[:         "input": "Based on the historical load data, please predict the load consumption in the next day. The region for prediction is SA. The start date of historical data was on 2019-3-29 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 2019-3-30 that is Weekend, and it is not a public holiday. Weather of the start date: the minimum temperature is 283.64; the maximum temperature is 289.68; the humidity is 65.5; the pressure is 1018.75.  Weather of the prediction date: the minimum temperature is 287.1; the maximum temperature is 292.85; the humidity is 67.0; the pressure is 1022.5. In 2019-03-29 17:21:00, the news that had the Long-Term Effect on Future Load Consumption is that A Sydney man who plotted to kill \u201cfive, six or seven\u201d people a month in the name of Islamic State, gave the terror group\u2019s salute in court. The region that may be influenced is NSW. The rationality is that This news potentially indicates concerns about security and societal stability in the long term, which can influence political stability and policies related to energy and security, thus indirectly affecting long-term load consumption.In 2019-03-29 17:59:00, the news that had the Short-Term Effect on Today's Load Consumption is that A severe thunderstorm warning has been issued for parts of NSW as remnants of Cyclone Trevor sweep through the state. The region that may be influenced is NSW. The rationality is that Severe weather conditions typically result in immediate changes to energy usage patterns due to the increased use of heating or cooling systems, as well as possible outages or emergency measures affecting short-term load consumption.In 2019-03-29 12:02:00, the news that had the Real-Time Direct Effect on Today's Load Consumption is that Dozens of planes were diverted away from Sydney Airport and hundreds of passengers stuck on the tarmac after a control tower issue. The region that may be influenced is NSW. The rationality is that The diversion of planes and delays can cause a sudden increase in demand at the airport and surrounding facilities. The extra use of air conditioning, lighting, and other electronic devices by stranded passengers can lead to a real-time direct effect on load consumption.",