1. Adjust parameters in the model: If specific parameters or variables are involved in your model, you can try to adjust their values to affect the downward trend of data. For example, in the optimization model, we can try to adjust the values of some parameters to minimize the optimization function and make the results closer to the target value.
2. Modify the model structure and algorithm: If your model contains complex algorithms or processes, you can try to modify its structure or operation mode to improve the downward trend of data. For example, in the simulation model, you can try to influence the output by changing the behavior of the experimental object.
3. Increase the number of data points: If your number of data points is small, random errors or other factors may affect the downward trend of data. In order to solve this problem, we can try to increase the number of data points to obtain more accurate and reliable results.
4. Use smoothing technology: If there is noise or interference in your data, you can try to use smoothing technology to reduce noise and improve the downward trend of data. For example, moving average or exponential smoothing can be used to smooth data.
Please note that this is just one of some technologies that may be useful. It depends on the AnyLogic model and data type you use, so please choose the most appropriate method according to the actual situation.