Abstract:
The disclosure discloses an intelligent terminal energy saving method based on artificial intelligence (AI) prediction. The method includes: collecting application (APP)-related operation data on the intelligent terminal; carrying out AI analysis on the APP-related operation data collected, to predict timing and a restriction measurement to restrict an APP in a background; and adopting the restriction measurement to restrict the APP in the background at the timing predicted. Corresponding to the method, the disclosure further discloses an intelligent terminal energy saving device based on AI prediction. Using the technical schemes disclosed in the disclosure, the power consumption of applications on a portable intelligent terminal can be reduced, and the battery life can be extended, without affecting the user experience.
Abstract:
A method and a device for clearing a process in an electronic device are provided. The method includes calculating an amount of memory allocated for a preset time period when a memory application is requested, predicting an amount of memory to be allocated for a future setting time period based on the amount of the memory, and selecting and clearing at least one of present processes based on the amount of the memory to be allocated. Accordingly, sufficient memory can be obtained in a short period of time by recalling a plurality of processes. In this way, the electronic device can continuously allocate an abundance of memory.
Abstract:
A method and apparatus for controlling game applications are provided. In the method, when an operating system receives a game starting command, the operating system determines a manner to start a corresponding game application according to whether the game application has resided in a memory, and when a cold boot manner is used, the operating system triggers the game application to report an amount of memory required currently by the game application, and determines whether a requirement of running the game application is met according to the amount of memory required and an amount of memory currently used, or the operating system ensures to meet the requirement of running the game application through background application freezing and clearing. When the game application finishes running, the operating system uses a pre-trained machine learning model to predict running hotness of the game application on the terminal device according to a current operating parameter of the game application, sorts game applications on the terminal device according to the running hotness, and performs a corresponding residing process when determining that the game application needs to reside in the memory according to a sorting result. The method can efficiently shorten the time cost to start the game application.