Intelligent Data-Analytics for Condition Monitoring
-10%
portes grátis
Intelligent Data-Analytics for Condition Monitoring
Smart Grid Applications
Iqbal, Atif; Malik, Hasmat; Fatema, Nuzhat
Elsevier Science & Technology
03/2021
268
Mole
Inglês
9780323855105
15 a 20 dias
520
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1. Advances in Machine Learning and Data Analytics
PART A: Intelligent Data Analytics for Classification in Smart Grid2. Intelligent Data Analytics for PV Fault diagnosis Using Deep Convolutional Neural Network (ConvNet/CNN)3. Intelligent Data Analytics for Power Transformer Health Monitoring Using Modified Fuzzy Q Learning (MFQL)4. Intelligent Data Analytics for Induction Motor Using Gene Expression Programming (GEP)5. Intelligent Data Analytics for Power Quality Disturbance Analysis Using Multi-Class ELM6. Intelligent Data Analytics for Transmission Line Fault Diagnosis Using EEMD Based Multiclass SVM and PSVM
PART B: Intelligent Data Analytics for Forecasting in Smart Grid7. Intelligent Data Analytics for Global Solar Radiation Forecasting for Solar Power Production Using Deep Learning Neural Network (DLNN)8. Intelligent Data Analytics for Wind Speed Forecasting for Wind Power Production Using Long Short-Term memory (LSTM) Network9. Intelligent Data Analytics for Time-Series Load Forecasting Using Fuzzy Reinforcement Learning (FRL)10. Intelligent Data Analytics for Battery Charging/Discharging Forecasting Using Semi-supervised and Unsupervised Extreme Learning Machines
PART A: Intelligent Data Analytics for Classification in Smart Grid2. Intelligent Data Analytics for PV Fault diagnosis Using Deep Convolutional Neural Network (ConvNet/CNN)3. Intelligent Data Analytics for Power Transformer Health Monitoring Using Modified Fuzzy Q Learning (MFQL)4. Intelligent Data Analytics for Induction Motor Using Gene Expression Programming (GEP)5. Intelligent Data Analytics for Power Quality Disturbance Analysis Using Multi-Class ELM6. Intelligent Data Analytics for Transmission Line Fault Diagnosis Using EEMD Based Multiclass SVM and PSVM
PART B: Intelligent Data Analytics for Forecasting in Smart Grid7. Intelligent Data Analytics for Global Solar Radiation Forecasting for Solar Power Production Using Deep Learning Neural Network (DLNN)8. Intelligent Data Analytics for Wind Speed Forecasting for Wind Power Production Using Long Short-Term memory (LSTM) Network9. Intelligent Data Analytics for Time-Series Load Forecasting Using Fuzzy Reinforcement Learning (FRL)10. Intelligent Data Analytics for Battery Charging/Discharging Forecasting Using Semi-supervised and Unsupervised Extreme Learning Machines
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
actual operating condition; artificial intelligence; artificial neural network; Box-Cox transformation; classification; condition monitoring; ConvNet/CNN; data analytics; data preprocessing; dataset sources; deep neural network; demonstration; DGA; diagnosis; EEMD; ELM; EMD; failure analysis; fault classification; fault detection and diagnosis; fault diagnosis; FDD; feature extraction; feature selection; forecasting; fuzzy reinforcement learning; gene expression programming; health indicator; IMFs; induction motor; J48 algorithm; lithium-ion battery; long short-term memory (LSTM); MFQL; MLP; MLP-ANN; online monitoring; open access; power quality; power system; prediction; PSVM; PV module failure; PV system; remaining-useful-life (RUL); software; solar radiation; SVM; transmission line; vertical power plant; visualization; WECS; wind speed
1. Advances in Machine Learning and Data Analytics
PART A: Intelligent Data Analytics for Classification in Smart Grid2. Intelligent Data Analytics for PV Fault diagnosis Using Deep Convolutional Neural Network (ConvNet/CNN)3. Intelligent Data Analytics for Power Transformer Health Monitoring Using Modified Fuzzy Q Learning (MFQL)4. Intelligent Data Analytics for Induction Motor Using Gene Expression Programming (GEP)5. Intelligent Data Analytics for Power Quality Disturbance Analysis Using Multi-Class ELM6. Intelligent Data Analytics for Transmission Line Fault Diagnosis Using EEMD Based Multiclass SVM and PSVM
PART B: Intelligent Data Analytics for Forecasting in Smart Grid7. Intelligent Data Analytics for Global Solar Radiation Forecasting for Solar Power Production Using Deep Learning Neural Network (DLNN)8. Intelligent Data Analytics for Wind Speed Forecasting for Wind Power Production Using Long Short-Term memory (LSTM) Network9. Intelligent Data Analytics for Time-Series Load Forecasting Using Fuzzy Reinforcement Learning (FRL)10. Intelligent Data Analytics for Battery Charging/Discharging Forecasting Using Semi-supervised and Unsupervised Extreme Learning Machines
PART A: Intelligent Data Analytics for Classification in Smart Grid2. Intelligent Data Analytics for PV Fault diagnosis Using Deep Convolutional Neural Network (ConvNet/CNN)3. Intelligent Data Analytics for Power Transformer Health Monitoring Using Modified Fuzzy Q Learning (MFQL)4. Intelligent Data Analytics for Induction Motor Using Gene Expression Programming (GEP)5. Intelligent Data Analytics for Power Quality Disturbance Analysis Using Multi-Class ELM6. Intelligent Data Analytics for Transmission Line Fault Diagnosis Using EEMD Based Multiclass SVM and PSVM
PART B: Intelligent Data Analytics for Forecasting in Smart Grid7. Intelligent Data Analytics for Global Solar Radiation Forecasting for Solar Power Production Using Deep Learning Neural Network (DLNN)8. Intelligent Data Analytics for Wind Speed Forecasting for Wind Power Production Using Long Short-Term memory (LSTM) Network9. Intelligent Data Analytics for Time-Series Load Forecasting Using Fuzzy Reinforcement Learning (FRL)10. Intelligent Data Analytics for Battery Charging/Discharging Forecasting Using Semi-supervised and Unsupervised Extreme Learning Machines
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
actual operating condition; artificial intelligence; artificial neural network; Box-Cox transformation; classification; condition monitoring; ConvNet/CNN; data analytics; data preprocessing; dataset sources; deep neural network; demonstration; DGA; diagnosis; EEMD; ELM; EMD; failure analysis; fault classification; fault detection and diagnosis; fault diagnosis; FDD; feature extraction; feature selection; forecasting; fuzzy reinforcement learning; gene expression programming; health indicator; IMFs; induction motor; J48 algorithm; lithium-ion battery; long short-term memory (LSTM); MFQL; MLP; MLP-ANN; online monitoring; open access; power quality; power system; prediction; PSVM; PV module failure; PV system; remaining-useful-life (RUL); software; solar radiation; SVM; transmission line; vertical power plant; visualization; WECS; wind speed