A Polak-Ribière-Polyak Conjugate Gradient-Based Neuro-Fuzzy Network and its Convergence

Gao, Tao; Wang, Jian; Bingjie, Zhang; Zhang, Huaqing; Ren, Peng; Pal, Nikhil R.

doi:10.1109/access.2018.2848117

Cited by 13 publications

(2 citation statements)

References 38 publications

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“…The storage requirements for the Powell-Beale algorithm (six vectors) are slightly higher than for Polak-Ribiere algorithm (four vectors) [26]. These requirements can be tested by…”

Section: Laboratory Setupmentioning

confidence: 99%

Analysis of training techniques of ANN for classification of insulators in electrical power systems

Stefenon

Branco

Nied

et al. 2020

IET Generation, Transmission & Distribution

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“…The storage requirements for the Powell-Beale algorithm (six vectors) are slightly higher than for Polak-Ribiere algorithm (four vectors) [26]. These requirements can be tested by…”

Section: Laboratory Setupmentioning

confidence: 99%

Analysis of training techniques of ANN for classification of insulators in electrical power systems

Stefenon

Branco

Nied

et al. 2020

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

“…To solve the above problems, the FCM algorithm was initialized via the cluster centers and the number of clusters obtained by the SCM, and the initial fuzzy inference system structure was established via the initialized FCM algorithm. Then the learning algorithm of the traditional ANFIS was improved with Fletcher-Reeves conjugate gradient method [11]- [13]. In this way, the model structure was simpified, and the model accuracy was improved.…”

Section: Introductionmentioning

confidence: 99%

Evaluation on Partial Discharge Intensity of Electrical Equipment Based on Improved ANFIS and Ultraviolet Pulse Detection Technology

Wang

Deng³

et al. 2019

IEEE Access

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The ultraviolet pulse detection technology has superiorities in response speed and antijamming capability, so it is extensively applied to insulation detection for electrical equipment. The existing detection and analysis methods have defects, such as failure of precise modeling caused by incomplete analysis of influence factor, poor model adaptability, and complex operation. In allusion to the problems, the ultraviolet pulse detection circuit was optimized and its sensitivity was analyzed through tests. Then, a partial discharge intensity evaluation method for electrical equipment based on the improved adaptive network based fuzzy inference system (improved ANFIS) was proposed combined with the detected pulse count (P), temperature (T) and humidity (H). The initial fuzzy inference system structure was established with the subtractive clustering method (SCM) and fuzzy C-means (FCM) algorithm, and the traditional ANFIS learning algorithm was improved via Fletcher-Reeves conjugate gradient method. In this way, the model parameters were optimized continuously, and the system ability of ignoring small changes in the network was improved. Finally, the effectiveness and practicability of the method were verified through field test. The experimental results demonstrated that the improved ANFIS reduced the model error by 2% when compared with traditional ANFIS, and the model accuracy is improved. Besides, the quantitative precision of the discharge intensity is higher than that of the traditional ANFIS by the contrastive analysis of field test data, indicating that the improved ANFIS evaluate the partial discharge intensity of electrical equipment more accurately. Thus, a decision basis can be provided for the equipment protection and charged maintenance of the electric system. INDEX TERMS Conjugate gradient method, improved ANFIS, partial discharge intensity, subtractive clustering, ultraviolet pulse detection.

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GT2FS-SMOTE: An Intelligent Oversampling Approach Based Upon General Type-2 Fuzzy Sets to Detect Web Spam

Kaur

Gosain

2020

Arab J Sci Eng

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A Polak-Ribière-Polyak Conjugate Gradient-Based Neuro-Fuzzy Network and its Convergence

Cited by 13 publications

References 38 publications

Analysis of training techniques of ANN for classification of insulators in electrical power systems

Analysis of training techniques of ANN for classification of insulators in electrical power systems

Evaluation on Partial Discharge Intensity of Electrical Equipment Based on Improved ANFIS and Ultraviolet Pulse Detection Technology

GT2FS-SMOTE: An Intelligent Oversampling Approach Based Upon General Type-2 Fuzzy Sets to Detect Web Spam

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