114 Result(s)
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Chapter and Conference Paper
Answering Approximate Range Aggregate Queries on OLAP Data Cubes with Probabilistic Guarantees
Approximate range aggregate queries are one of the most frequent and useful kinds of queries for Decision Support Systems (DSS). Traditionally, sampling- based techniques have been proposed to tackle this prob...
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Chapter and Conference Paper
Modeling Dynamic System by Recurrent Neural Network with State Variables
A study is performed to investigate the state evolution of a kind of recurrent neural network. The state variable in the neural system summarize the information of external excitation and initial state, and de...
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Chapter and Conference Paper
A Novel Individual Blood Glucose Control Model Based on Mixture of Experts Neural Networks
An individual blood glucose control model (IBGCM) based on the Mixture of Experts (MOE) neural networks algorithm was designed to improve the diabetic care. MOE was first time used to integrate multiple indivi...
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Chapter and Conference Paper
A Novel Intrusion Detection Method Based on Principle Component Analysis in Computer Security
Intrusion detection is an important technique in the defense-in-depth network security framework and a hot topic in computer security in recent years. In this paper, a new intrusion detection method based on P...
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Chapter and Conference Paper
Multisensors Information Fusion with Neural Networks for Noninvasive Blood Glucose Detection
A multisensors information fusion model (MIFM) based on the Mixture of Experts (ME) neural networks was designed to fuse the multi-sensors signals for infrared noninvasive blood glucose detection. ME algorithm...
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Chapter and Conference Paper
FMC: An Approach for Privacy Preserving OLAP
To preserve private information while providing thorough analysis is one of the significant issues in OLAP systems. One of the challenges in it is to prevent inferring the sensitive value through the more aggr...
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Chapter and Conference Paper
Practical Indexing XML Document for Twig Query
Answering structural queries of XML with index is an important approach of efficient XML query processing. Among existing structural indexes for XML data, F&B index is the smallest index that can answer all br...
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Chapter and Conference Paper
Adaptive Neural Network Control for Nonlinear Systems Based on Approximation Errors
A stable adaptive neural network control approach is proposed in this paper for uncertain nonlinear strict-feedback systems based on backstep**. The key assumptions are that the neural network approximation ...
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Chapter and Conference Paper
Nonlinear System Adaptive Control by Using Multiple Neural Network Models
Multiple radial based function (RBF)neural network models are used to cover the uncertainty of time variant nonlinear system, and multiple element controllers are set up based on the multiple RBF models. At ev...
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Chapter and Conference Paper
Estimation of the Future Earthquake Situation by Using Neural Networks Ensemble
Earthquakes will do great harms to the people, to estimate the future earthquake situation in Chinese mainland is still an open issue. There have been previous attempts to solve this problem by using artificia...
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Chapter and Conference Paper
A Reputation Multi-agent System in Semantic Web
Though research on the Semantic Web has progressed at a steady pace, its promise has yet to be realized. One major difficulty is that, by its very nature, the Semantic Web is a large, uncensored system to whic...
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Chapter and Conference Paper
Traffic Volume Forecasting Based on Wavelet Transform and Neural Networks
This paper focuses on traffic volume forecasting that is an essential component of any responsive traffic control or route guidance system. A new approach for traffic volume prediction is proposed based on wav...
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Chapter and Conference Paper
Appearance-Based Map Learning for Mobile Robot by Using Generalized Regression Neural Network
Regression analysis between features of high-dimension is receiving attention in environmental learning of mobile robot. In this paper, we propose a novel framework, namely General regression neural network (G...
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Chapter and Conference Paper
Soft-Sensor Method Based on Least Square Support Vector Machines Within Bayesian Evidence Framework
Based on the character and requirement of the dynamic weighing of loader, the soft sensor technique was adapted as the weighing method, and the least square support vector machine (LS-SVM) as its modelling met...
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Chapter and Conference Paper
EviRank: An Evidence Based Content Trust Model for Web Spam Detection
Creating an effective spam detection method is a challenging task. Traditional works usually regard this kind of work as a problem of binary classification. In this paper, however, we argue that it is more pro...
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Chapter and Conference Paper
Bayesian Method Based Trusted Overlay for Information Retrieval over Networks
Peer-to-peer (P2P) overlay networks provide a new way to retrieve information over networks. How to assurance the reliability of the resource is the crucial issue of security. This paper proposes a trustworthy...
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Chapter and Conference Paper
A Novel Factoid Ranking Model for Information Retrieval
How can we distinguish accurate information from inaccurate or untrustworthy information is a big challenge in the field of information retrieval. This paper discusses trust as a factoid learning problem, whic...
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Chapter and Conference Paper
Analog Circuit Fault Fusion Diagnosis Method Based on Support Vector Machine
Lack of fault samples and statistic characteristic of artificial neural network, which restrict its more development and application in fault diagnosis. Support Vector Machine (SVM) is a machine – learning alg...
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Chapter and Conference Paper
An Immune Concentration Based Virus Detection Approach Using Particle Swarm Optimization
This paper proposes an immune concentration based virus detection approach which utilizes a two-element concentration vector to construct the feature. In this approach, ‘self’ and ‘nonself’ concentrations are ...
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Chapter and Conference Paper
GDM2010 Workshop Organizers’ Message
The graph is a powerful tool for representing and understanding objects and their relationships in various application domains. Recently, graphs have been widely used to model many complex structured and schem...