Applied Mechanics and Materials Vols. 548-549

Abstract: Taguchi Gen'ichi introduced Mahalanobis-Taguchi System (MTS) which is in combination with the concepts of quality engineering and Mahalanobis Distance (MD). The MTS is proposed as diagnosis and forecasting method using multivariate measurement scale with its intention to help policy maker as basis for decision making. This study applies MTS approach in a manufacturing process to reduce a set of parameters, at the same time there will be a pattern, which can forecast and identify important parameters, constructed by MTS method. Through this pattern can minimize unimportant inspection in process and save unnecessary time and cost. The primary goal to structure a measuring scale which makes accurate forecasting in multidimensional system. The case study in this paper reviews the planarity of back-end process in 8-inch silicon wafers on the purpose to construct a pattern of reduced set of parameters. In this paper, using thirty-two current variables as reference space and furthermore reducing the variables to seven parameters in order to predict defective items. As a result, it has still good discriminant accuracy. If validation of the reduced-set parameters is reliable with its good discriminant accuracy, it means that the company in this case study can built defective items warning of the pattern parameters in back-end process because this approach of selecting parameters is feasible.

Abstract: Recently some studies have been revealed by inspiring from animals which live as colonies in the nature. Ant Colony System is one of these studies. This system is a meta-heuristic method which has been developed based upon food searching characteristics of the ant colonies. Ant Colony System is applied in a lot of discrete optimization problems such as travelling salesman problem. In this study solving the travelling salesman problem using ant colony system is aimed.

Abstract: We research on application of ant colony optimization. In order to avoid the stagnation and slow convergence speed of ant colony algorithm, this paper propose the multiple ant colony optimization algorithm based on the equilibrium of distribution. The simulation results show that the optimal algorithm can have better balance in reducing stagnation and improving the convergence.

Abstract: This paper mainly considers the application of the ant colony in our life. The principle of ant colony optimization, improves the performance of ant colony algorithm, and the global searching ability of the algorithm. We introduce a new adaptive factor in order to avoid falling into local optimal solution. With the increase the number of interations, this factor will benefit the ant search the edge with lower pheromone concentration and avoid the excessive accumulation of pheromone.

Abstract: In order to reduce the Orthogonal Frequency division Multiplexing (OFDM) Inter-Carrier Interference (ICI), Put forward a kind of modulation method that based on the orthogonal frequency division multiplexing of orthogonal wavelet, Using orthogonal wavelet instead of discrete Fourier transform, optimize the design for OFDM systems, on the premise of without protection interval to reduce the system interference, using MATLAB to simulate the OFDM system, results show that the optimization of the OFDM can reduce the power of the ICI and Inter-symbol Interference (ISI) and improve the comprehensive anti-jamming of the OFDM system.

Abstract: In this paper, a novel joint estimation of channel effective order and channel impulse response (CIR) is presented for multiuser orthogonal frequency division multiplexing/space-division multiple-access (OFDM/SDMA) systems. By exploiting Akaike’s Information Criterion (AIC) as the fitness function to search the optimal order, the proposed scheme performs the channel effective order and CIR estimation in a parallel way based on differential evolution (DE) algorithm. Simulation results demonstrate that the proposed scheme is capable of attaining a better mean square error performance than the fixed channel order scheme, and improving the performance of time-domain maximum likelihood (ML) channel estimator.

Abstract: This paper proposes a sign-algorithm based on adaptive Laguerre filter structure for improving the performance of the direct sequence-code division multiple access (DS-CDMA) communication system. The proposed adaptive equalizer employs a combination of sign and least mean square (LMS) algorithms to minimizing the effect of inter-symbol interference (ISI) that arises due to multipath propagation, and the computational complexity of equalizer. The performance of proposed equalizer was compared with traditional equalizers such as LMS and RLS algorithms in terms of varying path. The function detail and performance results of the proposed equalizer are described by computer simulations in terms of the bit error rate (BER).

Abstract: Wind speed forecasting is an effective method to improve power stability of wind farm. Grey system theory have certain advantages in the study of poor information and uncertainty problems, it is suitable for the system with limited computing power and data storage capacity, such as wind turbine control system. In order to further improve the prediction accuracy of grey model, we combined GM (1, 1) model and BP neural network prediction model in this paper, and improved the combined model by background value optimizing and introducing genetic algorithm. Through analyzing the simulation results and comparing the forecasting results with the actual wind speed, it is clear that the improved combined prediction model is superior to pure grey forecasting model and it meets the needs of the wind power control.

Abstract: Continuous Petri Nets(CPNs) has been a useful tool not only to approximate a discrete system but also to model a continuous process. In this paper, we consider a general CPNs----Interval speed CPNs(ICPNs). An approach to translate Interval speed CPNs to event clock automata is proposed. Since the instantaneous firing speed (IFS) vector is one of key parameters in behavior analysis for ICPN, an efficient way to determine the IFS of ICPNs was presented firstly. Then an algorithm of constructing evolution graph for ICPNs was developed, which offers all information for constructing automata for ICPNs. Furthermore, a procedure to transform a state evolution graph of ICPNs into an event clock automata is build. After having constructed the associated event clock automaton, we show that classical approaches of verification of event clock logic formulas can be applied to prove that the ICPNs model satisfies a particular property.

Abstract: The reduction of the index system at home and abroad mainly starts from the basic statistics and soft computing theory, but these methods are not always effective for complex index system. In this paper, a new multi-level indicators reduction model based on complex index system has been proposed through in-depth analysis of the multi-level environment and growth factors which affecting crop growth. First, exception handling model was introduced to determine indicators abnormalities or not in this method, then make a preliminary reduction in indicators of index layer from the point of multi-level statistical; Second, through clustering reduction model, and a further perfection of the index system is discussed; Finally, the optimal reduction index system of crop growth evaluation is proposed. The experiment results show that it can get the optimal reduction index system of crop growth evaluation by this method, and the optimal index system can cover 90% of the index system.