Method and apparatus for predicting time-series data

An apparatus comprising:

• a memory storing a time-series model;
• and
• a processor configured to:
• collect a first time-series data including a power consumption data for a preset first time period of an air conditioner,
• input the first time-series data including invalid data into a time-series model to obtain a first plurality of prediction data including a prediction data corresponding to the invalid data,
• replace the invalid data included in the first time-series data with preset valid data,
• input the first time-series data including the valid data into the time-series model to obtain a second plurality of prediction data including a prediction data corresponding to the replaced valid data,
• obtain a first similarity between the first plurality of prediction data and a plurality of reference data and a second similarity between the plurality of second plurality of prediction data and the plurality of reference data,
• collect a second time-series data including a power consumption data for a second time period after the first time period of the air conditioner, and
• determine whether to replace invalid data included in the second time-series data with a preset valid data by comparing the first similarity with the second similarity,
• wherein the invalid data is null data corresponding to power consumption less than or equal to a preset reference value, and the valid data is data other than the null data.

A system comprising:

• an air conditioner;
• and
• a server configured to communicate with the air conditioner,
• wherein the server is configured to:
• collect a first time-series data including a power consumption data for a preset first time period of the air conditioner,
• input the first time-series data including invalid data into a time-series model to obtain a first plurality of prediction data including a prediction data corresponding to the invalid data,
• replace the invalid data included in the first time-series data with preset valid data,
• input the first time-series data including the valid data into the time-series model to obtain a second plurality of prediction data including a prediction data corresponding to the replaced valid data,
• obtain a first similarity between the first plurality of prediction data and a plurality of reference data and a second similarity between the plurality of second plurality of prediction data and the plurality of reference data,
• collect a second time-series data including a power consumption data for a second time period after the first time period of the air conditioner, and
• determine whether to replace invalid data included in the second time-series data with a preset valid data by comparing the first similarity with the second similarity,
• wherein the invalid data is null data corresponding to power consumption less than or equal to a preset reference value, and the valid data is data other than the null data.