Journal ArticleDOI
An Approach to Estimating Product Design Time Based on Fuzzy $\nu$ -Support Vector Machine
Hong-Sen Yan,Duo Xu +1 more
TLDR
Compared with the fuzzy neural network (FNN) model, the Fnu-SVM method requires fewer samples and enjoys higher estimating precision.Abstract:
This paper presents a new version of fuzzy support vector machine (FSVM) developed for product design time estimation. As there exist problems of finite samples and uncertain data in the estimation, the input and output variables are described as fuzzy numbers, with the metric on fuzzy number space defined. Then, the fuzzy nu-support vector machine (Fnu-SVM) is proposed on the basis of combining the fuzzy theory with the nu-support vector machine, followed by the presentation of a time estimation method based on Fnu-SVM and its relevant parameter-choosing algorithm. The results from the applications in injection mold design and software product design confirm the feasibility and validity of the estimation method. Compared with the fuzzy neural network (FNN) model, our Fnu-SVM method requires fewer samples and enjoys higher estimating precisionread more
Citations
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Cyber security
E. Sandstrom,J. Weiss +1 more
TL;DR: In this paper, the authors discuss cyber security in the electric power industry in general as well as some perspectives in VATTENFALL, one of Europe's largest electric utilities, and discuss the impact of cyber security on the VANET.
Journal ArticleDOI
Urban traffic flow forecasting using Gauss-SVR with cat mapping, cloud model and PSO hybrid algorithm
TL;DR: The chaotic cloud particle swarm optimization algorithm (CCPSO) is proposed, based on cat chaotic mapping and cloud model, to optimize the hyper parameters of the Gauss-SVR model to improve forecasting accuracy of urban traffic flow.
Journal ArticleDOI
Intersection traffic flow forecasting based on ν-GSVR with a new hybrid evolutionary algorithm
TL;DR: A new forecasting approach for short-term traffic flow, combining ν-GSVR model and CCGA algorithm, is proposed, and it is indicated that the model yield more accurate results than the compared models in forecasting the short- term traffic flow at the intersection.
Journal ArticleDOI
Classification of epilepsy seizure phase using interval type-2 fuzzy support vector machines
TL;DR: An interval type-2 fuzzy support vector machine (IT2FSVM) is proposed to solve a classification problem which aims to classify three epileptic seizure phases from the electroencephalogram (EEG) captured from patients with neurological disorder symptoms.
Journal ArticleDOI
The prediction model of earthquake casuailty based on robust wavelet v -SVM
TL;DR: Improved support vector machine (SVM) is applied to the construction of earthquake casualty prediction model and robust wavelet (RW) v-SVM earthquake casualty Prediction model is proposed, which provides an effective method to solve this problem.
References
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Corinna Cortes,Vladimir Vapnik +1 more
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TL;DR: This tutorial gives an overview of the basic ideas underlying Support Vector (SV) machines for function estimation, and includes a summary of currently used algorithms for training SV machines, covering both the quadratic programming part and advanced methods for dealing with large datasets.
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Didier Dubois,Henri Prade +1 more
TL;DR: This book effectively constitutes a detailed annotated bibliography in quasitextbook style of the some thousand contributions deemed by Messrs. Dubois and Prade to belong to the area of fuzzy set theory and its applications or interactions in a wide spectrum of scientific disciplines.