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排序方式: 共有886条查询结果,搜索用时 31 毫秒
1.
RBF神经元网络在非线性系统建模中的应用   总被引:54,自引:1,他引:53  
本文从径向基函数神经网络的特点着手,分析了该网络存在的问题,并且对网络径向基函数中心的选取,计算以及网络的拓扑结构作了改进,最后用改进的径向基函数神经元网络对化工中的连接搅拌反应釜系统进行建模,结果表明方法有效。  相似文献
2.
基于神经网络的通用软测量技术   总被引:45,自引:0,他引:45       下载免费PDF全文
基于神经网络的通用软测量技术1)王旭东邵惠鹤(上海交通大学自动化研究所上海200030)关键词软测量,RBF神经网络,竞争学习,精馏塔.1)国家自然科学基金资助项目.收稿日期1996-12-031引言目前建立软测量模型有多种方法,但是还缺乏通用性,通...  相似文献
3.
基于生态种群竞争模型的协同进化   总被引:31,自引:0,他引:31       下载免费PDF全文
遗传算法基于适应度的进化模式没有考虑进化的外部环境和进化成分之间的关系,这是协同进化研究的内容.借鉴生态学对个体生存环境和种群竞争的认识,构造了一种基于生态种群竞争模型的新的协同进化模式.模拟实验表明,采用该模式的改进遗传算法在改善未成熟收敛和收敛速度两方面具有良好的性能.  相似文献
4.
Competitive Optimal On-Line Leasing   总被引:30,自引:0,他引:30  
Consider an on-line player who needs some equipment (e.g., a computer) for an initially unknown number of periods. At the start of each period it is determined whether the player will need the equipment during the current period and the player has two options: to pay a leasing fee c and rent the equipment for the period, or to buy it for a larger amount P . The total cost incurred by the player is the sum of all leasing fees and perhaps one purchase. The above problem, called the leasing problem (in computer science folklore it is known as the ski-rental problem), has received considerable attention in the economic literature. Using the competitive ratio as a performance measure this paper is concerned with determining the optimal competitive on-line policy for the leasing problem. For the simplest version of the leasing problem (as described above) it is known and readily derived that the optimal deterministic competitive performance is achieved by leasing for the first k-1 times and then buying, where k = P/c . This strategy pays at most 2-1/k times the optimal off-line cost. When considering alternative financial transactions one must consider their net present value. Thus, accounting for the interest rate is an essential feature of any reasonable financial model. In this paper we determine both deterministic and randomized optimal on-line leasing strategies while accounting for the interest rate factor. It is shown here, for the leasing problem, that the interest rate factor reduces the uncertainty involved. We find that the optimal deterministic competitive ratio is 1 + (1+i)(1-1/k)(1 - k(i/1+i)) , a decreasing function of the interest i (for all reasonable values of i ). For some applications, realistic values of interest rates result in relatively low competitive ratios. By using randomization the on-line player can further boost up the performance. In particular, against an oblivious adversary the on-line player can attain a strictly smaller competitive ratio of 2 - ( (k/(k-1)) γ - 2 )/( (k/(k-1)) γ -1 ) where γ = ln ( 1 - k(1 - 1/(1+i)) ) / ln(1/(1+i)) . Here again, this competitive ratio strictly decreases with i . We also study the leasing problem against a distributional adversary called ``Nature.' This adversary chooses the probability distribution of the number of leasing periods and announces this distribution before the on-line player chooses a strategy. Although at the outset this adversary appears to be weaker than the oblivious adversary, it is shown that the optimal competitive ratio against Nature equals the optimal ratio against the oblivious adversary. Received October 8, 1997; revised February 8, 1998.  相似文献
5.
基于模糊数学的企业综合竞争力评价和实证   总被引:25,自引:0,他引:25  
李存芳  周德群 《控制与决策》2007,22(3):337-340,348
科学地评价企业综合竞争力,关键在于构建企业综合竞争力的评价指标体系。并采取定性与定量相结合的系统评价,基于对企业综合竞争力内涵、要素的分析。构建了评价的指标体系,研究了模糊系统评价的可行性,建立了模糊系统评价的数学模型,并对一大型国有企业的综合竞争力进行了系统评价与实证分析.  相似文献
6.
加权关联规则挖掘算法的研究   总被引:20,自引:0,他引:20  
讨论了加权关联规则的挖掘算法,对布尔型属性,在挖掘算法MINWAL(O)和MINWAL(W)的基础上给出一种改进的加权关联规则挖掘算法,此算法能有效地考虑布尔型属必的重要性和规则中所含属性的个数,对数量型属性,应用竞争聚集算法将数量型属性划分成若干个模糊集,产系统地提出加权模糊关联规则的挖掘算法,此算法能有效地考虑数量型属性的重要性和规则中所含属性的个数,并适用于大型数据库。  相似文献
7.
分布式RBF神经网络及其在软测量方面的应用   总被引:19,自引:1,他引:18  
本文首先改进了竞争学习算法,并且在此基础上提出了递阶聚类的思想,然后利用这种思想得到了一种分布式RBF(Radial basis function)神经网络。文章最后将这种网络应用于建立精馏塔成分估计的软测量模型。利用精馏塔的现场操作数据进行仿真,效果很好。  相似文献
8.
9.
基于独立分量分析的虹膜识别方法   总被引:15,自引:1,他引:14  
虹膜识别技术作为一种生物识别手段,具有惟一性、稳定性和安全性等优点,从而成为当前模式识别和机器学习领域的一个研究热点.提出了一种新的虹膜识别方法,该方法利用独立分量分析(ICA)提取虹膜的纹理特征,并采用竞争学习机制进行识别.实验结果证明了该方法的有效性和对环境的适应性,在图像模糊、噪声干扰等不利条件下,仍然能够正确识别.  相似文献
10.
Optimal Search and One-Way Trading Online Algorithms   总被引:15,自引:0,他引:15  
This paper is concerned with the time series search and one-way trading problems. In the (time series) search problem a player is searching for the maximum (or minimum) price in a sequence that unfolds sequentially, one price at a time. Once during this game the player can decide to accept the current price p in which case the game ends and the player's payoff is p . In the one-way trading problem a trader is given the task of trading dollars to yen. Each day, a new exchange rate is announced and the trader must decide how many dollars to convert to yen according to the current rate. The game ends when the trader trades his entire dollar wealth to yen and his payoff is the number of yen acquired. The search and one-way trading are intimately related. Any (deterministic or randomized) one-way trading algorithm can be viewed as a randomized search algorithm. Using the competitive ratio as a performance measure we determine the optimal competitive performance for several variants of these problems. In particular, we show that a simple threat-based strategy is optimal and we determine its competitive ratio which yields, for realistic values of the problem parameters, surprisingly low competitive ratios. We also consider and analyze a one-way trading game played against an adversary called Nature where the online player knows the probability distribution of the maximum exchange rate and that distribution has been chosen by Nature. Finally, we consider some applications for a special case of portfolio selection called two-way trading in which the trader may trade back and forth between cash and one asset. Received October 19, 1998; revised August 12, 1999.  相似文献
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