An intelligent grid synchronization technique for microgrid system with smooth power quality using chaotic grey wolf optimization‐random forest algorithm scheme

2021 ◽  
Author(s):  
M. Manigandan ◽  
Basavaraja Banakara
Keyword(s):  
Random Forest ◽  
Power Quality ◽  
Grey Wolf ◽  
Random Forest Algorithm ◽  
Grey Wolf Optimization ◽  
Grid Synchronization ◽  
Algorithm Scheme

Liver Disease Detection Using Grey Wolf Optimization and Random Forest Classification

2021 ◽  
pp. 130-160
Author(s):  
Singaravelan Shanmugasundaram ◽  
Parameswari M.
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Random Forest Classifier ◽  
Cutting Edge ◽  
Learning Approaches ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Metavir Score

Utilizing machine learning approaches as non-obtrusive strategies is an elective technique in organizing perpetual liver infections for staying away from the downsides of biopsy. This chapter assesses diverse machine learning methods in expectation of cutting-edge fibrosis by joining the serum bio-markers and clinical data to build up the order models. An imminent accomplice of patients with incessant hepatitis C was separated into two sets—one classified as gentle to direct fibrosis (F0-F2) and the other ordered as cutting-edge fibrosis (F3-F4) as per METAVIR score. Grey wolf optimization, random forest classifier, and decision tree procedure models for cutting-edge fibrosis chance expectation were created. Recipient working trademark bend investigation was performed to assess the execution of the proposed models.

scholarly journals Power Quality Improvement in a Grid Coupled Solar PV System using Grey Wolf Optimization

2019 ◽  
Vol 8 (10) ◽  
pp. 3200-3204
Keyword(s):  
Quality Improvement ◽  
Power Quality ◽  
Reactive Power ◽  
Optimization Technique ◽  
Solar Irradiation ◽  
Solar Pv ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Power Quality Improvement ◽  
Utility Grid

Since the PV penetration in the utility grid is increasing rapidly, there is a need of a control strategy for the purpose of energy optimization and for providing clean and green electric power to the utility grid. In this paper, a dynamic technique is proposed employing a Fractional Order PI controller tuned using Grey Wolf Optimization Technique. The strategy provides the independent control active as well as reactive power being injected into the grid. A complete investigation on performance analysis and THD levels at different solar irradiation value were conducted on MATLAB/SIMULINK software. The efficacy of the work is validated by comparing the results obtained by using Grey Wolf Optimization with permissible IEEE standards and the observations proves the power quality improvement by reducing the THD i.e. Total Harmonic Distortion levels.

Evaluation of Grey Wolf Optimization Algorithm on Rigid and Flexible Receptor Docking

2020 ◽  
Author(s):  
Kin Meng Wong ◽  
Shirley Siu
Keyword(s):  
Scoring Function ◽  
Ligand Docking ◽  
Receptor Protein ◽  
Pose Prediction ◽  
Grey Wolf ◽  
Success Rates ◽  
Autodock Vina ◽  
Grey Wolf Optimization ◽  
Structure Based Drug Design ◽  
Docking Program

Protein-ligand docking programs are indispensable tools for predicting the binding pose of a ligand to the receptor protein in current structure-based drug design. In this paper, we evaluate the performance of grey wolf optimization (GWO) in protein-ligand docking. Two versions of the GWO docking program – the original GWO and the modified one with random walk – were implemented based on AutoDock Vina. Our rigid docking experiments show that the GWO programs have enhanced exploration capability leading to significant speedup in the search while maintaining comparable binding pose prediction accuracy to AutoDock Vina. For flexible receptor docking, the GWO methods are competitive in pose ranking but lower in success rates than AutoDockFR. Successful redocking of all the flexible cases to their holo structures reveals that inaccurate scoring function and lack of proper treatment of backbone are the major causes of docking failures.

Optimal Conductor Selection Using Grey Wolf Optimization

2016 ◽  
Vol 4 (3) ◽  
pp. 39
Author(s):  
Ramanaiah M. LAXMIDEVI ◽  
REDDY M. DAMODAR ◽  
◽  
Keyword(s):  
Grey Wolf ◽  
Grey Wolf Optimization

METHOD SUGGESTING CITY WALKING ROUTES FOR PEDESTRIANS USING AN EXAMPLE OF SAINT-PETERSBURG

2019 ◽  
pp. 71-76
Author(s):  
A.E. Semenov
Keyword(s):  
Random Forest ◽  
Develop Model ◽  
Random Forest Algorithm ◽  
Saint Petersburg ◽  
Pedestrian Navigation ◽  
Factors Influencing ◽  
The City

The method of pedestrian navigation in the cities illustrated by the example of Saint-Petersburg was investigated. The factors influencing people when they choose a route for their walk were determined. Based on acquired factors corresponding data was collected and used to develop model determining attractiveness of a street in the city using Random Forest algorithm. The results obtained shows that routes provided by the method are 14% more attractive and just 6% longer compared with the shortest ones.

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