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梯形区间二型模糊群决策发生算法及其综合比较法
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作者 邵小十 王铁旦 彭定洪 《小型微型计算机系统》 CSCD 北大核心 2018年第6期1328-1334,共7页
针对高度不确定环境下的多准则群体决策问题,提出一种基于梯形区间二型模糊的多重处理隶属函数中模糊不确定信息的群决策综合比较法.首先,利用群决策发生算法处理个体决策的聚合问题;其次,利用改进的重心比较法和区域截集法分别处理隶... 针对高度不确定环境下的多准则群体决策问题,提出一种基于梯形区间二型模糊的多重处理隶属函数中模糊不确定信息的群决策综合比较法.首先,利用群决策发生算法处理个体决策的聚合问题;其次,利用改进的重心比较法和区域截集法分别处理隶属函数中隶属程度问题和模糊不确定程度问题;最后,根据对隶属函数的处理结果得到综合比较计分值并作为方案选择的依据.通过对隶属函数的主隶属区域和模糊不确定的离散区域的双重挖掘,并以不同数量级形式记录在结果中,使得该决策方法更加契合人类决策行为、决策结果更加真实有效、决策风险更小.文末通过实例分析和比较,证明了本文提出方法的可行性和有效性. 展开更多
关键词 梯形区间二型模糊 群决策发生算法 综合比较法 隶属函数 模糊不确定性
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有效的寻找高阶非线性布尔函数的发生算法
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作者 Mulla.,W 汪海明 《密码与信息》 1998年第3期57-66,F003,共11页
我们报告发生算法(GA)据知是首次用于寻找高阶线性布尔函数的结果。表明,使用一种新的生殖程序,这种基本的方法要比使用随机搜索的方法寻找局部具有非常高的非线性度的布尔函数块几个数量级。
关键词 密码 布尔函数 报告发生算法 非线性布尔代数
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计数式TOD跳频码发生器算法的构造 被引量:14
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作者 张申如 梅文华 王庭昌 《电子与信息学报》 EI CSCD 北大核心 2002年第8期1096-1101,共6页
为同步长周期的跳频码序列,必须使用实时时间TOD。一种新的眼光是将跳频码发生算法看作是对TOD这一特殊“信息”序列的“分组加密“变换。单调递增的计数式TOD是目前常用的TOD序列形式,然而,现有的跳频码发生算法并不适应长周期、单调... 为同步长周期的跳频码序列,必须使用实时时间TOD。一种新的眼光是将跳频码发生算法看作是对TOD这一特殊“信息”序列的“分组加密“变换。单调递增的计数式TOD是目前常用的TOD序列形式,然而,现有的跳频码发生算法并不适应长周期、单调递增计数式TOD的使用,该文讨论了分析、改造跳频码序列发生算法使之适合长周期单调递增计数式TOD的需求、又保持良好跳频特性这一重要任务。 展开更多
关键词 跳频通信 发生 实时时间 TOD 跳频序列 发生算法
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改进的机器学习模型在肺结节良恶性分类中的研究 被引量:1
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作者 杨愉 谭雨豪 王丽嘉 《计算机与数字工程》 2024年第7期2227-2232,共6页
肺癌发病率不断上升,借助影像手段快速进行肺结节的早期评估,对提高患者生存质量具有重要意义。针对这个问题,提出了一种新的肺结节良恶性分类模型,该模型首先采用过采样算法消除良性样本比例过高导致的结果偏移现象;然后提取每个结节... 肺癌发病率不断上升,借助影像手段快速进行肺结节的早期评估,对提高患者生存质量具有重要意义。针对这个问题,提出了一种新的肺结节良恶性分类模型,该模型首先采用过采样算法消除良性样本比例过高导致的结果偏移现象;然后提取每个结节的影像组学特征,并结合斯皮尔曼相关性变量剔除以及最小绝对收缩选择算子进行特征筛选,选取最优特征子集;最后采用余弦递减型惯性权重改进随机发生分布式延迟粒子群算法,以精准搜索全局最优参数,建立最佳分类模型。利用LIDC数据库上的608例训练集和68例测试集对模型进行训练和测试。模型在测试集上的AUC、准确率、精确率、召回率分别为0.93、0.941、0.917以及0.971。结果表明该模型能有效分类肺结节,有望在临床上进行肺结节的良恶性辅助诊断。 展开更多
关键词 肺结节 分类 影像组学 过采样 随机发生分布式延迟粒子群算法
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Discussion on Calculation Method of Poverty Incidence in the Exit Evaluation of Poverty-Stricken Counties and Villages 被引量:4
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作者 杨子生 《Agricultural Science & Technology》 CAS 2017年第9期1766-1769,共4页
Poverty incidence is the key index that needs to be measured in the poverty exit examination and evaluation of 832 poverty-stricken counties and 128 000 poverty-stricken villages. In this paper, based on the statement... Poverty incidence is the key index that needs to be measured in the poverty exit examination and evaluation of 832 poverty-stricken counties and 128 000 poverty-stricken villages. In this paper, based on the statement of general concept and conventional calculation method of the poverty incidence, the calculation method of poverty incidence in the exit evaluation of poverty-stricken counties (also including poverty-stricken township and poverty-stricken villages) was investigated through the view of the third-party evaluation. In addition to considering the previous "number of planned poverty remaining population", the method also needed to give consideration to the exiting mistaken population, evaluation missing population. Based on the case in Yuanyang County, Honghe Hani and Yi Autonomous Prefecture, Yunnan Province, the poverty incidences of 10 exit planning villages by the end of 2017 in Yuanyang County were investigated and estimated, and suggestions were proposed to promote the precise poverty alleviation and poverty relief of the county. 展开更多
