An Intelligent Data Mining System Through Integration Of Electromagnetism-Like Mechanism And Fuzzy Neural Network

2010 ◽  
pp. 61-84
Author(s):  
Peitsang Wu ◽  
Yung-Yao Hung
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Global Optimization ◽  
Fuzzy Neural Network ◽  
Local Optimum ◽  
Sample Point ◽  
Mining System ◽  
The Em Algorithm ◽  
Fuzzy Neural ◽  
Data Mining System

In this chapter, a meta-heuristic algorithm (Electromagnetism-like Mechanism, EM) for global optimization is introduced. The Electromagnetism-like mechanism simulates the electromagnetism theory of physics by considering each sample point to be an electrical charge. The EM algorithm utilizes an attraction-repulsion mechanism to move the sample points towards the optimum. The electromagnetism-like mechanism (EM) can be used as a stand-alone approach or as an accompanying algorithm for other methods. Besides, the electromagnetism-like mechanism is not easily trapped into local optimum. Therefore, the purpose of this chapter is using the electromagnetism-like mechanism (EM) to develop an electromagnetism-like mechanism based fuzzy neural network (EMFNN), and employ the EMFNN to train fuzzy if-then rules.

scholarly journals Data Mining Algorithm Based on Fuzzy Neural Network

2015 ◽  
Vol 7 (1) ◽  
pp. 1930-1935
Author(s):  
Wu Jianhui ◽  
Su Yu ◽  
Shao Hongbo ◽  
Yin Sufeng ◽  
Xue Ling ◽  
...  
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Fuzzy Neural Network ◽  
Data Mining Algorithm ◽  
Mining Algorithm ◽  
Fuzzy Neural

Data mining method based on rough set and fuzzy neural network

2020 ◽  
Vol 38 (4) ◽  
pp. 3717-3725
Author(s):  
Jingyong Zhou ◽  
Yuan Guo ◽  
Yu Sun ◽  
Kai Wu
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Rough Set ◽  
Fuzzy Neural Network ◽  
Mining Method ◽  
Data Mining Method ◽  
Fuzzy Neural

Applying Artificial Intelligence to Short-Term Traffic Flow Forecasting

2012 ◽  
Vol 433-440 ◽  
pp. 5214-5217
Author(s):  
Hai Huang
Keyword(s):  
Neural Network ◽  
Traffic Flow ◽  
Optimization Algorithm ◽  
Fuzzy Neural Network ◽  
Pso Algorithm ◽  
Local Optimum ◽  
Short Term ◽  
Traffic Flow Forecasting ◽  
Fuzzy Neural ◽  
Low Efficiency

Short-term traffic flow forecasting has a high requirement for the responding time and accuracy of the forecasting method because the result is directly used for instant traffic inducing. Based on the introduction of the fuzzy neural network model for short-term traffic flow forecasting together with its detailed procedures, this paper adopt the particle swarm optimization algorithm to train the fuzzy neural network. Its global searching and optimization algorithm helps to overcome the shortcomings of the traditional fuzzy neural network, such as its low efficiency and “local optimum”. A case study is also given for the PSO algorithm to train the fuzzy neural network for traffic flow forecasting. The result shows that the average square error is 0.932 when the PSO algorithm is put to use for the network training, which is 3.926 when the PSO is not used. Thus result is more accurate and it requires less time for the training procedures. It proves this method is feasible and efficient.

The Application of Fuzzy Neural Network in Data Mining

2011 ◽  
Vol 179-180 ◽  
pp. 930-935
Author(s):  
Wang Lan Tian
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Fuzzy Neural Network ◽  
Data Classification ◽  
Complex Data ◽  
Spatial Evolution ◽  
Urban Construction ◽  
Fuzzy Neural

Fuzzy neural network, which can deal with complex data and prediction process that other algorithms can not accomplish, has become a focus in recent years in many fields. Data mining can extract such information and knowledge as data classification, spatial evolution and prediction and so on, and in the huge cadastral data find the implied information which is helpful for our urban construction.

A Research for Data Mining Technology Based on Fuzzy Neural Network

2012 ◽  
Vol 433-440 ◽  
pp. 2509-2512 ◽  
Author(s):  
Li Na Liu ◽  
Hui Juan Qi ◽  
De Xiong Li
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Fuzzy Neural Network ◽  
Fuzzy Theory ◽  
Complex Structure ◽  
Data Mining Algorithm ◽  
Mining Technology ◽  
Training Time ◽  
Mining Algorithm ◽  
Fuzzy Neural

This paper introduces the concept of data mining generally and summarizes several methods of data mining, and presents a data mining algorithm based on fuzzy neural network (FNN). Using fuzzy theory and neural network to structure and train fuzzy neural network, the algorithm overcomes the shortcomings of neural network such as complex structure, long training time and lack of understandable representation of results.

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