IRO Journals

Journal of Artificial Intelligence and Capsule Networks

Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3

Blockchain-Enabled Federated Learning on Kubernetes for Air Quality Prediction Applications
Volume-3 | Issue-3

Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4

Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3

Hybrid Parallel Image Processing Algorithm for Binary Images with Image Thinning Technique
Volume-3 | Issue-3

Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
Volume-3 | Issue-4

QoS-aware Virtual Machine (VM) for Optimal Resource Utilization and Energy Conservation
Volume-3 | Issue-3

Probabilistic Neural Network based Managing Algorithm for Building Automation System
Volume-3 | Issue-4

Fusion based Feature Extraction Analysis of ECG Signal Interpretation - A Systematic Approach
Volume-3 | Issue-1

Artificial Bee Colony Optimization Algorithm for Enhancing Routing in Wireless Networks
Volume-3 | Issue-1

Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4

Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3

Real Time Anomaly Detection Techniques Using PySpark Frame Work
Volume-2 | Issue-1

Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3

Audio Tagging Using CNN Based Audio Neural Networks for Massive Data Processing
Volume-3 | Issue-4

Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
Volume-3 | Issue-4

Frontiers of AI beyond 2030: Novel Perspectives
Volume-4 | Issue-4

Early Stage Detection of Crack in Glasses by Hybrid CNN Transformation Approach
Volume-3 | Issue-4

Artificial Intelligence Algorithm with SVM Classification using Dermascopic Images for Melanoma Diagnosis
Volume-3 | Issue-1

An Efficient Machine Learning based Model for Classification of Wearable Clothing
Volume-3 | Issue-4

Home / Archives / Volume-2 / Issue-1 / Article-4

Volume - 2 | Issue - 1 | march 2020

Performance Analysis of Wind Turbine Monitoring Mechanism Using Integrated Classification and Optimization Techniques
Dr. Subarna Shakya  235  201
Pages: 31-41
Cite this article
Shakya, D. S. (2020). Performance Analysis of Wind Turbine Monitoring Mechanism Using Integrated Classification and Optimization Techniques. Journal of Artificial Intelligence and Capsule Networks, 2(1), 31-41. doi:10.36548/jaicn.2020.1.004
Published
20 April, 2020
Abstract

The advanced improvements in the techniques utilized in the field of energy generation using the wind mills has led to the remarkable minimization in its capital investments and the cost incurred in its operation. This has even enhanced the prominence of the winds farms worldwide and has raised the market share of the energy produced using the wind mills. Thus leading to the increase in the necessity for capable monitoring mechanisms that is cost effective to report the conditions of the wind turbines regularly. So that it would be helpful in early diagnosis of any fault that has occurred in the wind turbines. To have an accurate monitoring and minimized maintenance cost the paper integrates the Support Vector machine based Cuckoo Search Algorithm. The incorporation of the SVM with the CSO is validated in MATLAB under the gain-factor and the fixed value types of faults that are liable to occur in the wind turbines and the results acquired are compared with the other existing methods such as the SVM-PSO and K-NN. The results observed shows that the SVM based CSO is more accurate in predicting the fault models than the other existing models.

Keywords

Wind Farms Fault Diagnosis Machine Learning Models Cuckoo Search Optimization (CSO) Support Vector Machine (SVM) Particle Swarm Optimization (PSO) K-Nearest Neighbor

Full Article PDF Download Article PDF 
×

Currently, subscription is the only source of revenue. The subscription resource covers the operating expenses such as web presence, online version, pre-press preparations, and staff wages.

Subscription Payment Details

townscript (INR / USD): click here

Subscription Fee

Annual Subscription 15,000 INR / 200 USD
Subscription form: click here