Main Reference PaperA Data Mining Approach Combining K-Means Clustering with Bagging Neural Network for Short-term Wind Power Forecasting, IEEE Internet of Things Journal, March 2017 [Java]
  • Wind power forecasting (WPF) based on K-means clustering and bagging neural network is proposed to classify the samples containing meteorological conditions and historical power data and to overcome the over fitting and instability problems of conventional networks.

+ Description
  • Wind power forecasting (WPF) based on K-means clustering and bagging neural network is proposed to classify the samples containing meteorological conditions and historical power data and to overcome the over fitting and instability problems of conventional networks.

  • To improve the forecasting accuracy using combined data mining approaches

  • To evaluate the effectiveness of the proposed approach.

+ Aim & Objectives
  • To improve the forecasting accuracy using combined data mining approaches

  • To evaluate the effectiveness of the proposed approach.

  • A technique is contributed that improves accuracy.

+ Contribution
  • A technique is contributed that improves accuracy.

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, & J2SE.

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, & J2SE.

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-Depending on the complexity of the project and requirements.

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