自动配线法求水文地质参数的优化路径法研究

针对人工配线法求取水文地质参数费时费力,而传统的计算机配线法存在操作不够简便、后台运算次数过多或缺少直观性的不足,该文基于配线法标准曲线与实测曲线基本重合的特点,采用控制点带动所有实测点沿标准曲线移动,寻找离差平方和最小值的优化路径法求到水文地质参数,提出该方法的关键在于控制点的确定,并补充手动配线法来保证计算的准确性。通过算例验证,新方法在满足精度要求的同时,大大提高了运算的速度,具有一定的应用前景。

基于宝鸡青铜器博物院的纹样提取研究

随着文创市场迭代越来越快,文创产品出现了同质化和设计效率低的问题,针对此问题提出了基于宝鸡青铜器博物院的纹样提取研究方法。以青铜器的纹样特点为切入点,采用Potrace交叉熵路径优化法对西周时期较为典型的酒器进行纹样的快速提取,再通过打散重构的方法将纹样符号化转译,最后应用在相关的文创产品中。本文的研究方法既提高了设计者的效率并且设计出的纹样用户满意度较高,说明了该方法的可行性。通过文创产品传播青铜器文化,既加强了宝鸡的城市文化符号也促进了人们对传统文化的了解,起到了传承与推广的作用。

Global optimal path planning for mobile robot based onimproved Dijkstra algorithm and ant system algorithm

A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.

Optimal path planning method of electric vehicles considering power supply

Because of the limitations of electric vehicle(EV)battery technology and relevant supporting facilities,there is a great risk of breakdown of EVs during driving.The resulting driver“range anxiety”greatly affects the travel quality of EVs.These limitations should be overcome to promote the use of EVs.In this study,a method for travel path planning considering EV power supply was developed.First,based on real-time road conditions,a dynamic energy model of EVs was established considering the driving energy and accessory energy.Second,a multi-objective travel path planning model of EVs was constructed considering the power supply,taking the distance,time,energy,and charging cost as the optimization objectives.Finally,taking the actual traffic network of 15 km×15 km area in a city as the research object,the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm.The simulation results show that compared with the traditional route planning method,the total distance in the proposed optimal route planning method increased by 1.18%,but the energy consumption,charging cost,and driving time decreased by 11.62%,41.26%and 11.00%,respectively,thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.

Dynamic services selection algorithm in Web services composition supporting cross-enterprises collaboration

Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services selection)to resolve dynamic Web services selection with QoS global optimal path,was proposed.The essence of the algorithm was that the problem of dynamic Web services selection with QoS global optimal path was transformed into a multi-objective services composition optimization problem with QoS constraints.The operations of the cross and mutation in genetic algorithm were brought into PSOA(particle swarm optimization algorithm),forming an improved algorithm(IPSOA)to solve the QoS global optimal problem.Theoretical analysis and experimental results indicate that the algorithm can better satisfy the time convergence requirement for Web services composition supporting cross-enterprises collaboration than the traditional algorithms.

Numerical study on the spatially varying drag coefficient in simulation of storm surges employing the adjoint method

From the simulation of storm surges resulting from Typhoons 7203 and 8509 in the Bohai Sea, Yellow Sea and East China Sea, water level data at tide stations are assimilated into a two-dimensional storm surge model, to study the spatially varying drag coefficient (DC) by employing the adjoint method. In this study, the DC at some grid points is uniformly selected as the independent DC, while the DC at other grid points is obtained through linear interpolation of the independent DC. The DC at independent points is optimized by employing the adjoint assimilation method, and global optimization is achieved by optimizing the independent DC. To demonstrate the method's performance, three comparative experiments are carried out. In the first experiment, the DC is treated as a constant. In the second and third experiments, the DC is derived using an empirical formula. Comparing the experimental results, it is found that the simulation accuracy for both Typhoons 7203 and 8509 increases greatly when optimizing the independent DC. However, the number of independent points makes no great difference to the precision of simulation. Moreover, the DC inverted from Typhoons 7203 and 8509 differs in some sea areas because of the different typhoon tracks. However, the spatial distribution of the inverted DC, for both Typhoons 7203 and 8509, demonstrates a clear effect of the DC on the storm surge modeling near the coastal areas where the DC is highest or lowest.

Mobile robot path planning method combined improved artificial potential field with optimization algorithm

To overcome the shortcomings of the traditional artificial potential field method in mobile robot path planning, an improved artificial potential field model （IAPFM） was established, then a new path planning method combining the IAPFM with optimization algorithm （trust region algorithm） is proposed. Attractive force between the robot and the target location, and repulsive force between the robot and the obstacles are both converted to the potential field intensity; and filled potential field is used to guide the robot to go out of the local minimum points ; on this basis, the effect of dynamic obstacles velocity and the robot＇s velocity is consid thers and the IAPFM is established, then both the expressions of the attractive potential field and the repulsive potential field are obtained. The trust region algorithm is used to search the minimum value of the sum of all the potential field inten- sities within the movement scope which the robot can arrive in a sampling period. Connecting of all the points which hare the minimum intensity in every sampling period constitutes the global optimization path. Experiment result shows that the method can meet the real-time requirement, and is able to execute the mobile robot path planning task effectively in the dynamic environment.

SVC Video Transmission Optimization Algorithm in Software Defined Network

Scalable video coding(SVC) is a powerful tool to solve the network heterogeneity and terminal diversity in video applications. However, in related works about the optimization of SVC-based video streaming over Software Defined Network(SDN), most of the them are focused either on the number of transmission layers or on the optimization of transmission path for specific layer. In this paper, we propose a noval optimization algorithm for SVC to dynamically adjust the number of layers and optimize the transmission paths simultaneously. We establish the problem model based on the 0/1 knapsack model, and then solve it with Artificial Fish Swarm Algorithm. Additionally, the simulations are carried out on the Mininet platform, which show that our approach can dynamically adjust the number of layers and select the optimal paths at the same time. As a result, it can achieve an effective allocation of network resources which mitigates the congestion and reduces the loss of non-SVC stream.

Optimization of air quantity regulation in mine ventilation networks using the improved differential evolution algorithm and critical path method

In mine ventilation networks, the reasonable airflow distribution is very important for the production safety and economy. Three basic problems of the natural, full-controlled and semi-controlled splitting were reviewed in the paper. Aiming at the high difficulty semi-controlled splitting problem, the general nonlinear multi-objectives optimization mathematical model with constraints was established based on the theory of mine ventilation networks. A new algorithm, which combined the improved differential evaluation and the critical path method （CPM） based on the multivariable separate solution strategy, was put forward to search for the global optimal solution more efficiently. In each step of evolution, the feasible solutions of air quantity distribution are firstly produced by the improved differential evolu- tion algorithm, and then the optimal solutions of regulator pressure drop are obtained by the CPM. Through finite steps iterations, the optimal solution can be given. In this new algorithm, the population of feasible solutions were sorted and grouped for enhancing the global search ability and the individuals in general group were randomly initialized for keeping diversity. Meanwhile, the individual neighbor- hood in the fine group which may be closely to the optimal solutions were searched locally and slightly for achieving a balance between global searching and local searching, thus improving the convergence rate. The computer program was developed based on this method. Finally, the two ventilation networks with single-fan and multi-fans were solved. The results show that this algorithm has advantages of high effectiveness, fast convergence, good robustness and flexibility. This computer program could be used to solve lar^e-scale ~eneralized ventilation networks o^timization problem in the future.

Robot Positioning and Navigation Based on Hybrid Wireless Sensor Network

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.