Applied Mechanics and Materials Vols. 571-572

Abstract: Fetal electrocardiogram (FECG) blind source extraction (BSE) algorithm based on temporal structure and discrete wavelet transformation (DWT) in noise is proposed in this paper. After building the basic blind source separation (BSS) and BSE models for FECG, some preprocessing procedures based on the temporal structure of the FECG are constructed. Using DWT we can move the conventional time-domain signals to the wavelet-domain, and then the source number is detected and the robust noise reduction technique in FECG can be deduced too. According this preprocessing and second-order statistics (SOS), the proposed robust FECG extraction algorithm is derived.

Abstract: In this paper, linking with the basic principle of FCM (Fuzzy c-means clustering) algorithm, on the basis of theory research, the segmented partitions emerge when the state of the lives reaches an equilibrium. The artificial life approach is promising in image processing because it is inherently parallel and coincides with the self-governing biological process. Then combined with intensity-texture-position feature space in order to produce connected regions shown in the image, the final segmentation result is achieved at last. The experiment results prove that in the view of the biomedical image segmentation, this algorithm provides fast segmentation with high perceptual segmentation quality.

Abstract: It is hard to accurately predict solar radiation due to its very prominent nonlinear feature, so four major models based on the k-NN model, which have time, sunshine hours, temperature, wind speed and humidity as input data, are presented in the paper for hourly solar radiation forecasting. The models forecasting instantaneous solar radiation values in the Xining region have been created through experiments carried out in Qinghai University. The accuracy of the optimum model is up to 88.7% on average and 97.01% at most on the premise and the allowed absolute percentage error is lower than 20%.

Abstract: As the pivotal intermediary guiding public opinion in the interpersonal communication network, opinion leader’s discovery and identification have great social significance. Aiming at the existing problem of IDM models and its related model, this paper proposed a Influence diffusion model based on semantic orientation, which combines semantic understanding to reduce the diffusion of mendacious influence, analyzing text orientation to quantify the emotional intention, using reply structure to calculate diffused influence, then identifying the network opinion leaders. Experiments indicated that this method can improve the accuracy of opinion leader identification effectively.

Abstract: This paper proposes a multi-thread-memory particle swarm optimization (MTM-PSO) for dynamic optimization problems (DOPs). It introduces multi-thread memory to multi-swarm approaches to deal with DOPs. External memory and multi-swarm approaches are adopted. The best particles near the peaks in each environment are saved in the memory according to storage strategy of update and implement. Multi-thread memory makes full use of local and global optima found in each environment. It makes the good information in the previous evolution transfer to the current population adequately. Using the multi-thread memory and its storage strategy, the particles in the memory are always the best information of local and global optima found until in the current envionment. The information will benefit the future evolution. Experiments on the moving peak benchmark (MPB) for different numbers of peaks testiy MTM-PSO has better performance than dynamic optimization algorithms only with multi-swarm approach.

Abstract: Mining newsworthy events from a large number of microblogging information is not only the primary problem that several big microblogging websites need to solve, but also a new research field in micro-information age. For now, a lot of study about even recognizing has been made at home and abroad, but relatively rarely contrapose short text (microblogging message). The paper considers newsworthy event recognizing in short text as classification problem, utilizes the decision tree classification algorithm in data mining, sufficiently mines features of event in short text, and then recognizes the newsworthy event in microblogging. In the last, we verify the effect of the model.

Abstract: The problems of reliability and maintainability for repairable systems are investigated in this paper, and Markov process is employed to build the mathematical models of availability and reliability for the repairable systems. Firstly, the formulas of availability and reliability for single repairable systems are deduced. Then, the repairable system with two parallel components and one standby are investigated, which is common in engineering application. Finally, simple approaches are summarized for availability of complicated repairable systems. Since the two approaches has the same result, which provides theoretical proof for the study of repairable systems’reliability and availability.

Abstract: Multiswarm approaches are used in many literatures to deal with dynamic optimization problems (DOPs). Each swarm tries to find promising areas where usually peaks lie and many good results have been obtained. However, steep peaks are difficult to be found with multiswarm approaches , which hinders the performance of the algorithm to be improved furtherly. Aiming at the bottleneck, the paper introduces the idea of sequential niche technique to traditional multiswarm approach and thus proposes a novel algorithm called reverse space search multiswarm particle swarm optimization (RSPSO) for DOPs. RSPSO uses the information of the peaks found by coarse search of traditional multiswarm approach to modify the original fitness function. A newly generated subswarm - reverse search subswarm evolves with the modified fitness function, at the same time, other subswarms using traditional mltiswarm approach still evolve. Two kinds of subswarm evolve in cooperation. Reverse search subswarm tends to find much steeper peak and so more promising area where peaks lie is explored. Elaborated experiments on MPB show the introduction of reverse search enhances the ability of finding peaks , the performance of RSPSO significantly outperforms traditional multiswarm approaches and it has better robustness to adapt to dynamic environment with wider-range change severity.

Abstract: Ship sailing at sea is affected by many factors, such as winds, waves and so on, which makes six degrees of freedom motions and thus influences the shipboard arms control, aircraft landing and other operations. In view of the non-linear and non-stationary features of ship motion in waves, a new method based on EMD (Empirical Model Decomposition) and SVM (Support Vector Machine) is presented to predict the ship motion. The EMD is used to decompose the ship motion time series data into several IMFs (intrinsic mode functions) and a residual trend term, which decreases the difficulty of prediction. As the IMF is relatively stationary, but also non-linear, these features are fit to be processed by using SVM. Then the decompositions are used as inputs into SVM to forecast ship motion. The simulation and comparison analysis show that the EMD-SVM prediction model can effectively forecast the ship motion in waves.

Abstract: The learning behaviours of buyers and sellers with the assumption of bounded rationality were studied in the double sealed-bid bargaining mechanism. A multi-agent simulation trading system was constructed to observe the process of equilibrium approach when exist the multiple equilibria. The bidding choices of the agents were modelled by particle swarm optimization (PSO) algorithm. In our proposed model, two populations of buyers and sellers were randomly matched to deal repeatedly until the iteration stop, and each agent would update his bidding strategy in each round by imitating the successful member in his population and by private experience. Results show that the final biddings of the agents in both populations commonly approach a Nash equilibrium which is reasonable for the market principle.