[:         "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 2019-10-16 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 2019-10-17 that is Weekday, and it is not a public holiday. Weather of the start date: the minimum temperature is 283.29; the maximum temperature is 289.47; the humidity is 52.5; the pressure is 1018.75.  Weather of the prediction date: the minimum temperature is 280.84; the maximum temperature is 292.0; the humidity is 62.25; the pressure is 1017.75. In 2019-10-16 21:10:00, the news that had the Long-Term Effect on Future Load Consumption is that Multiple cities are trialling a freeze on drive-throughs at restaurants after a study linked the convenient feature to climate change. The region that may be influenced is General / Multiple Regions. The rationality is that Policies that are tied to climate change actions such as the freeze on drive-throughs could lead to a shift in consumption behavior over the long term. If sustainable practices become more widespread, they could encourage the adoption of energy efficiency measures and potentially decrease energy load consumption.In 2019-10-16 22:22:00, the news that had the Short-Term Effect on Today's Load Consumption is that Authorities fear properties could be under threat from a sizeable grass fire burning in Darwin near the city\u2019s airport. The region that may be influenced is Darwin. The rationality is that The grass fire near the airport could cause disruptions in power infrastructure and lead to increased energy usage in the short-term as emergency services respond and residents might use more electricity for tasks like air filtering and to stay informed about the fire.In 2019-10-16 13:30:00, the news that had the Real-Time Direct Effect on Today's Load Consumption is that The end of the week will see a bizarre contrast in weather with maximum temperatures 40C lower in Victoria than some parts of Queensland due to a vicious cold front. The region that may be influenced is Victoria / Queensland. The rationality is that Extreme weather conditions such as described could have a direct impact on energy load, with different needs in Victoria and Queensland due to the temperature contrast. Queensland might experience increased air conditioning use, while Victoria might have increased heating demand.",