Name
Title | ||
|---|---|---|
On the use of nonlinear methods for low-power CPU frequency prediction based on Android context variables |
Abstract | ||
|---|---|---|
The objective of this paper is to analyze the use of nonlinear models to predict the CPU frequency that reaches the lowest power consumption of a smartphone based on Android OS context variables. Artificial neural networks (ANNs) and k-nearest neighbors (k-NN) techniques are investigated, and their results are compared to those obtained by the linear method (LM). Experimental results indicate the k-NN technique is the best option in terms of model accuracy and performance when compared to the other prediction models. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/NCA.2016.7778627 | 2016 IEEE 15th International Symposium on Network Computing and Applications (NCA) |
Keywords | Field | DocType |
LM,k-NN,k-nearest neighbors,ANNs,artificial neural networks,Android OS context variables,smartphone,lowest power consumption,CPU frequency prediction,nonlinear methods | Central processing unit,Android (operating system),Nonlinear system,Computer science,Nonlinear methods,Artificial intelligence,Predictive modelling,Artificial neural network,Machine learning,Benchmark (computing),Humanoid robot | Conference |
ISBN | Citations | PageRank |
978-1-5090-3217-4 | 0 | 0.34 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sidartha A. L. Carvalho | 1 | 1 | 1.70 |
| D. C. Cunha | 2 | 5 | 4.46 |
| Abel Guilhermino Silva-Filho | 3 | 62 | 12.94 |