基于改进粒子群优化算法的鲁棒性列车运行图编制方法

以列车优先级、追踪运行间隔时间和连发间隔时间限制为约束条件,以旅客列车的走行公里总数、平均旅行速度、对标准计划的延迟总时间和延迟时间方差,以及货物列车的日车公里总数和日产量6个指标无量纲转化后的合计值最大为综合目标函数,建立列车运行图编制优化模型。为增加列车运行图的鲁棒性,引入虚拟车和缓冲时间槽2个参数,采用改进的粒子群优化算法给出鲁棒性列车运行图编制方法。以5个车站、5列旅客列车和7列货物列车构造模拟环境,采用该方法进行列车运行图编制模拟。结果表明:该方法可铺画出更优的列车运行图,计算效率高;在行车计划受到扰动后,虚拟车和缓冲时间槽释放资源,运行图可以较快地恢复到可接受范围,容错鲁棒性好。

火电机组年合同电量的编制与分解算法研究

在传统调度、完全市场、限量竞价三种模式下,提出了火电机组年合同电量的编制与分解算法。算法从兼顾电网调度公平性和经济性的角度出发,以发电-负荷平衡、最大/最小发电量、机组检修计划等条件为约束,对火电机组的年合同电量进行编制和分解。算法通过调整各种模式下交易电量的市场份额以适应市场交易机制的变化,并对不同机制下的年合同电量提出了相应不同的编制与分解算法,具有较强的适用性和适度的前瞻性。某地方电网算例验证了该算法的实用性和有效性。

基于自适应遗传算法的城际列车运行图编制方法

对城际列车运行图编制问题进行研究,确定列车在各区间运行的最优顺序,并建立以列车总运行时间最小为目标的列车运行图优化模型。在此基础上,采用自适应选择机制的变异算子和交叉算子,设计一种自适应遗传算法进行求解。该算法采用"列车-区间运行顺序"的染色体二维编码形式,首先对列车在各区间运行的顺序进行编码;求解过程中,结合广度优先循环布线的原则进行解码,通过"到发时刻-发现冲突-解决冲突"逐区段进行铺画,得到列车在各车站实际的到发时刻;同时,利用自适应遗传算法进行全局优化,得到问题最优解。实验表明,自适应机制能够提高算法性能并较快得到列车最优运行顺序,铺画出更高效准确的列车运行图。

二维最优搜索算法在板材下料中的应用

如何提高产品的质量、降低物资清耗,增强产品的市场竞争能力,是国家和企业最为关心的问题。根据最优化理论,采用二维最优搜索算法编制的“板材下料最优自动编排“软件,极大的提高了板材的利用率,降低了产品成本、收到了明显的经济效益和社会效益。被国家计委列为全国节材重点推广项目,被吉林省机械电子厅列为双增双节活动重点项目之一。一、板材下料的最优化问题最优化技术就是研究和解决最优化问题的一门学科。它研究和解决如何在一切可能的方案中寻求最优的方案。具体说来就是解决以下两大问题:一是如何将最优化问题表示成数学模型,二是如何根据数学模强。

车载LiDAR数据道路建模研究

构建道路模型是建设三维数字城市最重要的工作之一。根据道路点云在车载激光点云中的表现特征,提出了一种新的道路建模方法:首先插入辅助截面,将散乱的道路点云投影至临近辅助截面;然后对投影的点进行重采样,使散乱的点云成为有序的数据处理单位;最后构建三角网,获得道路模型。

Multi-path planning algorithm based on fitness sharing and species evolution

A new algorithm is proposed for underwater vehicles multi-path planning. This algorithm is based on fitness sharing genetic algorithm, clustering and evolution of multiple populations, which can keep the diversity of the solution path, and decrease the operating time because of the independent evolution of each subpopulation. The multi-path planning algorithm is demonstrated by a number of two-dimensional path planning problems. The results show that the multi-path planning algorithm has the following characteristics: high searching capability, rapid convergence and high reliability.

Geospacial information utilized under the access control strategy

This paper introduces a solution to the secure requirement for digital rights management （DRM） by the way of geospacial access control named geospacial access control （GeoAC） in geospacial field. The issues of authorization for geospacial DRM are concentrated on. To geospacial DRM, one aspect is the declaration and enforcement of access rights, based on geographic aspects. To the approbation of digital geographic content, it is important to adopt online access to geodata through a special data infrastructure （SDI）. This results in the interoperability requirements on three different levels： data model level, service level and access control level. The interaction between the data model and service level can be obtained by criterions of the open geospacial consortium （OGC）, and the interaction of the access control level may be reached by declaring and enforcing access restrictions in GeoAC. Then an archetype enforcement based on GeoAC is elucidated. As one aspect of performing usage rights, the execution of access restrictions as an extension to a regular SDI is illuminated.

Dynamic formation control for autonomous underwater vehicles

Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which several algorithms were developed for the complex underwater environment.Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes.Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles.Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation.The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated.Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness,even with a concave obstacle.It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.

Network coding resources optimization with transmission delay constraint in multicast networks

Minimizing network coding resources of multicast networks,such as the number of coding nodes or links,has been proved to be NP-hard,and taking propagation delay into account makes the problem more complicated. To resolve this optimal problem,an integer encoding routing-based genetic algorithm( REGA) is presented to map the optimization problem into a genetic algorithm( GA)framework. Moreover,to speed up the search process of the algorithm,an efficient local search procedure which can reduce the searching space size is designed for searching the feasible solution.Compared with the binary link state encoding representation genetic algorithm( BLSGA),the chromosome length of REGA is shorter and just depends on the number of sinks. Simulation results show the advantages of the algorithm in terms of getting the optimal solution and algorithmic convergence speed.

