algorithm for spatial statistical data based on point cloud clustering is proposed in this paper to solve the above-mentioned problems. The access rule of the spatial data will be mapped into a point cloud. And the part of points will be deleted according to the clustering gradient of point cloud. Then the statistical data is compressed by run-length coding and spatial clustering extraction. The experimental results show that the algorithm have a high compression efficiency.