高考数列求和的网络题型

2002年高考考试说明明确指出:注重学科的内在联系和知识的综合,从学科整体高度考虑问题,在知识网络交汇点设计试题.

The applying of BP network in forecasting the demand and its growth rate for coal

Based on the statistical data from 1975 to 1997, we forecast the growth rate of coal consuming and the quantity in coming decade with the BP neuron network in the article.

Modeling approaches to pressure balance dynamic system in shield tunneling

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.

Route optimization model for pedestrian evacuation in metro hubs

The route optimization problem for road networks was applied to pedestrian flow.Evacuation path networks with nodes and arcs considering the traffic capacities of facilities were built in metro hubs,and a path impedance function for metro hubs which used the relationships among circulation speed,density and flow rate for pedestrians was defined.Then,a route optimization model which minimizes the movement time of the last evacuee was constructed to optimize evacuation performance.Solutions to the proposed mathematical model were obtained through an iterative optimization process.The route optimization model was applied to Xidan Station of Beijing Metro Line 4 based on the actual situations,and the calculation results of the model were tested using buildingExodus microscopic evacuation simulation software.The simulation result shows that the proposed model shortens the evacuation time by 16.05%,3.15% and 2.78% compared with all or none method,equally split method and Logit model,respectively.Furthermore,when the population gets larger,evacuation efficiency in the proposed model has a greater advantage.

Heterogeneous Quality of Experience Guarantees Over Wireless Networks

Quality of experience(Qo E), which is very critical for the experience of users in wireless networks, has been extensively studied. However, due to different human perceptions, quantifying the effective capacity of wireless network subject to diverse Qo E is very difficult, which leads to many new challenges regarding Qo E guarantees in wireless networks. In this paper, we formulate the Qo E guarantees model for cellular wireless networks. Based on the model, we convert the effective capacity maximization problem into the equivalent convex optimization problem. Then, we develop the optimal Qo E-driven power allocation scheme, which can maximize the effective capacity. The obtained simulation results verified our proposed power allocation scheme, showing that the effective capacity can be significantly increased compared with that of traditional Qo E guarantees based schemes.

A surrogate-based optimization algorithm for network design problems

Network design problems （NDPs） have long been regarded as one of the most challenging problems in the field of transportation planning due to the intrinsic non-convexity of their bi-level programming form. Furthermore, a mixture of continuous/discrete decision variables makes the mixed network design problem （MNDP） more complicated and difficult to solve. We adopt a surrogate-based optimization （SBO） framework to solve three featured categories of NDPs （continuous, discrete, and mixed-integer）. We prove that the method is asymptotically completely convergent when solving continuous NDPs, guaranteeing a global optimum with probability one through an indefinitely long run. To demonstrate the practical performance of the proposed framework, numerical examples are provided to compare SBO with some existing solving algorithms and other heuristics in the literature for NDP. The results show that SBO is one of the best algorithms in terms of both accuracy and efficiency, and it is efficient for solving large-scale problems with more than 20 decision variables. The SBO approach presented in this paper is a general algorithm of solving other optimization problems in the transportation field.

Characteristic model-based consensus of networked heterogeneous robotic manipulators with dynamic uncertainties

In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of multiple robotic agents interconnected on directed graphs containing a spanning tree. A novel characteristic model-based distributed adaptive control scenario is proposed with a state-relied projection estimation law and a characteristic model-based distributed controller. The performance analysis is also unfolded where the uniform ultimate boundedness(UUB) of consensus errors is derived by resorting to the discrete-time-domain stability analysis tool and the graph theory. Finally, numerical simulations illustrate the effectiveness of the proposed theoretical strategy.

Model and Algorithm of Transportation Problem on Network

Transportation problem on network needs to determine the freight quantity and the transportation route between supply point and demand point. Therefore, taken the uncertainty of freight supply and demand into account, a collaborative optimization model is formulated with transportation capacity constraint. In addition, a two-stage genetic algorithm （GA） is put forward. Herein, the first stage of this GA is adopted a priority-based encoding method for determining the supply and demand relationship between different points. Then supply and demand relationship which the supply and the demand are both greater than zero is a minimum cost flow （MCF） problem on network in the second stage. Aim at the purpose to solve MCF problem, a GA is employed. Moreover, this algorithm is suitable for balance and unbalance transportation on directed network or undirected network. At last, the model and algorithm are verified to be efficient by a numerical example.