Artificial Intelligence and Data Mining 2014

Fuding Xie, Suohai Fan, Jianzhou Wang, Helen Lu, Caihong Li
2014 Abstract and Applied Analysis  
Artificial intelligence and data mining techniques have been widely used in many domains to solve classification, planning, diagnosis, computation, prediction, and optimization problems. The aim of this special issue is to reflect the latest development in this research field and provide advanced knowledge for researchers actively working on algorithms and applications of artificial intelligence. The accepted papers in this issue are concerned with the following topics: (i) forecasting models
more » ... sed on statistical methods and artificial intelligence; (ii) advanced artificial intelligence algorithm and novel data mining techniques; (iii) computational intelligence in medical science and biology; (iv) time series analysis in economics and finance; (v) machine learning on massive datasets. Among them, there are nine papers regarding forecasting models based on artificial intelligence and data mining techniques. In "Short-term wind speed forecasting using decomposition-based neural networks combining abnormal detection method," authored by X. Chen et al., two threestage hybrid approaches are developed for short-term wind speed forecasting. In "Wind power assessment based on a WRF wind simulation with developed power curve modeling methods," authored by Z. Guo and X. Xiao, the authors propose two improved power curve modeling methods. In "A hybrid approach by integrating brain storm optimization algorithm with grey neural network for stock index forecasting," authored by Y. Sun, a novel hybrid model based on the brain storm optimization approach is constructed for stock index forecast. In "Hybrid wind speed forecasting model study
doi:10.1155/2014/819641 fatcat:ktzo3xoqn5f4zkg6jienbohscq