Applied Mechanics and Materials Vols. 511-512

Abstract: According to the mechanization of the Kalman filter, the processing load of implementing a Kalman filter can be different under various system propagation rates and measurement update rates. With the definitions of uniform and complete observability, uniform and complete controllability, an analytic method of evaluating the effects of various system propagation rates and measurement update rates on the azimuth error during stationary north-finding was proposed. Variance calculations and experimental tests were presented to demonstrate the applicability of the proposed analytic method and let analysts maintain good physical insight into the estimation behavior of the final azimuth error. In conclusion, the proposed analytic method will help analysts optimize system propagation rate and measurement update rate to make the computational load fall within the available processing capacity.

Abstract: The main objective of dynamic deployment in Wireless Sensor Networks is to use the mobility of sensor nodes, trying to increase the coverage area of the networks through dynamically adjusting the node positions. In this paper, with the characteristics of the optimal sensor deployment in theory, we improve the standard artificial bee colony algorithm by introducing the distance factor to improve the onlooker bees selection probability formula, changing the working mode of the scout bee to avoid worse coverage rate and changing the limit l for scout bee to increase the chance to get better solution. Results show that the improved artificial bee colony algorithm has faster convergent speed and higher coverage rate compared with the standard artificial bee colony algorithm.

Abstract: T-S model is linearized at sampling points into the form of linear time-invariant state space , and using supervisory predictive control and muti-step predictive control strategy, which reduces amount of calculation and improves the control performance. Introduction

Abstract: A novel Mamdani fuzzy classifier based on improved chaos immune algorithm is developed, in which bilateral Gaussian membership function parameters are set as constraint conditions and the indexes of fuzzy classification effectiveness and number of correct samples of fuzzy classification as the subgoal of fitness function. Moreover, Iris database is used for classification effectiveness simulation experiment. The results show that Mamdani fuzzy classifier based on improved chaos immune algorithm can effectively improve the prediction accuracy of classification of data sets with noises and outliers.

Abstract: The H{infinity} filter design problem of recurrent neural networks with time delay is considered. Based on delay decomposition approach, the delay-dependent condition is derived to ensure that the filtering error system is globally asymptotically stable with a guaranteed performance. And the design of such a filter can be solved by the linear matrix inequality. A numerical example is provided to demonstrate that the developed approach is efficient.

Abstract: In structured environment, according to the requirement of indoor robot navigation for accuracy and real-time performance, On the basis of a novel positioning method using infrared landmarks, another novel infrared landmark indoor positioning method which uses high power infrared tube as landmarks, infrared camera as receiving sensor ,and combines track deduction is proposed in this paper. An improved Interacting Multiple Models Unscented Kalman Filter (IMM-UKF) data fusion algorithm for the two positioning scheme is used to improve the precision. Experimental results show that the novel infrared landmark indoor positioning method can increase the location speed and precision effectively.

Abstract: In each step of logistics, transportation plays an important role to increase profit for the logistics enterprises. The vehicle routing problem is getting more and more attention of researchers and logistics enterprises. There are many factors that affect the path, many of which can only be described qualitatively, such as traffic, environment etc., These factors need to be taken into account comprehensively for path selection. The paper proposes the two-stage optimization method of transport network to solve the problem of optimal path, which combines the qualitative analysis with quantitative analysis. Examples show that it is feasible. Keywords: Transport network; AHP algorithm; Dynamic programming

Abstract: Owing to its potential to satisfy all outstanding requests for the same data item with a single response, on-demand data broadcast becomes a widely accepted approach to dynamic and scalable wireless information dissemination. In the existing works, clients must wait until the deadline of their requests in the case the requests cannot be satisfied. In this paper, broadcast admission control is introduced to data broadcast systems such that the clients can be informed in advance on the result of admission control for the requests. Furthermore, a matching based allocation scheme is proposed for batch scheduling to maximize data sharing among requests. Simulation results show that our proposed algorithms have better comprehensive performance than traditional algorithms in terms of scheduling, admission control and QoS.

Abstract: This paper proposes an improved PD type Iterative Learning Control (ILC) algorithm combined with Wavelet theory for linear time-invariant systems with random time delays. The transfer function of multi-level wavelet filter is researched, and the sufficient condition of the convergence is given. Simulation results illustrate the applicability and effectiveness of proposed approach.

Abstract: An algorithm of weighted k-means clustering is improved in this paper, which is based on improved genetic algorithm. The importance of different contributors in the process of manufacture is not the same when clustering, so the weight values of the parameters are considered. Retaining the best individuals and roulette are combined to decide which individuals are chose to crossover or mutation. Dynamic mutation operators are used here to decrease the speed of convergence. Two groups of data are used to make comparisons among the three algorithms, which suggest that the algorithm has overcome the problems of local optimum and low speed of convergence. The results show that it has a better clustering.