Household Electricity Consumption – Machine Learning Algorithm

November 28, 2018
machine learning

 

Power supply, generation, and its billing generate a huge amount of data. ML actually makes it possible to learn from this data and use an algorithm to accurately predict future occurrences like volumes of load and its demand, snag identification, efficiency and power loss reduction, problems and logistics involved in metering and billing and everything in between from power generation to its billing and beyond.

Machine learning courses in India could teach you how to understand ML and data analytics, so you aid ML to perform at its best in predicting outcomes. The Algorithm in ML for household electricity consumption works on data drawn from smart meters, solar panels, and data regarding the usage of electricity at different times of the day.

This huge data comprises the multi-variable time-series, and the algorithm can successfully predict future consumption. In real terms, the ML algorithm can predict such information as to help make the power generation and supply system more efficient.

Obviously, there are many steps involved in helping the machine take data in its raw multivariate form and enabling it to arrive at the future consumption prediction. This is where Machine learning courses come in handy. You can learn the techniques of ML involving predictive strategies like the direct methods and the recursive ones.

A good idea is to also incorporate learning of Big Data Hadoop training courses that can help one understand strategies, working of ML and data analytics. The logic of the process of algorithm development would be developing

  • The framework development for evaluation of non- linear, linear, and ML ensemble algorithms.
  • Evaluation of ML as it uses the strategy of forecasting the time-series both by the direct daily method and the recursive method.

Again such processes involve

  1. Describing the problem.
  2. Preparing and loading the data set.
  3. Evaluating the model.
  4. Recursive forecasting.
  5. Multi-Step direct forecasting.

Through highly accurate predictions ML helps the algorithm to plan future power generation, reduce transmission losses, tweak the metering, billing and collection systems and so much more. Once you master such algorithms, ML and data analytics, the scope of applying ML to various and everyday issues on a real-time basis, open the wide world of opportunity and good remuneration to you.

Yes, ML and data analytics use Python framework which has immense scope for progress basically because it can predict the outcomes of simple and complex tasks, single and multi-variate tasks, and even makes single and complex predictions by learning from the data, filling in the missing values, creating new values and so on. And to learn an ML course is essential. Start today and soon you will be able to master such tasks quite easily.

 

Reference:

https://machinelearningmastery.com/multi-step-time-series-forecasting-with-machine-learning-models-for-household-electricity-consumption/

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