This article investigates the influence of the property of VGO derived from the Kazakhstan- Russian mixed crude on the hydrocracking catalyst. The influence of reaction temperature, reaction pressure, space velocity a...This article investigates the influence of the property of VGO derived from the Kazakhstan- Russian mixed crude on the hydrocracking catalyst. The influence of reaction temperature, reaction pressure, space velocity and hydrogen/oil ratio on the distribution and quality of products was analyzed with the optimal process regime determined, when the VGO was hydrocracked in the presence of the FC-16 catalyst.展开更多
Traditional sensor network and robot navigation are based on the map of detecting the fields available in advance. The optimal algorithms are developed to solve the energy saving, the shortest path problems, etc. Howe...Traditional sensor network and robot navigation are based on the map of detecting the fields available in advance. The optimal algorithms are developed to solve the energy saving, the shortest path problems, etc. However, in the practical enviroranent, there are many fields, whose map is difficult to get, and needs to be detected. In this paper a kind of ad-hoc navigation algorithm is explored, which is based on the hybrid sensor network without the prior map in advance. The navigation system is composed of static nodes and dynamic trades. The static nodes monitor the occurrances of the events and broadcast them. In the syston, a kind of algorithm is to locate the rdbot, which is based on duster broadcasting. The dynamic nodes detect the adversary or dangerous fields and broadcast warning messages. The robot gets the message and follows ad-hoc routine to arrive where the events occur. In the whole process, energy saving has been taken into account. The algorithms, which are based on the hybrid sensor network, are given in this paper. The simulation and practical results are also available.展开更多
For unconstrained optimization, a new hybrid projection algorithm is presented m the paper. This algorithm has some attractive convergence properties. Convergence theory can be obtained under the condition that Δ↓f...For unconstrained optimization, a new hybrid projection algorithm is presented m the paper. This algorithm has some attractive convergence properties. Convergence theory can be obtained under the condition that Δ↓f（x） is uniformly continuous. If Δ↓f（x） is continuously differentiable pseudo-convex, the whole sequence of iterates converges to a solution of the problem without any other assumptions. Furthermore, under appropriate conditions one shows that the sequence of iterates has a cluster-point if and only if Ω＊ ≠ θ. Numerical examples are given at the end of this paper.展开更多
In this paper, a new class of memoryless non-quasi-Newton method for solving unconstrained optimization problems is proposed, and the global convergence of this method with inexact line search is proved. Furthermore, ...In this paper, a new class of memoryless non-quasi-Newton method for solving unconstrained optimization problems is proposed, and the global convergence of this method with inexact line search is proved. Furthermore, we propose a hybrid method that mixes both the memoryless non-quasi-Newton method and the memoryless Perry-Shanno quasi-Newton method. The global convergence of this hybrid memoryless method is proved under mild assumptions. The initial results show that these new methods are efficient for the given test problems. Especially the memoryless non-quasi-Newton method requires little storage and computation, so it is able to efficiently solve large scale optimization problems.展开更多
文摘This article investigates the influence of the property of VGO derived from the Kazakhstan- Russian mixed crude on the hydrocracking catalyst. The influence of reaction temperature, reaction pressure, space velocity and hydrogen/oil ratio on the distribution and quality of products was analyzed with the optimal process regime determined, when the VGO was hydrocracked in the presence of the FC-16 catalyst.
基金supported by the National nature Science Fund(No.50875247)
文摘Traditional sensor network and robot navigation are based on the map of detecting the fields available in advance. The optimal algorithms are developed to solve the energy saving, the shortest path problems, etc. However, in the practical enviroranent, there are many fields, whose map is difficult to get, and needs to be detected. In this paper a kind of ad-hoc navigation algorithm is explored, which is based on the hybrid sensor network without the prior map in advance. The navigation system is composed of static nodes and dynamic trades. The static nodes monitor the occurrances of the events and broadcast them. In the syston, a kind of algorithm is to locate the rdbot, which is based on duster broadcasting. The dynamic nodes detect the adversary or dangerous fields and broadcast warning messages. The robot gets the message and follows ad-hoc routine to arrive where the events occur. In the whole process, energy saving has been taken into account. The algorithms, which are based on the hybrid sensor network, are given in this paper. The simulation and practical results are also available.
基金This work is supported by National Natural Science Foundation under Grants No. 10571106 and 10471159.
文摘For unconstrained optimization, a new hybrid projection algorithm is presented m the paper. This algorithm has some attractive convergence properties. Convergence theory can be obtained under the condition that Δ↓f（x） is uniformly continuous. If Δ↓f（x） is continuously differentiable pseudo-convex, the whole sequence of iterates converges to a solution of the problem without any other assumptions. Furthermore, under appropriate conditions one shows that the sequence of iterates has a cluster-point if and only if Ω＊ ≠ θ. Numerical examples are given at the end of this paper.
基金Foundation item： the National Natural Science Foundation of China （No. 60472071） the Science Foundation of Beijing Municipal Commission of Education （No. KM200710028001）.
文摘In this paper, a new class of memoryless non-quasi-Newton method for solving unconstrained optimization problems is proposed, and the global convergence of this method with inexact line search is proved. Furthermore, we propose a hybrid method that mixes both the memoryless non-quasi-Newton method and the memoryless Perry-Shanno quasi-Newton method. The global convergence of this hybrid memoryless method is proved under mild assumptions. The initial results show that these new methods are efficient for the given test problems. Especially the memoryless non-quasi-Newton method requires little storage and computation, so it is able to efficiently solve large scale optimization problems.
