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基于模糊层次分析法的应用性技术成果评价 总被引:2,自引:0,他引:2
针对现有应用性技术成果的评价指标体系,建立了相应的模糊层次分析法数学模型,此模型可克服传统层次分析法判断矩阵构造主观性强和一致性不易检验等缺点,为应用性技术成果的等级评价提供了一种简便合理的科学评价方法. 相似文献
64.
为更好地评判操作人员对燃气涡轮发电机组的操作训练,设计了一种虚拟评判系统.根据操作实际,制定了评判标准,建立了评判指标体系.考虑到指标之间的相互影响和反馈关系,解决指标权重分配问题,利用网络分析法(ANP)处理指标间的复杂关系,并采用三角模糊数和模糊优先规划方法(FPP)完成权重的计算,引入云理论确定隶属度,使用蚁群算法优化BP神经网络,结合模糊综合评判构造模糊蚁群神经网络评判模型.上述方法能够有效减少主观因素对权重的影响,弥补传统评判方法的不足.实际应用表明,改进的评判系统具有很强的实用性,是一种可行的评判系统. 相似文献
65.
Fuzzy adaptive networks in machining process modeling: surface roughness prediction for turning operations 总被引:6,自引:0,他引:6
Yue Jiao Shuting Lei Z. J. Pei E. S. Lee 《International Journal of Machine Tools and Manufacture》2004,44(15):1643-1651
Due to the complexity of the machine tool structure and the cutting process, the dynamics of machining processes are still not completely understood. This is especially true due to the demand of high-speed machining to increase productivity. In order to model and control these complex processes, new approaches, which can represent complex phenomenon combined with learning ability, are needed. The combined neural–fuzzy approach appears to be ideally suited for this purpose. In this paper, the recently developed fuzzy adaptive network (FAN) is used to model surface roughness in turning operations. The FAN network has both the learning ability of neural network and linguistic representation of complex, not well-understood, vague phenomenon. Furthermore, it can continuously improve the initially obtained rough model based on the daily operating data. To illustrate this approach, a model representing the influences of machining parameters on surface roughness is established and then the model is verified by the use of the results of pilot experiments. Finally, a comparison with the results based on statistical regression is provided. 相似文献
66.
In recent years, strategy aspects related to core competency, risk analysis and organizational flexibility especially have been growing. This trend has led researchers and industries to become more interested in the multi-criteria decision making (MCDM) models for selecting outsourcing providers. The efficiency of decision-making mostly depends on the ability of decision-makers analyzing the complex cause and effect relationship between criteria and taking effective actions based on the analysis. Using an analytical method to select the most eligible outsourcing provider is significant for a company which desires to improve its competitiveness. In this study, a fuzzy integrated multi-criteria decision making method for evaluation and determination of an outsourcing provider for a telecommunication company is analyzed by using DEMATEL and Fuzzy ANP multi-criteria decision making techniques. First, DEMATEL method is used in order to put forward the interrelationship among the main criteria which are determined in the study for outsourcing selection process. Then, local weights of the sub-criteria and sub-subcriteria are calculated by Fuzzy ANP approach on the basis of cause-effect relationships that are exposed through DEMATEL method. The local weights are put into ANP supermatrix, and calculations are implemented to select out the most eligible outsourcing provider. 相似文献
67.
Smith模糊PID匀速升温控制策略研究 总被引:3,自引:0,他引:3
针对电加热炉匀速升温过程模型建立困难、调节过程滞后等问题,提出了一种基于炉体散热补偿的Smith模糊PID控制算法。通过炉体散热补偿建立针对被控量升温速率的一阶线性纯滞后模型;采用Smith预估器消除纯滞后特性带来的影响,提高系统的稳定性,加快调节过程;引入模糊PID控制,克服Smith预估补偿环节鲁棒性差的弱点,实现参数的自适应调整,并提高了稳态精度,实现了高精度的匀速升温控制。试验结果表明,该控制策略的控制偏差低于5%,明显优于常规PID控制。 相似文献
68.
Optimal representation of acoustic features is an ongoing challenge in automatic speech recognition research. As an initial step toward this purpose, optimization of filterbanks for the cepstral coefficient using evolutionary optimization methods is proposed in some approaches. However, the large number of optimization parameters required by a filterbank makes it difficult to guarantee that an individual optimized filterbank can provide the best representation for phoneme classification. Moreover, in many cases, a number of potential solutions are obtained. Each solution presents discrimination between specific groups of phonemes. In other words, each filterbank has its own particular advantage. Therefore, the aggregation of the discriminative information provided by filterbanks is demanding challenging task. In this study, the optimization of a number of complementary filterbanks is considered to provide a different representation of speech signals for phoneme classification using the hidden Markov model (HMM). Fuzzy information fusion is used to aggregate the decisions provided by HMMs. Fuzzy theory can effectively handle the uncertainties of classifiers trained with different representations of speech data. In this study, the output of the HMM classifiers of each expert is fused using a fuzzy decision fusion scheme. The decision fusion employed a global and local confidence measurement to formulate the reliability of each classifier based on both the global and local context when making overall decisions. Experiments were conducted based on clean and noisy phonetic samples. The proposed method outperformed conventional Mel frequency cepstral coefficients under both conditions in terms of overall phoneme classification accuracy. The fuzzy fusion scheme was shown to be capable of the aggregation of complementary information provided by each filterbank. 相似文献
69.
Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. In real-world applications, transactions may contain quantitative values and each item may have a lifespan from a temporal database. In this paper, we thus propose a data mining algorithm for deriving fuzzy temporal association rules. It first transforms each quantitative value into a fuzzy set using the given membership functions. Meanwhile, item lifespans are collected and recorded in a temporal information table through a transformation process. The algorithm then calculates the scalar cardinality of each linguistic term of each item. A mining process based on fuzzy counts and item lifespans is then performed to find fuzzy temporal association rules. Experiments are finally performed on two simulation datasets and the foodmart dataset to show the effectiveness and the efficiency of the proposed approach. 相似文献
70.
The main aim of this paper is to investigate the group decision making on incomplete multiplicative and fuzzy preference relations without the requirement of satisfying reciprocity property. This paper introduces a new characterization of the multiplicative consistency condition, based on which a method to estimate unknown preference values in an incomplete multiplicative preference relation is proposed. Apart from the multiplicative consistency property among three known preference values, the method proposed also takes the multiplicative consistency property among more than three values into account. In addition, two models for group decision making with incomplete multiplicative preference relations and incomplete fuzzy preference relations are presented, respectively. Some properties of the collective preference relation are further discussed. Numerical examples are provided to make a discussion and comparison with other similar methods. 相似文献