Small lung nodules detection based on local variance analysis and probabilistic neural network

2018 ◽  
Vol 161 ◽  
pp. 173-180 ◽  
Author(s):  
Marcin Woźniak ◽  
Dawid Połap ◽  
Giacomo Capizzi ◽  
Grazia Lo Sciuto ◽  
Leon Kośmider ◽  
...  
Keyword(s):  
Neural Network ◽  
Probabilistic Neural Network ◽  
Variance Analysis ◽  
Lung Nodules ◽  
Local Variance

scholarly journals Small Lung Nodules Detection Based on Fuzzy-Logic and Probabilistic Neural Network With Bioinspired Reinforcement Learning

2020 ◽  
Vol 28 (6) ◽  
pp. 1178-1189 ◽  
Author(s):  
Giacomo Capizzi ◽  
Grazia Lo Sciuto ◽  
Christian Napoli ◽  
Dawid Polap ◽  
Marcin Wozniak
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Reinforcement Learning ◽  
Probabilistic Neural Network ◽  
Lung Nodules

Classification and Identification of Power System Disturbances Using Wavalet and Artificial Neural Network Technique

2005 ◽  
Vol 2 (2) ◽  
pp. 25
Author(s):  
Noraliza Hamzah ◽  
Wan Nor Ainin Wan Abdullah ◽  
Pauziah Mohd Arsad
Keyword(s):  
Neural Network ◽  
Power Quality ◽  
Probabilistic Neural Network ◽  
Microsoft Excel ◽  
Waveform Data ◽  
The Neural Network ◽  
Harmonic Voltage ◽  
Power Quality Disturbances ◽  
Electronic Load ◽  
Wavelet Technique

Power Quality disturbances problems have gained widespread interest worldwide due to the proliferation of power electronic load such as adjustable speed drives, computer, industrial drives, communication and medical equipments. This paper presents a technique based on wavelet and probabilistic neural network to detect and classify power quality disturbances, which are harmonic, voltage sag, swell and oscillatory transient. The power quality disturbances are obtained from the waveform data collected from premises, which include the UiTM Sarawak, Faculty of Science Computer in Shah Alam, Jati College, Menara UiTM, PP Seksyen 18 and Putra LRT. Reliable Power Meter is used for data monitoring and the data is further processed using the Microsoft Excel software. From the processed data, power quality disturbances are detected using the wavelet technique. After the disturbances being detected, it is then classified using the Probabilistic Neural Network. Sixty data has been chosen for the training of the Probabilistic Neural Network and ten data has been used for the testing of the neural network. The results are further interfaced using matlab script code.  Results from the research have been very promising which proved that the wavelet technique and Probabilistic Neural Network is capable to be used for power quality disturbances detection and classification.

scholarly journals Study on channel prediction for automated guided vehicle using a probabilistic neural network

2019 ◽  
Vol 8 (8) ◽  
pp. 311-317 ◽  
Author(s):  
Julian Webber ◽  
Norisato Suga ◽  
Abolfazl Mehbodniya ◽  
Kazuto Yano ◽  
Yoshinori Suzuki
Keyword(s):  
Neural Network ◽  
Probabilistic Neural Network ◽  
Automated Guided Vehicle ◽  
Channel Prediction

An improved robust heteroscedastic probabilistic neural network based trust prediction approach for cloud service selection

2018 ◽  
Vol 108 ◽  
pp. 339-354 ◽  
Author(s):  
Nivethitha Somu ◽  
Gauthama Raman M.R. ◽  
Kalpana V. ◽  
Kannan Kirthivasan ◽  
Shankar Sriram V.S.
Keyword(s):  
Neural Network ◽  
Probabilistic Neural Network ◽  
Service Selection ◽  
Cloud Service ◽  
Trust Prediction ◽  
Prediction Approach
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