Wireless Sensor Networks (WSN) is an emerging technology that is developed with a large number of useful applications. On the other hand, Artificial Neural Networks (ANN) have found many successful applications in non...
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the proceedings contain 461 papers. the topics discussed include: distributed lock manager for distributed file system in shared-disk environment;an asymmetric data conversion scheme based on binary tags;scalable orch...
ISBN:
(纸本)9780769541082
the proceedings contain 461 papers. the topics discussed include: distributed lock manager for distributed file system in shared-disk environment;an asymmetric data conversion scheme based on binary tags;scalable orchestration strategy for automatic service composition;an energy efficient clustering scheme for self-organizing distributed wireless sensor networks;conceptual multi-level hierarchy for evaluation and classification;QoS assessment over multiple attributes;feature selection of gene expression data using regression model;incremental emerging patterns mining for identifying safe and non-safe power load lines;methods of pattern extraction and interval prediction for equipment maintenance;text detection using multilayer separation in real scene images;face recognition using layered linear discriminant analysis and small subspace;and a rotate-based best neighborhood matching algorithm for high definition image error concealment.
the paper addresses the problem of using Japanese candlestick methodology to analyze stock or forex market data by neural nets. Self organizing maps are presented as tools for providing maps of known candlestick forma...
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ISBN:
(纸本)9783642132070
the paper addresses the problem of using Japanese candlestick methodology to analyze stock or forex market data by neural nets. Self organizing maps are presented as tools for providing maps of known candlestick formations. they may be used to visualize these patterns, and as inputs for more complex trading decision systems. in that case their role is preprocessing, coding and pre-classification of price data. An example of a profitable system based on this method is presented. Simplicity and efficiency of training and network simulating algorithms is emphasized in the context of processing streams of market data.
Water leakage is now a serious widespread problem in water distribution network (WDN), no matter what pipe material it used, leakage will occur inevitably with time. therefore, the problem of water leakage has become ...
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ISBN:
(纸本)9780415548519
Water leakage is now a serious widespread problem in water distribution network (WDN), no matter what pipe material it used, leakage will occur inevitably with time. therefore, the problem of water leakage has become the focus of China's water supply industry. When leakage occurs, the values of the pressure at monitoring points will fluctuate which are relation with leakage degree or location. And it is just like the fingerprints by which software can identify a person. therefore, in this paper, PNN (PNN) is provided for recognizing fluctuations caused by leakage so as to find the leakage locations approximately by the method of Bayesian classifier selector. the model is applied in water supply networks of a city located in Northeast of China, using its actual monitoring data to check the established leakage locating model. then we analyzed the existing problems of model and proposed possible measures for leakage control of water industry.
A discussion on involvement of knowledge based methods in implementation of user friendly computer programs for disabled people is the goal of this paper. the paper presents a concept of a computer program that is aim...
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the paper presents preliminary results of data analysis and discusses the application of soft computing methods in the field of non-destructive tests. the main objective of developed diagnostic system are the automati...
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ISBN:
(纸本)9783642132315
the paper presents preliminary results of data analysis and discusses the application of soft computing methods in the field of non-destructive tests. the main objective of developed diagnostic system are the automatic detection and evaluation of damage. thus the system is composed of two signal processing techniques known as novelty detection and patternrecognition. For this purpose autoassociative as well as feed-forward neural networks are used. All the signals used for training the system are obtained from laboratory tests of strip specimens, where phenomenon of elastic wave propagation in solids was utilized. Computed parameters of time signals defines various types of input vectors used for training neural networks. the results finally obtained prove that the proposed diagnostic system made automation of structure testing possible and can be applied to Structural Health Monitoring.
Radar signal recognition is an important step of radar countermeasure processing. the classical recognition method is called weight distance, in which the feature parameter weights are obtained by expert and then the ...
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In patternrecognition applications with high number of input features and insufficient number of samples, the curse of dimensionality can be overcome by extracting features from smaller feature subsets. the domain kn...
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At the present IC technologies, the accurately extraction of the interconnects parasitic parameters become more important. But for the time consuming, that computingthe parameters of interconnects with field solver d...
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this paper presents a systematic Differential Fault Analysis (DFA) method on Feistel ciphers, the outcome of which closely links to that of the theoretical cryptanalysis with provable security. For this purpose, we in...
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