1. Yapay zekâ tarafından kontrol edilen özgün bir termoelektrik CPU soğutma sistemi.
- Author
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Umut, İlhan and Akal, Dinçer
- Subjects
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CENTRAL processing units , *ARTIFICIAL intelligence , *HEAT convection , *HEAT conduction , *RANDOM forest algorithms , *K-nearest neighbor classification - Abstract
Due to the excessive temperature rise in the Central Processing Unit (CPU), computers shut down and system damage occurs over time. In this study, a new thermoelectric cooling system is designed to reduce the temperature in the CPU. The novel cooling system is designed using a thermoelectric module. It is to remove the excess heat by conduction and convection by taking advantage of the temperature difference between the thermoelectric cooler and the CPU we add to the system. Since the temperature of the thermoelectric cooler will always be lower than the CPU temperature, effective cooling will be provided. A special electronic circuit and software have been developed for the control of the cooling unit. Three different artificial intelligence models (artificial neural network, random forest, and k-nearest neighbor) were created to dynamically control the additional cooling system and their successes were compared. Artificial intelligence determines the power and fan speed of the thermoelectric cooling system. It performs this control by evaluating all parameters (different values such as CPU frequency, voltage, number of processes) instead of a specific CPU load or a specific temperature value. While the CPU temperature was 41°C at maximum load, this temperature was reduced to 31°C thanks to the designed thermoelectric cooling system. All methods provided a high classification success in education. By using the artificial neural network 97.973% classification success was achieved, whereas the classification success for random forest and k-nearest neighbour model were 97.297% and 96.306%, respectively. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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