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11.
Electrocardiogram is the most commonly used tool for the diagnosis of cardiologic diseases. In order to help cardiologists to diagnose the arrhythmias automatically, new methods for automated, computer aided ECG analysis are being developed. In this paper, a Modified Artificial Bee Colony (MABC) algorithm for ECG heart beat classification is introduced. It is applied to ECG data set which is obtained from MITBIH database and the result of MABC is compared with seventeen other classifier's accuracy.In classification problem, some features have higher distinctiveness than others. In this study, in order to find higher distinctive features, a detailed analysis has been done on time domain features. By using the right features in MABC algorithm, high classification success rate (99.30%) is obtained. Other methods generally have high classification accuracy on examined data set, but they have relatively low or even poor sensitivities for some beat types. Different data sets, unbalanced sample numbers in different classes have effect on classification result. When a balanced data set is used, MABC provided the best result as 97.96% among all classifiers.Not only part of the records from examined MITBIH database, but also all data from selected records are used to be able to use developed algorithm on a real time system in the future by using additional software modules and making adaptation on a specific hardware. 相似文献
12.
This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning
of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed
Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given
visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample
size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive
experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr
and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood
(ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given
sparse data, while CL-AIC should be chosen given moderate or large data sample sizes. 相似文献
13.
In this paper, a new approach for fault detection and isolation that is based on the possibilistic clustering algorithm is proposed. Fault detection and isolation (FDI) is shown here to be a pattern classification problem, which can be solved using clustering and classification techniques. A possibilistic clustering based approach is proposed here to address some of the shortcomings of the fuzzy c-means (FCM) algorithm. The probabilistic constraint imposed on the membership value in the FCM algorithm is relaxed in the possibilistic clustering algorithm. Because of this relaxation, the possibilistic approach is shown in this paper to give more consistent results in the context of the FDI tasks. The possibilistic clustering approach has also been used to detect novel fault scenarios, for which the data was not available while training. Fault signatures that change as a function of the fault intensities are represented as fault lines, which have been shown to be useful to classify faults that can manifest with different intensities. The proposed approach has been validated here through simulations involving a benchmark quadruple tank process and also through experimental case studies on the same setup. For large scale systems, it is proposed to use the possibilistic clustering based approach in the lower dimensional approximations generated by algorithms such as PCA. Towards this end, finally, we also demonstrate the key merits of the algorithm for plant wide monitoring study using a simulation of the benchmark Tennessee Eastman problem. 相似文献
14.
An Improved Immune Genetic Algorithm for Solving the Optimization Problems of Computer Communication Networks 总被引:4,自引:0,他引:4
1 IntroductionIndesigningacomputercommunicationnet work ,thenetworkaveragedelayisanimportantpa rameterinthenetworkperformance .Inthispaper,weonlyconsiderM /M/1networks,whichmeansthatthemessageprocessingtimeisaprobabilisticdensityfunctionwithnegativepower,thegroupar rivalandsendingisofPoissiondistributionwithasinglequeue .Supposethatthenetworktopologicalstructureandtheestimatesoftheexternaltrafficrequirementsaregiven ,howtoselecttheoptimalroutestobeusedbythecommunicatingnodesinthenetworksoast… 相似文献
15.
In this article, a subtractive clustering-based fuzzy identification method and a Sugeno-type fuzzy inference system are used for modeling in metal cutting. This approach is considered with its application on the experimental study of Boring and Trepanning Association (BTA) deep-hole drilling. The model for the surface roughness is identified by using the cutting speed and feed as input data and roughness as the output data. Using subtractive clustering in both input and output spaces performs the model-building process. Minimum error model is obtained through enumerative search of clustering parameters. The fuzzy model obtained is capable of predicting the surface roughness for a given set of inputs (speed and feed). Therefore, the operator can predict the quality of the surface for a given set of working parameters and will then be able to set the machining parameters to achieve a certain surface quality. The fuzzy model is verified experimentally by further experimentation using different sets of inputs. The tool life is also investigated using the same approach. The fuzzy inference system obtained is capable of predicting the tool life for a given set of cutting parameters. Therefore, the operator will be able to predict how many minutes the cutting tool is going to last and will set the time for the next tool change. 相似文献
16.
以一种进化聚类算法(ECM)为基础,提出了一种新的T-S型动态模糊推理模型的建模算法.以往许多神经模糊模型都不适用于自适应在线学习,而文章模型能够实时地调整模糊规则库及规则参数,具有较强的在线学习能力.仿真结果表明,该方法是有效的. 相似文献
17.
应用有序聚类法对辽宁省锦凌水库坝基的风化岩体进行定量分带,所得结果与地质观察方法、规范法等所得出的结果进行了分析比较.采用岩体风化差异系数法进行综合分析,最终推荐按照有序聚类方法进行风化岩体分带. 相似文献
18.
19.
J. L. Díez J. L. Navarro A. Sala 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2007,11(10):973-983
In this work, simple modifications on the cost index of particular local-model fuzzy clustering algorithms are proposed in
order to improve the readability of the resulting models. The final goal is simultaneously providing local linear models (reasonably
close to the plant’s Jacobian) and clustering in the input space so that desirable characteristics (regarding final model
accuracy, and convexity and smoothness of the cluster membership functions) are improved with respect to other proposals in
literature. Some examples illustrate the proposed approach. 相似文献
20.
H原子对固态合金化颗粒表面成份分布影响的研究 总被引:1,自引:0,他引:1
本文研究了氢化物TiH2对Fe+Ti机械合金化非晶储氢合金的表面成份偏聚和性能的影响。应用X射线光电子谱(XPS)和俄歇电子谱(AES)对样品表面由表及里逐层测量成份分布。同时应用热重分析方法研究了样品氧化性能和产物。研究结果表明,在机械合金化过程中,H原子不仅能使FeTi非晶化,同时促使表面产生明显的Fe原子偏聚。表面Fe/Ti原子比接近7。非晶FeTi(H)相的氧化分两个阶段进行,Ti原子首先氧化(833K),随后Fe原子氧化(890K)。 相似文献