Advanced Materials Research Vols. 712-715

Abstract: The problem of diagnosing and forecasting reservoir sensitivity damage timely and accurately is always an important field of the reservoir protection research, this paper based on collecting data from core analysis .the main factors affecting reservoir sensitivity are obtained with single variable regression method, established a model of reservoir sensitivity prediction by applying an approach based on multi-level transfer function quantum neural networks. It effectively improved networks convergence and prediction accuracy. The analysis indicates that the model needs fewer parameters, has wider applicability and reliable results (the coincidence rate attains over 91%).and quantitatively reflect reservoir potential sensitivity, thus it can provide reliable basis to reservoir protection.

Abstract: The forecasting technique is one of the key factors for load forecasting. According to analysis, the Fast Intrinsic Mode Decomposition (FIMD) method is applied to short-term load forecasting in this paper. The specific implementation process of the proposed short-term load forecasting method is in the following. The selected load sample data are decomposed into a number of stationary Intrinsic Mode Functions (IMFs) with respective single mode by the FIMD method firstly. Then, each obtained load component with different frequency band is forecasted according to the Gene Expression Programming (GEP) method by time-sharing. The final forecasting models are obtained by rebuilding the forecasting model of each IMF. Lots of virtual forecasting tests are done, and it proves that the proposed load forecasting method based on the FIMD method in this paper is more accurate than the method based on Empirical Mode Decomposition (EMD).

Abstract: In recent years, with the large-scale grid connection of wind power, wind power as an important factor to load forecasting should not be overlooked; A least squares-support vector machine (LSSVM) has been improved for the region including wind power, based on the influence from the load caused by the changes of wind and the characteristics between load and wind power. The method uses the models of least squares-support vector machine to classify and build different models , and gets the integration of each model for equivalent load forecasting, which provides the reference for the region including wind power.

Abstract: To objectively determine layout priority sequence of element in human machine interface (HMI), and avoid the result difference induced in applying empirical method by different persons and keeping traceability of layout process, intelligent algorithm based on layout priority sequence for HMI was presented in this paper. With importance, operating frequency, operating sequence and reliability in ergonomics principles taken as parameters, the objective function model of layout priority sequence was made up based on ant colony algorithm. It was certificated in the main control room of a nuclear power plant, which layout priority sequence was acquired using the established objective function model. The experiment show that layout priority sequence deduced through the algorithm is a unique one. Its process is traceable, and it advantages than current methods.

Abstract: Constraint simplified mixed integer programming model was presented based on time transformation mechanism of no-wait flow shop. And a hybrid intelligence algorithm which combines the advantages of heuristic algorithm and neighborhood search algorithm was proposed. The initial population was generated by Johnson method, NEH method, Rajendran Method, Dannerbring method, and heuristic rules. The crossover and mutation operators in each generation were introduce neighborhood search (NS) and tabu search (TS). And the optimal individual was reserved in each generation. We compared the new hybrid intelligence algorithm (abbreviation H&NSGA ) with the algorithm blending heuristic and GA (NSGA), the algorithm blending neighborhood search and GA (HAGA), GA with the optimal individual reserved, and results show that the results and stability of solutions based on H&NSGA are better than the other three algorithms.

Abstract: In the current researches on network public opinion, the events are mostly focused, instead of the users who are of great significance, but often ignored. Concerning this problem,the user-based event model encompassing the users and their concepts is introduced in this paper, and user concept clustering in spreading events is simulated with the speciation algorithm based particle swarm optimization (SPSO). According to the results of user concept clustering, the analysis of event dynamic evolution model is implemented. The clustering convergence velocity of users is controlled with the change of velocity parameter for subsequently coordinating event evolution, so that the recognition of network hot events is realized and the situation of emergencies is analyzed.Finally, the PSO-based and SPSO-based clustering behaviors of users are simulated, respectively. The experimental results show that SPSO can more effectively simulate the clustering behaviors of users in public opinion network and discover multiple user clustering centers.

Abstract: Materials science is an interdisciplinary field applying the properties of matter to various areas of science and engineering. In this paper, we discuss a new set of symmetric tight frame wave-lets with the associated filterbanks outputs downsampled by several generators. The frames consist of several generators obtained from the lowpass filter using spectral factorization, with lowpass fil-ter via a simple approach using Legendre polynomials. The filters are feasible to be designed and offer smooth scaling functions and frame wavelets. We shall give an example to demonstrste that so -me examples of symmetric tight wavelet frames with three compactly supported real-valued sym- metric generators will be presented to illustrate the results.

Abstract: Manufacturing science focuses on understanding problems from the perspective of the stakeholders involved and then applying manufacturing science as needed. We investigate semi-orthogonal frame wavelets and Parseval frame wavelets in with a dilation factor. We show that every affine subspace is the orthogonal direct sum of at most three purely non-reducing subspaces. This result is obtained through considering the basicquestion as to when the orthogonal complement of an afffine subspace in another one is still affine subspace.The definition of multiple pseudofames for subspaces with integer translation is proposed. The notion of a generalized multiresolution structure of is also introduced. The construction of a generalized multireso-lution structure of Paley-Wiener subspaces of is investigated.

Abstract: In order to make an accurate prediction of coke quality, which indicators need to find out with the coal for coke affect. This paper proposes a principal component analysis to determine with the indicators of coal coke weight, the results show that this method can effectively confirm with the main component of coal coke impact, and lay a solid foundation for subsequent coke prediction.

Abstract: During digital final assembly of some types of aircraft, the posture of fuselage or wing must be revised in the case that real cutting allowances of some wing-fuselage joint holes are insufficient for finish machining. A constrained optimization modal is proposed to gain the optimum objective posture, which will ensure that each wing-fuselage joint has enough cutting allowance and meet all other technological requirements on the posture of fuselage or wing too.