[:         "input": "Based on the historical load data, please predict the load consumption in the next day. The region for prediction is TAS. The start date of historical data was on 2019-10-23 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 2019-10-24 that is Weekday, and it is not a public holiday. Weather of the start date: the minimum temperature is 282.13; the maximum temperature is 298.97; the humidity is 67.0; the pressure is 1014.0.  Weather of the prediction date: the minimum temperature is 288.58; the maximum temperature is 299.39; the humidity is 40.0; the pressure is 991.0. In 2019-10-23 08:02:00, the news that had the Long-Term Effect on Future Load Consumption is that Drought-stricken farmers are urging the federal government to offer exit packages to \u201cease the burden\u201d for those wanting to leave the land. The region that may be influenced is NSW. The rationality is that This news reflects shifts in agricultural activities and potential land use changes, which could have long-term implications for regional energy demands, especially if farming practices are reduced or significantly altered.In 2019-10-23 15:40:00, the news that had the Short-Term Effect on Today's Load Consumption is that A watch and act notice has been issued for a fire that is burning out of control at Wongulla towards Leochels Rd at Nildottie. The region that may be influenced is SA. The rationality is that Wildfires may lead to an immediate increase in load consumption due to emergency response efforts, displacement of populations, and the usage of equipment to combat the fires.In 2019-10-23 06:39:26, the news that had the Real-Time Direct Effect on Today's Load Consumption is that CBD traffic has been delayed throughout the morning peak due to a burst water main on Morphett St near Franklin St, but the road is expected to reopen at lunchtime. The region that may be influenced is SA. The rationality is that This incident may cause a direct change in electricity usage patterns due to traffic disruptions and repair operations, including increased load from traffic management systems and water pumping and repair equipment.",