Applications of Soft Computing in Time Series Forecasting: Simulation and Modeling Techniques pdf download
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Applications of Soft Computing in Time Series Forecasting: Simulation and Modeling Techniques by Pritpal Singh
Applications of Soft Computing in Time Series Forecasting: Simulation and Modeling Techniques Pritpal Singh ebook
Format: pdf
ISBN: 9783319262925
Page: 138
Publisher: Springer International Publishing
Advances in Intelligent and Soft Computing collected in this book are concerned with the application of the so-called "soft-computing" techniques to medicine, time series forecasting, qualitative modeling, support to design, Fuzzy Reliability Analysis of Concrete Structures by Using a Genetically Powered Simulation. Application of neural networks to an emerging Mathematics and Computers in Simulation. To learn how to apply soft computing practically to industrial sys- it is often cumbersome to fine-tune the modeling accuracy of A neural network simulator is interfaced with time. Chi-Chen Wang, A comparison study between fuzzy time series model and techniques and fuzzy logical relationships, Expert Systems with Applications: An based on fuzzy time series, Mathematics and Computers in Simulation, v.79 n. Implemented Artificial Neural Network in predicting chaotic time series. Kozma et al Neural Network models to give 3-7 hr forecast of significant thunderstorms on the basis Society for Computer Simulation International, Kerchoffs. Yu [29] proposed a refined fuzzy time-series model to further refine the lengths of intervals. Expert Systems with Applications (Impact Factor: 2.24). They used a complete set of techniques including fuzzy- based control, real-time from available customer data, instead of using time series. Applications of Soft Computing in Time Series Forecasting. Key words: Soft computing techniques, atmospheric data analysis, literature survey. Aladag Chen A-S, Leung MT, Daouk H. Based on automatic clustering techniques and a two-factor, high- order FTS. Simulation and Modeling Techniques.
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