Applied Mechanics and Materials Vols. 433-435

Abstract: Most of the imperfect inductive inferences are under the condition of inadequate cognition, so is the universe and black hole oriented topological inductive logic. When a cognition is not very clear, what we need is Lee Smolins logic existing for working cosmography, which is called Topos Theory. We human cognition has another big loophole, i.e., our inner black hole, which is our wisdom itself. The wisdom that we human have is another unclear world similar to universe. So the understanding of human wisdom and its cognitive process needs to construct topos logic.

Abstract: In modern science, machine language was developed on the basis of multidisciplinary, so it forms the nature of cross subject or multidisciplinary subject, especially it crosses with modern logic. Burks developed the logic of casual statement, and tried to apply to the constructing of machine language. While applying the logic of casual statement to machine language, philosophy of logical machine was put forward. Philosophy of logical machine takes an important role in guiding the development of the discipline of contemporary machine language and its practical applications.

Abstract: As humankind enters the era of organized social cognition, the collective wisdom of the human form needs to face a very complex social conditions and the social environment. In such circumstances, more likely to use social cognition inductive logic. The accumulation and wealth of society knowledge will be more and more abstract representation to promote social awareness, and promote more in-depth characteristics from behavior to inductive references, while ignoring or rarely used to from the nature of the behavior of deductive reasoning. In dynamic cognition conditions, the fusion method is using the following branches of cognitive logic, dynamic logic and probability logic to combine to form a probabilistic dynamic cognition logic, and logic to study the use of these information changes in probability reference. In complex cognitive conditions, the pursuit of knowledge as the basic logic of the value of research areas, including philosophy logic, artificial intelligence logic, computer logic, fuzzy logic and so on.

Abstract: Particle Swarm Optimization (PSO) is a good method to tune PID controller. But it doesnt work well enough in the application condition of high real-time requirement and control accuracy. This paper describes a parallel PSO algorithm for PID controller tuning. We designed the parallel algorithm and realized it in multi-core and message passing interface (MPI). We developed the test system using Visual C # 2008, and the performance experiment shows that the algorithm has satisfied tuning accuracy, speedup and efficiency.

Abstract: This paper presents a new approach to multi-robot exploration of unstructured environment in which both multi-robot task cooperation and behavior coordination strategies are implemented. The task cooperation is achieved by assigning exploring goals to robots dynamically in a cooperative way, and the behavior coordination of robots are carried out with modified artificial potential field to assure a balanced distribution along the frontier areas as soon as possible. In this way, unnecessary detours are avoided so as to make the exploration process more efficient. A series of simulation results demonstrate that the task cooperation and behavior coordination among multiple robots are well implemented to distribute various robots over the unknown complex environment properly and accomplish the exploration mission effectively.

Abstract: This paper proposes a novel stopping criterion based on the HDA stopping criterion. To devise the criterion, we consider both the HDA criterion and the mean of the absolute values of the log-likelihood ratios (LLR) at the output of the component decoders over each frame together. The new criterion saves more than 0.5 iteration ,in the low signal-to-noise ratios (SNR) situation,with a negligible degradation of the error performance.

Abstract: One approach to extend the network lifetime is to divide the deployed sensors into disjoint subsets of sensors, or sensor covers, such that each sensor cover can cover all targets and work by turns. The more sensor covers can be found, the longer sensor network lifetime can be prolonged.This study propose a novel hybrid genetic algorithm (NHGA) comprising both basic generic operations with a fitness-improving local-search strategy to divide all wireless sensor nodes into a maximum number of disjoint set covers (DSCs). The simulation results show that NHGA outperforms the existing methods by generating more disjoint set covers and prolongs network lifetime.

Abstract: The purpose of this paper is to review the literatures which have made an explicit study on personalized recommendation in E-Learning systems. By identifying the important research areas, which are in different perspectives, firstly, filtering recommendation is introduced before the illustration of how it has been developed in E-Learning systems. Then personalized recommendation is proposed for E-Learning system. Although social network is the basic way to improve the communication efficiency with others in E-Learning system, previous studies pay less attention on this. Therefore social network analysis should be taken into consideration for the recommendation in E-Learning system for further research.

Abstract: Support vector machine (SVM) could well solve the over-learning and the low generalization ability of the neural network. But the single classifier cannot achieve satisfactory recognition rate and anti-interference ability. An aircraft engine fault diagnosis method based on support vector machine multiple classifiers is proposed in this paper. Firstly, sample characteristic information which constitutes the fault feature vectors obtained from the existing engine fault. Then, after training the SVM multiple classifier by faulty feature vectors, the SVM model of the fault diagnosis system is established; Finally, the trained SVM multiple classifier is used to recognize and classify the test faults. Applying the noise on the test samples, SVM multiple classifiers can still get a good diagnosis effect. It shows that the fault diagnosis algorithm has good robustness and can be applied to the study of aero engine fault diagnosis.

Abstract: This study analyses and compares several forecast methods of urban rail transit passenger flow, and indicates the necessity of forecasting short-term passenger flow. Support vector regression is a promising method for the forecast of passenger flow because it uses a risk function consisting of the empirical error and a regularized term which is based on the structural risk minimization principle. In this paper, the prediction model of urban rail transit passenger flow is constructed. Through the comparison with BP neural networks forecast methods, the experimental results show that applying this method in URT passenger flow forecasting is feasible and it provides a promising alternative to passenger flow prediction.