基于替换的组合电路的等价性检验方法

介绍了基于替换的组合电路的等价性检验算法，利用待检验的两个电路的结构相似性来逐步约简电路，从而加速了验证过程。     

Incorporation of Perception-based Information in Robot Learning Using Fuzzy Reinforcement Learning Agents

Robot learning in unstructured environments has been proved to be an extremely challenging problem, mainly because of many uncertainties always present in the real world. Human beings, on the other hand, seem to cope very well with uncertain and unpredictable environments, often relying on perception-based information. Furthermore, humans beings can also utilize perceptions to guide their learning on those parts of the perception-action space that are actually relevant to the task. Therefore, we conduct a research aimed at improving robot learning through the incorporation of both perceptionbased and measurement-based information. For this reason, a fuzzy reinforcement learning (FRL) agent is proposed in this paper. Based on a neural-fuzzy architecture, different kinds of information can be incorporated into the FRL agent to initialise its action network, critic network and evaluation feedback module so as to accelerate its learning. By making use of the global optimisation capability of GAs (genetic algorithms), a GA-based FRL (GAFRL) agent is presented to solve the local minima problem in traditional actor-critic reinforcement learning. On the other hand, with the prediction capability of the critic network, GAs can perform a more effective global search. Different GAFRL agents are constructed and verified by using the simulation model of a physical biped robot. The simulation analysis shows that the biped learning rate for dynamic balance can be improved by incorporating perception-based information on biped balancing and walking evaluation. The biped robot can find its application in ocean exploration, detection or sea rescue activity, as well as military maritimeac tivity.     

GPS整周模糊度搜索算法的可靠性和时效性比较

研究了GPS载波相位快速静态定位中的整周模糊度搜索算法,对实数编码的改进遗传算法和LAMBDA算法进行了对比分析.算例表明:实数编码的遗传算法在搜索效率和可靠性方面和LAMBDA算法相当.     

A high precision comprehensive evaluation method for flood disaster loss based on improved genetic programming

Precise comprehensive evaluation of flood disaster loss is significant for the prevention and mitigation of flood disasters. Here, one of the difficulties involved is how to establish a model capable of describing the complex relation between the input and output data of the system of flood disaster loss. Genetic programming （GP） solves problems by using ideas from genetic algorithm and generates computer programs automatically. In this study a new method named the evaluation of the grade of flood disaster loss （EGFD） on the basis of improved genetic programming （IGP） is presented （IGP-EGFD）. The flood disaster area and the direct economic loss are taken as the evaluation indexes of flood disaster loss. Obviously that the larger the evaluation index value, the larger the corresponding value of the grade of flood disaster loss is. Consequently the IGP code is designed to make the value of the grade of flood disaster be an increasing function of the index value. The result of the application of the IGP-EGFD model to Henan Province shows that a good function expression can be obtained within a bigger searched function space; and the model is of high precision and considerable practical significance. Thus, IGP-EGFD can be widely used in automatic modeling and other evaluation systems.     

第三次全国国土调查坡度图制作关键技术研究——以A地区为例

栅格数据矢量化、图斑融合、数据拼接、图斑边界处理等关键技术是坡度图制作的关键,也是第三次全国国土调查数据处理的难点.遗传算法可以对国土调查坡度图制作的关键技术进行优化,提高图形制作的效率和精准度.文章利用遗传算法对国土调查坡度图的数据进行优化,最终成果达到国土调查的预期目的.     

GA-BP网络模型在GPS似大地水准面精化中的应用

针对误差反向传播（BP）算法训练速度慢和易于陷入局部最小值的缺点,提出了利用遗传算法（GA）的全局寻优性,结合GA和BP的各自优点,分析和建立了进化神经网络（GA-BP）模型,并将该模型应用于似大地水准面模型精化。最后以南方某市E级GPS控制网高程数据为例,进行BP和GA-BP模型的对比实验,通过对内、外符合精度及MAPE（平均绝对误差百分比）指标分析,验证了该方法的可行性。     

用遗传算法对自动控制系统数学模型寻优

探讨用遗传算法对数学模型进行优化。考虑到控制系统稳健性的要求 ,用遗传算法寻找出控制系统最佳稳定域 ,实现控制系统数学模型的寻优。阐述了用遗传算法求解问题的步骤和参数的取值 ,并用仿真实验对优化结果进行了检验。结果表明 :在控制系统数学模型的优化中 ,遗传算法具有其他算法无可比拟的优越性。     

基于遗传算法的瞬变电磁法线圈阵列优化设计

为解决瞬变电磁检测技术遇到地底干扰物时在探测精度方面的不足,从载流直导线出发,利用磁场矢量叠加原理,计算单个正三角形空间磁场分布,设计了一种正三角形发射线圈阵列。为得到更好的磁聚焦特性,利用遗传算法对线圈阵列的具体参数进行优化。仿真结果表明:87.5%及以上的磁场能量集中在半径0.113m的特定区域内。说明该线圈阵列在较小目标区域实现了聚焦,具有良好的聚焦性,可以应用在瞬变电磁检测技术发射回线中。     

基于性能的结构抗风设计理论框架

提出了基于性能的结构抗风设计理论框架,将风压强度划分为4个设计风压等级（弱风压、中风压、强风压及超强风压）,将人体振动舒适度划分为6个等级（无振感、轻微振感、中等振感、烦恼、非常烦恼和无法忍受）、三种振动水平（与人的舒适感相关的振动水平、与人正常工作和操作有关的振动水平、与人的生理健康直接相关的振动水平）。结合不同类别建筑物的性能需求及人体振动舒适度的要求,将结构风振性能水准划分为4种状态（性能健康、性能亚健康、性能病态及性能丧失）,将结构风振性能目标划分为5个等级（A、B、C、D、E）。提出了结构抗风概念设计与计算分析的一般原则,给出了结构性能抗风安全性评价及社会经济评价基本内容的建议。     

用遗传算法解算病态方程

对应用遗传算法解决病态方程问题进行了探讨。利用拟合法而不是通过法方程求解参数，从而避免了法方程系数求逆，使病态方程的解答有了较好的结果。通过模拟计算并和其他方法进行比较，证明该方法是可行的和有效的。