[:         "input": "Based on the historical load data, please predict the load consumption in the next day. The region for prediction is QLD. The start date of historical data was on 2019-3-11 that is Weekday, and it is not a public holiday. The data frequency is 30 minutes per point. Historical data covers 1 day. The date of prediction is on 2019-3-12 that is Weekday, and it is not a public holiday. Weather of the start date: the minimum temperature is 295.78; the maximum temperature is 310.01; the humidity is 65.0; the pressure is 1009.0.  Weather of the prediction date: the minimum temperature is 295.28; the maximum temperature is 307.56; the humidity is 78.0; the pressure is 1011.0. In 2019-03-11 22:10:00, the news that had the Long-Term Effect on Future Load Consumption is that Hungry bugs are being used to battle a prickly problem of getting rid of cacti in Onkaparinga Park. The region that may be influenced is SA. The rationality is that The introduction of biological agents to control invasive species suggests a shift towards more sustainable and environmentally friendly agricultural practices. This can lead to long-term changes in energy consumption patterns related to industrial and agricultural sectors.In 2019-03-11 21:50:00, the news that had the Short-Term Effect on Today's Load Consumption is that Airlines in multiple countries have suspended the use of Boeing\u2019s new 737 MAX 8 aircraft, as the black box of an Ethiopian Airlines flight is examined for clues. The region that may be influenced is WA. The rationality is that Grounding aircraft could result in short-term increases in load consumption due to potential additional flights for stranded passengers, changes in air traffic, or increased activity at airports. However, these effects are usually localized and temporary.In 2019-03-11 21:03:00, the news that had the Real-Time Direct Effect on Today's Load Consumption is that Sydneysiders faced lengthy delays getting home after a broken down train sparked chaos across the rail network. The region that may be influenced is NSW. The rationality is that The malfunction of a train in a major city's rail network could cause immediate changes in consumption as stations might see increased lighting and escalator use, commuters may choose alternative electric transportation, or people turn to residential consumption sooner as they arrive home later.",