关键词 Poverty-stricken county EXIT Evaluation Poverty incidence Calculation method
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基于改进组合赋权的岩爆多维云模型预测研究 被引量:29
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作者 黄建 夏元友 吝曼卿 《中国安全科学学报》 CAS CSCD 北大核心 2019年第7期26-32,共7页
岩爆是地下开挖工程主要的地质灾害之一,其烈度分级预测是一个急需解决的世界性难题。针对其预测过程中的不确定性,选取切向应力与岩石单轴抗压强度比σθ/σc、岩石单轴抗压强度与抗拉强度比σc/σt、弹性变形能指数Wet建立评价指标体... 岩爆是地下开挖工程主要的地质灾害之一,其烈度分级预测是一个急需解决的世界性难题。针对其预测过程中的不确定性,选取切向应力与岩石单轴抗压强度比σθ/σc、岩石单轴抗压强度与抗拉强度比σc/σt、弹性变形能指数Wet建立评价指标体系,以改进熵权-基于指标相关性的指标权重确定方法(CRITIC)综合计算预测指标权重,结合不确定性人工智能理论,将逆向云发生器算法用于确立多维云模型的3个数字特征,生成所有预测指标的多维云模型。用国内外48组典型岩爆实例数据检验本文模型的准确性与有效性,并与基于权重融合的云模型、一维正态云模型的预测结果进行对比。结果表明:该模型应用于岩爆预测有更高的准确性。 展开更多
关键词 岩石力学 岩爆预测 多维云模型 熵权 逆向云发生算法 基于指标相关性的指标权重确定方法(CRITIC)
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Optimization and Synthesis of RF CMOS Polyphase Filters with Layout Considerations
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作者 张子三 马向鹏 +1 位作者 Kolnsberg Stephan Kokozinski Rainer 《Journal of Semiconductors》 EI CAS CSCD 北大核心 2004年第12期1612-1617,共6页
A novel software tool for optimization and synthesis of RF CMOS polyhase filters(PPFs),PPFOPTIMA,is developed.In the optimization engine,genetic algorithm is adopted to avoid local optima.Experiments on PPFOPTIMA demo... A novel software tool for optimization and synthesis of RF CMOS polyhase filters(PPFs),PPFOPTIMA,is developed.In the optimization engine,genetic algorithm is adopted to avoid local optima.Experiments on PPFOPTIMA demonstrate that it is an efficient design aid for design and optimization of RF CMOS PPFs. 展开更多
关键词 RF CMOS polyphase filters quadrature signal generation genetic algorithms analog CAD
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On-line Scheduling Algorithm for Penicillin Fed-batch Fermentation
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作者 薛耀锋 袁景淇 《Journal of Donghua University(English Edition)》 EI CAS 2005年第5期43-46,共4页
An on-line scheduling algorithm to maximize gross profit of penicillin fed-batch fermentation is proposed. According to the on-line classification method, fed-batch fermentation batches are classified into three categ... An on-line scheduling algorithm to maximize gross profit of penicillin fed-batch fermentation is proposed. According to the on-line classification method, fed-batch fermentation batches are classified into three categories. Using the scheduling strategy, the optimal termination sequence of batches is obtained. Pseudo on-line simulations for testing the proposed algorithm with the data from industrial scale penicillin fermentation are carried out. 展开更多
关键词 fed-batch process on-line scheduling penicillin fermentation
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基于云模型的基坑支护结构水平变形预测 被引量:3
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作者 陈明洋 《铁道建筑技术》 2021年第7期163-167,共5页
基坑支护结构的水平变形是基坑监测的一个重点,对其准确预测一直是一个急需解决的难题。针对其预测过程中不确定性,首次将云模型理论应用于基坑支护结构水平变形量的预测。利用熵权法确定各评价指标的权重,结合不确定性人工智能理论,通... 基坑支护结构的水平变形是基坑监测的一个重点,对其准确预测一直是一个急需解决的难题。针对其预测过程中不确定性,首次将云模型理论应用于基坑支护结构水平变形量的预测。利用熵权法确定各评价指标的权重,结合不确定性人工智能理论,通过逆向云发生器算法确定云模型的3个数字特征,从而建立云模型。以国内5组工程实例检验模型,预测值与实际值误差最大不超过8.7%,满足实际工程的要求,表明云模型在对基坑支护水平变形的预测中具有良好的实用性和可靠性。 展开更多
