基于模型修正技术的模拟集成电路几何规划优化方法

为了兼顾模拟集成电路设计优化的求解精度和计算效率,提出一种基于正项式模型修正技术的几何规划优化方法.首先将模拟集成电路的设计目标与约束简化为正项式模型,然后在采用几何规划方法迭代优化的过程中利用晶体管级SPICE仿真不断修正这一正项式模型.实例表明,与传统基于公式的优化方法和基于仿真的优化方法相比,该方法能够在尽量保证计算效率和全局最优解的前提下使优化精度满足晶体管级SPICE仿真的要求.     

改进的门单元多输入跳变电流源模型

电压信号的非线性问题和多输入跳变现象给时序分析带来了严重挑战.为更好地解决此问题,文中设计电路对门单元输入端和内部节点间的密勒电容进行了验证,从器件结构上分析了其来源,并通过引入该电容改进了已有多输入跳变电流源模型,以获得更高的模型精度;同时将二输入门单元模型扩展到多输入门单元,并详述了建模方法.多种门单元上的数值实验结果表明,与已有模型相比,在可接受的时间开销内,文中模型能够显著地提高门单元时延和输出波形的仿真精度.     

IRS-P6 LISS-3和Landsat-5 TM两种多光谱传感器影像数据的对比分析

随着载有各种新型传感器的卫星相继发射升空,不同传感器之间的相互比较成了一个研究热点。首先从传感器的轨道特征、光谱范围等方面对IRS-P6 LISS-3和Landsat-5 TM进行了机理方面的对比分析,选取3对同日过空的遥感影像,研究了IRS-P6 LISS-3和Landsat-5 TM遥感数据在可见光-近红外、短红外各对应光谱波段之间的关系,建立TM和LISS-3各波段之间的相互转换公式,与Chander等提出的转换公式进行对比分析。结果表明:实际TM和模拟TM多光谱数据之间具有较强的相关关系,决定系数R²均大于0.97;模拟TM与实际TM的水体指数(MNDWI)和归一化植被指数(NDVI)空间散点分布和实际LISS-3与实际TM的空间散点分布相比,具有更强的相关关系,其决定系数R²有一定提高,散点分布趋于对称。因此,所求的关系转换方程具有较高的精度和有效性,效果优于Chander等提出的转换公式。     

改进BP网络在航材需求预测中的应用

针对航材备件需求预测问题,在对影响航材备件需求量的多个因素进行分析研究的基础上,运用改进BP神经网络算法进行预测的仿真实验。实验结果表明,改进BP神经网络能够对积累的历史数据进行充分的应用,并且有较高的预测准确性。     

基于Boost消息机制研究与实现

消息通信机制可以有效的简化系统设计,增强系统的可扩展性。Boost Signal/Slot机制,为在进行消息机制开发提供了有力的工具。以Boost为基础,分析了Boost消息机制的实现方式,通过引入一个简单实例,演示了利用Boost构造消息机制的基本方法。     

水库周边违建问题清查整治中的依法行政与权利救济

针对临近水库的别墅等建筑物的清查整治,在实体层面,尤其对于五证齐全的建筑物,如何定性为违建需要慎重把握,对水库管理范围的界定是一个重点问题;在程序层面,应避免执法中因急于求成而催生的程序违法.强拆行为会产生重大损失,涉及多方主体和多重法律关系,应理清其中各方的法律责任,妥善解决纠纷.     

Simple Question Answering over Knowledge Graph Enhanced by Question Pattern Classification

Knowledge and Information Systems - Question answering over knowledge graph (KGQA), which automatically answers natural language questions by querying the facts in knowledge graph (KG), has drawn...     

A two-stage adaptive multi-fidelity surrogate model-assisted multi-objective genetic algorithm for computationally expensive problems

Surrogate model-assisted multi-objective genetic algorithms (MOGA) show great potential in solving engineering design problems since they can save computational cost by reducing the calls of expensive simulations. In this paper, a two-stage adaptive multi-fidelity surrogate (MFS) model-assisted MOGA (AMFS-MOGA) is developed to further relieve their computational burden. In the warm-up stage, a preliminary Pareto frontier is obtained relying only on the data from the low-fidelity (LF) model. In the second stage, an initial MFS model is constructed based on the data from both LF and high-fidelity (HF) models at the samples, which are selected from the preliminary Pareto set according to the crowding distance in the objective space. Then the fitness values of individuals are evaluated using the MFS model, which is adaptively updated according to two developed strategies, an individual-based updating strategy and a generation-based updating strategy. The former considers the prediction uncertainty from the MFS model, while the latter takes the discrete degree of the population into consideration. The effectiveness and merits of the proposed AMFS-MOGA approach are illustrated using three benchmark tests and the design optimization of a stiffened cylindrical shell. The comparisons between the proposed AMFS-MOGA approach and some existing approaches considering the quality of the obtained Pareto frontiers and computational efficiency are made. The results show that the proposed AMFS-MOGA method can obtain Pareto frontiers comparable to that obtained by the MOGA with HF model, while significantly reducing the number of evaluations of the expensive HF model.

     

Compiler-directed scratchpad memory data transfer optimization for multithreaded applications on a heterogeneous many-core architecture

The Journal of Supercomputing - The heterogeneous many-core architecture plays an important role in the fields of high-performance computing and scientific computing. It uses accelerator cores with...