Advanced Materials Research Vol. 818

Abstract: A secure scheme for wireless sensor network is presented through dividing sensing area into clusters and using the overlap key sharing (OKS) concept in this paper. The two-dimensional sensing square is divided into a number of small squares called cells, four of which consist of a cluster called logical group. The overlap key sharing protocol creates long bit clusters as the key cluster pools and distributes a sub-group to store every sensor as the key cluster. Analysis and comparison demonstrate this scheme enhances the WSN security, realizes the flexile secure grades for WSNs, and has good network connectivity.

Abstract: Vehicle-use engine performance optimization question belongs to many target decisions. A question that meet widespreadly in many target decisions is the select of weight coefficient, and how convert many targets as the question of simple target. This paper's tallying up four kinds of the select devices of weight coefficient in the vehicle-use engine performances optimization process according to the different circumstance.

Abstract: Building a model to predict the state of slag on coal-fired boilers is a good way to optimize the coal combustion and reduce the risk of boiler slag. This paper built new models based on vague sets to predict the state of slag on coal-fired boilers, in which there were six input vectors, which were softening temperature, SiO₂-Al₂O₃ ratio, alkali-acid ratio, percentage of silicon content, the dimensionless average temperature furnace and the dimensionless inscribed circle diameter furnace, and one output vectors, which was slagging degree. Two methods, which were based on the sense of distance and symmetric fuzzy cross entropy, were proposed to calculate the similarity between vague sets. 10 coal burning boilers were selected as known samples and the feasibility of the new methods was proved by the result of predicting the state of slag on the four coal burning boilers from Jilin heat and power plant, Xinli power plant, Jinzhou power plant and Qinhuangdao power plant. Through predicting and determining, it proves that the two pattern recognition models are high in prediction accuracy. Compared with the normal method, it is easier for operators to predict, determine the slagging state and reduce disturbance as far as possible. Besides, a prediction system has been developed by object-oriented high-level language accordingly.

Abstract: A new prediction model of material chemical character effects on biofouling mass was built based on RBF network, in which there were four input vectors, which were carbon content, hydrogen content and oxygen content of the solid materials and flow rate, and one output vectors, which was the average amount of biofouling formed on the solid surface. Firstly, creating the sample database and normalizing all samples. Secondly, training the model based on the training samples to obtain the optimal prediction model, then, predicting the training samples. Comparing with experimental results, the accuracy of the RBF model is 95.5%. Besides, the model was tested by poly (ethylene terephthalate), and the predicted and actual results are consistent. Thus, the construction of the predictive model is reasonable and feasible.