关键词 基坑支护结构水平变形 熵权 云模型 逆向云发生算法
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Genetic Algorithm to Optimize the Design of Main Combustor and Gas Generator in Liquid Rocket Engines 被引量:5
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作者 Min Son Sangho Ko Jaye Koo 《Journal of Thermal Science》 SCIE EI CAS CSCD 2014年第3期259-268,共10页
A genetic algorithm was used to develop optimal design methods for the regenerative cooled combustor and fuel-rich gas generator of a liquid rocket engine. For the combustor design, a chemical equilibrium analysis was... A genetic algorithm was used to develop optimal design methods for the regenerative cooled combustor and fuel-rich gas generator of a liquid rocket engine. For the combustor design, a chemical equilibrium analysis was applied, and the profile was calculated using Rao's method. One-dimensional heat transfer was assumed along the profile, and cooling channels were designed. For the gas-generator design, non-equilibrium properties were derived from a counterflow analysis, and a vaporization model for the fuel droplet was adopted to calculate residence time. Finally, a genetic algorithm was adopted to optimize the designs. The combustor and gas generator were optimally designed for 30-tonf, 75-tonf, and 150-tonf engines. The optimized combustors demonstrated superior design characteristics when compared with previous non-optimized results. Wall temperatures at the nozzle throat were optimized to satisfy the requirement of 800 K, and specific impulses were maximized. In addition, the target turbine power and a burned-gas temperature of 1000 K were obtained from the optimized gas-generator design. 展开更多
关键词 Liquid Rocket Engine Main Combustor Gas Generator OPTIMIZATION Genetic Algorithm
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SIGNAL ESTIMATION WITH BINARY-VALUED SENSORS
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作者 Leyi WANG Gang George YIN +1 位作者 Chanying LI Weixing ZHENG 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2010年第3期622-639,共18页
This paper introduces several algorithms for signal estimation using binary-valued outputsensing.The main idea is derived from the empirical measure approach for quantized identification,which has been shown to be con... This paper introduces several algorithms for signal estimation using binary-valued outputsensing.The main idea is derived from the empirical measure approach for quantized identification,which has been shown to be convergent and asymptotically efficient when the unknown parametersare constants.Signal estimation under binary-valued observations must take into consideration oftime varying variables.Typical empirical measure based algorithms are modified with exponentialweighting and threshold adaptation to accommodate time-varying natures of the signals.Without anyinformation on signal generators,the authors establish estimation algorithms,interaction between noisereduction by averaging and signal tracking,convergence rates,and asymptotic efficiency.A thresholdadaptation algorithm is introduced.Its convergence and convergence rates are analyzed by using theODE method for stochastic approximation problems. 展开更多
关键词 IDENTIFICATION signal estimation.
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