Hybridization of Haar Wavelet Decomposition and Computational Intelligent Algorithms for the Estimation of Climate Change Behavior
作者: Haruna ChiromaSameem AbdulkareemAdamu I. AbubakarEka Novita SariTutut HerawanAbdulsalam Ya’u Gital
作者单位: Department of Artificial Intelligence, University of Malaya;;Department of Information System, International Islamic University;;AMCS Research Center;;Department of Information Systems, University of Malaya;;Department of Computer Science, University of Technology Malaysia
英文丛书称: Lecture Notes in Computer Science;;Lec. Notes Stat.
出版社: Springer Berlin Heidelberg,   2014
ISBN: 978-3-642-55031-7
来源数据库: Springer Book
DOI: 10.1007/978-3-642-55032-4_23
关键词: Haar Wavelet DecompositionRelevance Vector MachineAdaptive Linear Neural NetworkClimate Change
原始语种摘要: Abstract We propose a hybrid of haar wavelet decomposition, relevance vector machine, and adaptive linear neural network (HWD-RVMALNN) for the estimation of climate change behavior. The HWD-RVMALNN is able to improve estimation accuracy of climate change more than the approaches already discussed in the literature. Comparative simulation results show that the HWD-RVMALNN outperforms cyclical weight/bias rule, Levenberg-Marquardt, resilient back-propagation, support vector machine, and learning vector quantization neural networks in both estimation accuracy and computational efficiency. The model proposes in this study can provide future knowledge of climate change behavior. The future climate change behavior can be used by policy makers in formulating policies that can drastically reduce...
全文获取路径: Springer  (合作)

  • change 变化
  • machine 机器
  • computational 计算的
  • quantization 量子化
  • wavelet 波涟
  • alert 警戒的
  • climate 气候
  • policy 政策
  • estimation 估计
  • vector 矢量