ANALYSIS OF DATA FROM HYDROGEN GAS POWER PLANT USING MACHINE LEARNING

By Manvi Chandra

MACHINE LEARNINGMachine learning is a subfield of computer science that evolved

from the study of pattern recognition and computational learning theory in artificial intelligence.

Machine Learning explores pattern recognition during data analysis through computer science and statistics.

Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look.

TYPES OF MACHINE LEARNING ALGORITHMS

MACHINE LEARNING STUDIOMicrosoft Azure Machine Learning Studio is a collaborative, drag-

and-drop tool you can use to build, test, and deploy predictive analytics solutions on your data.

WORKFLOW

Data Gathering

Load the data set

Clean the data set Split the data

Train ModelApply Algorithm

Evaluate Model

MODEL FOR HYDROGEN GAS POWER PLANT DATA

RESULTS AND ANALYSIS

RESULTS AND ANALYSIS CONTINUED According to our research we are able to predict Vehicle Pressure

(Pressure of hydrogen gas within the vehicle Hydrogen Storage System)using our model.

The algorithm used is decision forest regression.Decision forest are an ensemble learning method for

classification, regression and other tasks, that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees.

RESULTS AND ANALYSIS CONTINUEDSTATE OF CHARGE (SOC):- Ratio of hydrogen density within the vehicle storage system to the full-fill density. SOC is expressed as a percentage and is computed based on the gas density as per formula below:-

Our model predict vehicle pressure which in turn could be used to determine the state of charge.

Thank You