Expediency of this work is conditioned by the inconsistency between the market requirement of the specialists and the planning process of high educational system. For solving this problem it is important to make consu...Expediency of this work is conditioned by the inconsistency between the market requirement of the specialists and the planning process of high educational system. For solving this problem it is important to make consulting or expect system for flexible planning of teaching modules of every specialty. We make an attempt to consider this problem in two aspects: the prediction of market demand for planning taking into consideration of studies duration and scheduling of educational process. The prediction task consists in data acquisition of market requirement for each profession in discrete time interval to predict dynamic evolution of every specialty. The solution of the prediction task will be using to determination of prognostic quantity of students for each specialty. As regards the second aspect, it consists in finding a schedule of the teaching modules, i.e. the distribution of subjects in the semesters, keeping the total limits of credits, to update and adapt syllabus. In this paper, we present a genetic algorithm as a solution method for the modular scheduling problem. Genetic algorithms (GAs) allow a more general approach to the scheduling problem, which is rated using a fitness function. GA can be successfully applied to find optimized sequential schedules.展开更多
In order to deal with modeling problem of a pressure balance system with time-delay, nonlinear, time-varying and uncertain characteristics, an intelligent modeling procedure is proposed, which is based on artificial n...In order to deal with modeling problem of a pressure balance system with time-delay, nonlinear, time-varying and uncertain characteristics, an intelligent modeling procedure is proposed, which is based on artificial neural network(ANN) and input-output data of the system during shield tunneling and can overcome the precision problem in mechanistic modeling(MM) approach. The computational results show that the training algorithm with Gauss-Newton optimization has fast convergent speed. The experimental investigation indicates that, compared with mechanistic modeling approach, intelligent modeling procedure can obviously increase the precision in both soil pressure fitting and forecasting period. The effectiveness and accuracy of proposed intelligent modeling procedure are verified in laboratory tests.展开更多
In this paper, we address an open problem raised by Levy(2009) regarding the design of a binary minimax test without the symmetry assumption on the nominal conditional probability densities of observations. In the bin...In this paper, we address an open problem raised by Levy(2009) regarding the design of a binary minimax test without the symmetry assumption on the nominal conditional probability densities of observations. In the binary minimax test, the nominal likelihood ratio is a monotonically increasing function and the probability densities of the observations are located in neighborhoods characterized by placing a bound on the relative entropy between the actual and nominal densities. The general minimax testing problem at hand is an infinite-dimensional optimization problem, which is quite difficult to solve. In this paper, we prove that the complicated minimax testing problem can be substantially reduced to solve a nonlinear system of two equations having only two unknown variables, which provides an efficient numerical solution.展开更多
This paper considers dynamical systems under feedback with control actions limited toswitching.The authors wish to understand the closed-loop systems as approximating multi-scale problemsin which the implementation of...This paper considers dynamical systems under feedback with control actions limited toswitching.The authors wish to understand the closed-loop systems as approximating multi-scale problemsin which the implementation of switching merely acts on a fast scale.Such hybrid dynamicalsystems are extensively studied in the literature,but not much so far for feedback with partial stateobservation.This becomes in particular relevant when the dynamical systems are governed by partialdifferential equations.The authors introduce an augmented BV setting which permits recognition ofcertain fast scale effects and give a corresponding well-posedness result for observations with such minimalregularity.As an application for this setting,the authors show existence of solutions for systemsof semilinear hyperbolic equations under such feedback with pointwise observations.展开更多
文摘Expediency of this work is conditioned by the inconsistency between the market requirement of the specialists and the planning process of high educational system. For solving this problem it is important to make consulting or expect system for flexible planning of teaching modules of every specialty. We make an attempt to consider this problem in two aspects: the prediction of market demand for planning taking into consideration of studies duration and scheduling of educational process. The prediction task consists in data acquisition of market requirement for each profession in discrete time interval to predict dynamic evolution of every specialty. The solution of the prediction task will be using to determination of prognostic quantity of students for each specialty. As regards the second aspect, it consists in finding a schedule of the teaching modules, i.e. the distribution of subjects in the semesters, keeping the total limits of credits, to update and adapt syllabus. In this paper, we present a genetic algorithm as a solution method for the modular scheduling problem. Genetic algorithms (GAs) allow a more general approach to the scheduling problem, which is rated using a fitness function. GA can be successfully applied to find optimized sequential schedules.
基金Project(2013CB035402) supported by the National Basic Research Program of ChinaProjects(51105048,51209028) supported by the National Natural Science Foundation of China
文摘In order to deal with modeling problem of a pressure balance system with time-delay, nonlinear, time-varying and uncertain characteristics, an intelligent modeling procedure is proposed, which is based on artificial neural network(ANN) and input-output data of the system during shield tunneling and can overcome the precision problem in mechanistic modeling(MM) approach. The computational results show that the training algorithm with Gauss-Newton optimization has fast convergent speed. The experimental investigation indicates that, compared with mechanistic modeling approach, intelligent modeling procedure can obviously increase the precision in both soil pressure fitting and forecasting period. The effectiveness and accuracy of proposed intelligent modeling procedure are verified in laboratory tests.
基金supported by National Natural Science Foundation of China(Grant Nos.61473197,61671411 and 61273074)Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT 16R53)Program for Thousand Talents(Grant Nos.2082204194120 and 0082204151008)
文摘In this paper, we address an open problem raised by Levy(2009) regarding the design of a binary minimax test without the symmetry assumption on the nominal conditional probability densities of observations. In the binary minimax test, the nominal likelihood ratio is a monotonically increasing function and the probability densities of the observations are located in neighborhoods characterized by placing a bound on the relative entropy between the actual and nominal densities. The general minimax testing problem at hand is an infinite-dimensional optimization problem, which is quite difficult to solve. In this paper, we prove that the complicated minimax testing problem can be substantially reduced to solve a nonlinear system of two equations having only two unknown variables, which provides an efficient numerical solution.
基金support of the Elite Network of Bavaria under the grant #K-NW-2004-143
文摘This paper considers dynamical systems under feedback with control actions limited toswitching.The authors wish to understand the closed-loop systems as approximating multi-scale problemsin which the implementation of switching merely acts on a fast scale.Such hybrid dynamicalsystems are extensively studied in the literature,but not much so far for feedback with partial stateobservation.This becomes in particular relevant when the dynamical systems are governed by partialdifferential equations.The authors introduce an augmented BV setting which permits recognition ofcertain fast scale effects and give a corresponding well-posedness result for observations with such minimalregularity.As an application for this setting,the authors show existence of solutions for systemsof semilinear hyperbolic equations under such feedback with pointwise observations.