Complexity scalable control algorithm for intra coding in H.264 under energy constraints

In this paper, the complexity of intra coding is first analyzed so as to achieve a weight of complexity measurement for each intra mode. Then, a new complexity scalable control algorithm for intra coding in H. 264 is proposed, based on the rearrangement of the order of candidate modes and an efficient complexity allocation and control （CAAC） scheme at the macroblock （MB） level. The candidate modes of each MB are rearranged according to the local-edge information. Experimental results show that our proposed algorithm can make an appropriate cut-off point of the candidate modes sequence adaptively according to the current energy condition of a mobile device, so as to adjust the complexity at any level while maximizing the video quality, which can prolong the operational lifetime of the battery with minimum degradation in video quality.

Algorithms for semi on-line multiprocessor scheduling problems

In the classical multiprocessor scheduling problems, it is assumed that the problems are considered in off\|line or on\|line environment. But in practice, problems are often not really off\|line or on\|line but somehow in between. This means that, with respect to the on\|line problem, some further information about the tasks is available, which allows the improvement of the performance of the best possible algorithms. Problems of this class are called semi on\|line ones. The authors studied two semi on\|line multiprocessor scheduling problems, in which, the total processing time of all tasks is known in advance, or all processing times lie in a given interval. They proposed approximation algorithms for minimizing the makespan and analyzed their performance guarantee. The algorithms improve the known results for 3 or more processor cases in the literature.

Multi-boid Flocking with Formation Control Using Local Sensing and Communication

Behavior-based flocking has got remarkable attention in the recent past. The flocking algorithms can have inherent properties like organizing,healing and re-configuring for a distributed system. In this research we presented the emergent flocking behavior-based control. We defined the basis behavior and with variety of combination, and obtained a complex group behavior flocking. Unlike classical flocking, we implemented additional rules obstacle avoidance,formation and seek target which results in V-formation flocking while avoiding obstacles. We performed the visual simulation of our flocking algorithm using MATLAB. The results concluded that the multi-boid flock could successfully navigate to the target while avoiding collisions. This can be applied to areas where we need to maximize the coverage of sensors or minimize the risk of combative attack,both in military and civilian scenarios.

A novel dynamic frame rate control algorithm for H.264 low-bit-rate video coding

The goal of this paper is to improve human visual perceptual quality as well as coding efficiency of H. 264 video at low bit rate conditions by adaptively adjusting the number of skipped frames. The encoding frames are selected according to the motion activity of each frame and the motion accumulation of successive frames. The motion activity analysis is based on the statistics of motion vectors and with consider- ation of the characteristics of H. 264 coding standard. A prediction model of motion accumulation is pro- posed to reduce complex computation of motion estimation. The dynamic encoding frame rate control algorithm is applied to both the frame level and the GOB （Group of Macroblocks ） level. Simulation is done to compare the performance of JM76 with the proposed frame level scheme and GOB level scheme.

A New Approximation to the Jacobian Logarithm Suitable for MAP Decoding in BICM-ID

In this paper, a new method to approximate the compensation term in the Jacobian logarithm used by the MAP decoder is proposed. Using the proposed approximation, the complex functions In（.） and exp（.） in the Exact-log-MAP algorithm can be estimated with high accuracy and lower computational complexity. The efficacy of the proposed approximation is investigated and demonstrated by applying it to iteratively decoded BICM （Bit Interleaved Coded Modulation）.

A novel mapping scheme and modified decoding algorithm for BICM-ID

This paper proposes a novel mapping scheme for bit-interleaved coded modulation with iterative decoding(BICM-ID).The symbol mapping is composed of two QPSK with different radiuses and phases,called cross equalization-8PSK-quasi-semi set partitioning(CE-8PSK-Quasi-SSP).Providing the same average power,the proposed scheme can increase the minimum squared Euclidean distance(MSED)and then improve the receiving performance of BICM-ID compared with conventional symbol mapping schemes.Simultaneously,a modified iteration decoding algorithm is proposed in this paper.In the process of iteration decoding,different proportion of the extrinsic information to the systematic observations results in distinct decoding performance.At high SNR(4~9dB),the observation information plays a more important role than the extrinsic information.Simulation results show that the proportion set at 1.2 is more suitable for the novel mapping in BICM-ID.When the BER is 10^(-4),more than 0.9dB coding gain over Rayleigh channels can be achieved for the improved mapping and decoding scheme.

A New Quantum Gray-Scale Image Encoding Scheme

In this paper, a new quantum images encoding scheme is proposed. The proposed scheme mainly consists of four different encoding algorithms. The idea behind of the scheme is a binary key generated randomly for each pixel of the original image. Afterwards, the employed encoding algorithm is selected corresponding to the qubit pair of the generated randomized binary key. The security analysis of the proposed scheme proved its enhancement through both randomization of the generated binary image key and altering the gray-scale value of the image pixels using the qubits of randomized binary key. The simulation of the proposed scheme assures that the final encoded image could not be recognized visually. Moreover, the histogram diagram of encoded image is flatter than the originM one. The Shannon entropies of the final encoded images are significantly higher than the original one, which indicates that the attacker can not gain any information about the encoded images.