基于启发式规则优化的网页元素提取方法

网页信息提取方法中的启发式规则,是识别网页标签信息、利用网页节点分析结果、针对网页不同内容、完成信息提取的重要手段。本研究在对现有启发式规则进行研究分析的基础上,提出了几种优化的启发式规则,实现对网页标题、发布时间、来源以及正文内容等元素信息的精准提取。本研究进一步提出了运用编辑距离算法实现正文内容提取准确率的判定,并提出阙值优化方法,克服了正文提取中噪声节点多、内容识别不完全的缺陷,大大提高了提取的准确度。     

Probabilistic heuristic estimates

Though they constitute the major knowledge source in problem-solving systems, no unified theory of heuristics has emerged. Pearl [15] defines heuristics as criteria, methods, or principles for deciding which among several alternative courses of action promises to be the most effective in order to achieve some goal. The absence of a more precise definition has impeded our efforts to understand, utilize, and discover heuristics. Another consequence is that problem-solving techniques which rely on heuristic knowledge cannot be relied upon to act rationally — in the sense of the normative theory of rationality.To provide a sound basis for BPS, the Bayesian Problem-Solver, we have developed a simple formal theory of heuristics, which is general enough to subsume traditional heuristic functions as well as other forms of problem-solving knowledge, and to straddle disparate problem domains. Probabilistic heuristic estimates represent a probabilistic association of sensations with prior experience — specifically, a mapping from observations directly to subjective probabilities which enables the use of theoretically principled mechanisms for coherent inference and decision making during problem-solving. This paper discusses some of the implications of this theory, and describes its successful application in BPS.This research was made possible by support from Heuristicrats, the National Aeronautics and Space Administration, and the Rand Corporation.     

Heuristic collision-free path planning for an autonomous platform

In this paper, a heuristic and learning, algorithmic scheme for collision-free navigation is presented. This scheme determines an optimum collision-free navigation path of an autonomous platform by using a trial and error process, past navigation knowledge and current information extracted from the generated surrounding environment.     

A heuristic 0–1 integer programming method

Summary In this paper, we present a novel relaxation method for the integer programming problem:Ax=b,A {–1,0,+1}^m×N,x {0,1}^N, N>m. The report includes experimental results of problems with up tom=100 equations andN=400 variables.     

考虑转包的平行机供应链排序

研究一类考虑转包的供应链排序问题, 即工厂从客户处接受一批订单, 这些订单既可以由工厂完成, 也可以通过支付一定费用进行转包. 工厂需要确定被转包的订单集并安排未被转包订单的生产和运输. 针对工厂为平行机生产环境的情况, 以交货期限内完成所有订单的转包成本、生产成本与运输成本之和最小化为目标, 构建了问题的数学模型, 并设计了启发式算法. 最后通过数值实验结果表明了算法的有效性.

     

基于未知环境状态新定义及知识启发的机器人导航Q学习算法

由于强大的自主学习能力, 强化学习方法逐渐成为机器人导航问题的研究热点, 但是复杂的未知环境对算法的运行效率和收敛速度提出了考验。提出一种新的机器人导航Q学习算法, 首先用三个离散的变量来定义环境状态空间, 然后分别设计了两部分奖赏函数, 结合对导航达到目标有利的知识来启发引导机器人的学习过程。实验在Simbad仿真平台上进行, 结果表明本文提出的算法很好地完成了机器人在未知环境中的导航任务, 收敛性能也有其优越性。     

多拓扑路由实现IP网络区分服务的优化算法*

在IP网络使用多拓扑技术对不同业务区分服务和路由优化的背景下,提出一种改进的链路权重优化启发式算法,在一定条件下以一定概率接受非可行解,从而引入松弛机制扩大候选解范围,避免搜索陷入局部最优。在仿真中将所提出的算法和已有算法进行了比较,结果证明该算法能够为每个高优先级需求的服务层协定（SLA）提供保证,有效降低全网总时延或提高网络吞吐量。     

一种求解资源受限项目调度问题的遗传算法

提出一种求解使用可更新资源的单模式资源受限项目调度问题的遗传算法．采用遗传算法对项目活动进行调度,在满足紧前关系约束和资源约束的条件下,最小化项目工期．继承了基于排列和基于优先级的编码方案的优点,提出一种新的基于优先权排列的编码方案．采用串行调度方法生成项目计划．使用PSPLIB中的标准问题库对算法进行了充分的数值实验,通过与既有算法进行比较,证明本文算法的有效性．     

搜索双安全边缘点的实时路径规划方法研究

针对未知不确定性环境下机器人路径规划的特点,提出了基于搜索双安全边缘点的实时路径规划新方法.该方法从有限的实时环境信息中搜索躲避障碍物和保证机器人到达目标点的双安全边缘点信息,并结合启发式算法,实现了基于双安全边缘点的实时路径规划.机器人的实际工作环境是十分复杂的,要求路径规划算法有较高的适应能力,特别在u型环境中要求算法能够脱离死区.仿真实验在2种U型环境和复杂环境中进行,仿真结果表明,该方法具有反应灵敏、实时性好的特点,对不确定环境具有良好的适应性,能够实现未知复杂环境下的路径规划.