The circular-consecutive k-out-of-n:F(G) system (Cir/Con/k/n:F(G) system) usually consists of n components arranged in a circle where the system fails (works) if consecutive k components fail (work). The optimization ...
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The circular-consecutive k-out-of-n:F(G) system (Cir/Con/k/n:F(G) system) usually consists of n components arranged in a circle where the system fails (works) if consecutive k components fail (work). The optimization of the Cir/Con/k/n system is a typical case in the component assignment problem. In this paper, the Birnbaum importance-based genetic algorithm (BIGA), which takes the advantages of genetic algorithm and Birnbaum importance, is introduced to deal with the reliability optimization for Cir/Con/k/n system. The detailed process and property of BIGA are put forward at first. Then, some numerical experiments are implemented, whose results are compared with two classic Birnbaum importance-based search algorithms, to evaluate the effectiveness and efficiency of BIGA in Cir/Con/k/n system. Finally, three typical cases of Cir/Con/k/n systems are introduced to demonstrate the relationships among the component reliability, optimal permutation, and component importance.
In a real e-commerce website, usually only a small number of users will give ratings to the items they purchased, and this can lead to the very sparse user-item rating data. The data sparsity issue will greatly limit ...
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In a real e-commerce website, usually only a small number of users will give ratings to the items they purchased, and this can lead to the very sparse user-item rating data. The data sparsity issue will greatly limit the recommendation performance of most recommendation algorithms. However, a user may register accounts in many e-commerce websites. If such users' historical purchasing data on these websites can be integrated, the recommendation performance could be improved. But it is difficult to align the users and items between these websites, and thus how to effectively borrow the users' rating data of one website (source domain) to help improve the recommendation performance of another website (target domain) is very challenging. To this end, this paper extended the traditional one-dimensional psychometrics model to multidimension. The extended model can effectively capture users' multiple interests. Based on this multidimensional psychometrics model, we further propose a novel transfer learning algorithm. It can effectively transfer users' rating preferences from the source domain to the target domain. Experimental results show that the proposed method can significantly improve the recommendation performance.
A quantitative analysis to identify the key geometric error elements and their coupling is the prerequisite and foundation for improving the precision of machine tools. The purpose of this paper is to identify key geo...
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A quantitative analysis to identify the key geometric error elements and their coupling is the prerequisite and foundation for improving the precision of machine tools. The purpose of this paper is to identify key geometric error elements and compensate for geometric errors accordingly. The geometric error model of three-axis machine tool is built on the basis of multibody system theory;and the quantitative global sensitivity analysis (GSA) model of geometric error elements is constructed by using extended Fourier amplitude sensitivity test method. The crucial geometric errors are identified;and stochastic characteristics of geometric errors are taken into consideration in the formulation of building up the compensation strategy. The validity of geometric error compensation based on sensitivity analysis is verified on a high-precision three-axis machine tool with open CNC system. The experimental results show that the average compensation rates along the X, Y, and Z directions are 59.8%, 65.5%, and 73.5%, respectively. The methods of sensitivity analysis and geometric errors compensation presented in this paper are suitable for identifying the key geometric errors and improving the precision of CNC machine tools effectively.
Bicycle movements are always associated with lateral drifts. However, the impacts of lateral drift behavior, as well as variable lateral clearance maintaining behavior due to the variation of drift intensity, on mixed...
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Bicycle movements are always associated with lateral drifts. However, the impacts of lateral drift behavior, as well as variable lateral clearance maintaining behavior due to the variation of drift intensity, on mixed bicycle flow are not clear. This paper establishes a new cellular automata model to study typical characteristics of mixed bicycle traffic induced by lateral drift and its accompanying behavior. Based on derived positive correlation between passing speed and drift speed through survey, the occurrence probability of lateral drift and the degree of maintained lateral clearance are both introduced in accordance with the variance of passing speed. Then, in whole density region, firm conformity between simulation results and actual survey data is reached, which has seldom been achieved in previous studies. It is further verified that speed distortions in intermediate and high density region induced by assumption of constant lateral clearance requirements can be revised by introducing its variability characteristics. In addition, two contrastive impacts of lateral drift behavior are observed. That is, it causes speed fluctuation in low density while alleviating the speed fluctuation in relatively high density. These results are expected to be helpful to improve the simulation performance of mixed bicycle flow as well as depict more realistic vehicle-bicycle conflicts and so on.
In different fields of science and engineering, a model of a given underlying dynamical system can be obtained by means of measurement data records called time series. This model becomes very important to understand t...
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In different fields of science and engineering, a model of a given underlying dynamical system can be obtained by means of measurement data records called time series. This model becomes very important to understand the original system behaviour and to predict the future values of that system. From the model, parameters such as the prediction horizon can be computed to obtain the point where the prediction becomes useless. In this work, a new parallel kd-tree based approach for computing the prediction horizon is presented. The parallel approach uses the maximal Lyapunov exponent, which is computed by Wolf's method, as an estimator of the prediction horizon.
We discuss long-term dynamical behavior of the solutions for the nonautonomous suspension bridge-type equation in the strong Hilbert space D(A) x H-2(Omega) boolean AND H-0(1)(Omega), where the nonlinearity g(u, t) is...
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We discuss long-term dynamical behavior of the solutions for the nonautonomous suspension bridge-type equation in the strong Hilbert space D(A) x H-2(Omega) boolean AND H-0(1)(Omega), where the nonlinearity g(u, t) is translation compact and the time-dependent external forces h (x,t) only satisfy condition (C*) instead of translation compact. The existence of strong solutions and strong uniform attractors is investigated using a new process scheme. Since the solutions of the nonautonomous suspension bridge-type equation have no higher regularity and the process associated with the solutions is not continuous in the strong Hilbert space, the results are new and appear to be optimal.
Recently the generalized Hyers-Ulam (or Hyers-Ulam-Rassias) stability of the following functional equation Sigma(m)(j=1) f(-r(j)x(j)+Sigma(1 gamma satisfies the above mentioned functional equation then the mapping f ...
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Recently the generalized Hyers-Ulam (or Hyers-Ulam-Rassias) stability of the following functional equation Sigma(m)(j=1) f(-r(j)x(j)+Sigma(1 <= i <= m,i not equal j) r(i)x(i)) + 2 Sigma(m)(i=1) r(i)f(x(i)) = mf (Sigma(m)(i=1) r(i)x(i)) where r(1),...,r(m) is an element of R, proved in Banach modules over a unital C*-algebra. It was shown that if Sigma(m)(i=1) r(i)not equal 0, r(i),r(j)not equal 0 for some 1 <= i < j <= m and a mapping f : X -> gamma satisfies the above mentioned functional equation then the mapping f : X -> gamma is Cauchy additive. In this paper we prove the Hyers-Ulam-Rassias stability of the above mentioned functional equation in random normed spaces (briefly RNS).
A two-dimensional nonlinear plate equation is revisited, which arises from the model of the viscoelastic thin rectangular plate with four edges supported. We establish that the system is exponentially decayed if the m...
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A two-dimensional nonlinear plate equation is revisited, which arises from the model of the viscoelastic thin rectangular plate with four edges supported. We establish that the system is exponentially decayed if the memory kernel satisfies the condition of the exponential decay. Furthermore, we show the existence of the global attractor by verifying the condition (C).
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