The Quantitative Metallogenic Prediction Model based on PSO-BP algorithm and Fuzzy Neural Network

International Journal of Advancements in Computing Technology ◽

10.4156/ijact.vol5.issue5.4 ◽

2013 ◽

Vol 5 (5) ◽

pp. 32-39

Author(s):

Zhenwu WANG ◽

Xuejun Zhao

Keyword(s):

Neural Network ◽

Prediction Model ◽

Fuzzy Neural Network ◽

Bp Algorithm ◽

Model Based ◽

Fuzzy Neural ◽

Metallogenic Prediction

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A fuzzy neural network prediction model based on manifold learning to reduce dimensions for typhoon intensity

2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA) ◽

10.1109/iciea.2013.6566432 ◽

2013 ◽

Author(s):

Jin Long ◽

Shi Xvming ◽

Huang Xiaoyan ◽

Huang Ying

Keyword(s):

Neural Network ◽

Prediction Model ◽

Manifold Learning ◽

Fuzzy Neural Network ◽

Model Based ◽

Typhoon Intensity ◽

Fuzzy Neural ◽

Neural Network Prediction ◽

Network Prediction

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Effluent COD of SBR Process Prediction Model Based on Fuzzy-Neural Network

2005 International Conference on Neural Networks and Brain ◽

10.1109/icnnb.2005.1614749 ◽

2006 ◽

Author(s):

Qiumei Cong ◽

Tianyou Chai

Keyword(s):

Neural Network ◽

Prediction Model ◽

Fuzzy Neural Network ◽

Model Based ◽

Fuzzy Neural ◽

Process Prediction

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Study on wood dyeing pigment formula prediction model based on dynamic fuzzy neural network

2010 2nd International Conference on Computer Engineering and Technology ◽

10.1109/iccet.2010.5485872 ◽

2010 ◽

Author(s):

Xuemei Guan ◽

Minghui Guo ◽

Jun Cao

Keyword(s):

Neural Network ◽

Prediction Model ◽

Fuzzy Neural Network ◽

Model Based ◽

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Water quality Prediction Model Based on fuzzy neural network

Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer ◽

10.2991/mmebc-16.2016.127 ◽

2016 ◽

Author(s):

Fan Liao ◽

Chunxia Zhao

Keyword(s):

Neural Network ◽

Water Quality ◽

Prediction Model ◽

Fuzzy Neural Network ◽

Quality Prediction ◽

Water Quality Prediction ◽

Model Based ◽

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A Novel Network Intrusion Attempts Prediction Model Based on Fuzzy Neural Network

Computational Science – ICCS 2006 - Lecture Notes in Computer Science ◽

10.1007/11758501_58 ◽

2006 ◽

pp. 419-426 ◽

Author(s):

Guiling Zhang ◽

Jizhou Sun

Keyword(s):

Neural Network ◽

Prediction Model ◽

Fuzzy Neural Network ◽

Model Based ◽

Network Intrusion ◽

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A short-term climate prediction model based on a modular fuzzy neural network

Advances in Atmospheric Sciences ◽

10.1007/bf02918756 ◽

2005 ◽

Vol 22 (3) ◽

pp. 428-435 ◽

Author(s):

Jin Long ◽

Jin Jian ◽

Yao Cai

Keyword(s):

Neural Network ◽

Prediction Model ◽

Fuzzy Neural Network ◽

Climate Prediction ◽

Model Based ◽

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Airworthiness Evaluation Model Based on Fuzzy Neural Network

Smart Service Systems, Operations Management, and Analytics - Springer Proceedings in Business and Economics ◽

10.1007/978-3-030-30967-1_17 ◽

2019 ◽

pp. 183-194

Author(s):

Jie-Ru Jin ◽

Peng Wang ◽

Yang Shen ◽

Kai-Xi Zhang

Keyword(s):

Neural Network ◽

Fuzzy Neural Network ◽

Evaluation Model ◽

Model Based ◽

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Novel Model Based on Wavelet Transform and GA-fuzzy Neural Network Applied to Short Time Traffic Flow Prediction

Information Technology Journal ◽

10.3923/itj.2011.2105.2111 ◽

2011 ◽

Vol 10 (11) ◽

pp. 2105-2111 ◽

Author(s):

Yuesheng Gu ◽

Yancui Li ◽

Jiucheng Xu ◽

Yanpei Liu

Keyword(s):

Neural Network ◽

Wavelet Transform ◽

Traffic Flow ◽

Fuzzy Neural Network ◽

Traffic Flow Prediction ◽

Model Based ◽

Flow Prediction ◽

Fuzzy Neural ◽

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Short-Term Power Load Forecasting Model Based on Fuzzy Neural Network using Improved Decision Tree

2019 IEEE Sustainable Power and Energy Conference (iSPEC) ◽

10.1109/ispec48194.2019.8975070 ◽

2019 ◽

Author(s):

Zhenxue Xie ◽

Ruogu Wang ◽

Zihao Wu ◽

Tong Liu

Keyword(s):

Neural Network ◽

Decision Tree ◽

Fuzzy Neural Network ◽

Load Forecasting ◽

Forecasting Model ◽

Model Based ◽

Power Load Forecasting ◽

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Surface Roughness Prediction Model of Cylinder Grinding

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.157-158.123 ◽

2012 ◽

Vol 157-158 ◽

pp. 123-126 ◽

Author(s):

Ning Ding ◽

Yi Chen Wang ◽

Ding Tong Zhang ◽

Yu Xiang Shi ◽

Jian Shi

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Prediction Model ◽

Fuzzy Neural Network ◽

Vibration Signal ◽

Vibration Data ◽

Proposed Model ◽

Fuzzy Neural ◽

Roughness Prediction

Based on the theory of roughness during cylinder grinding and the theory of fuzzy-neural network, a surface roughness intelligent prediction model is developed in this paper. The feed, speed, and the vibration data are the inputs for the model. An accelerometer is used to gather the vibration signal in real time. The model is used in the grinding experiment, and verifies the feasibility of the proposed model.

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