|
|
|
|
|
Jinghui Feng, Haopeng Kuang and Lihua Zhang
Feature selection can efficiently improve classification accuracy and reduce the dimension of datasets. However, feature selection is a challenging and complex task that requires a high-performance optimization algorithm. In this paper, we propose an enh...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yanping Shen, Kangfeng Zheng, Yanqing Yang, Shuai Liu and Meng Huang
Various machine-learning methods have been applied to anomaly intrusion detection. However, the Intrusion Detection System still faces challenges in improving Detection Rate and reducing False Positive Rate. In this paper, a Class-Level Soft-Voting Ensem...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jeffrey O. Agushaka and Absalom E. Ezugwu
A situation where the set of initial solutions lies near the position of the true optimality (most favourable or desirable solution) by chance can increase the probability of finding the true optimality and significantly reduce the search efforts. In opt...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ming-Wei Li, Jing Geng, Shumei Wang and Wei-Chiang Hong
Hybridizing evolutionary algorithms with a support vector regression (SVR) model to conduct the electric load forecasting has demonstrated the superiorities in forecasting accuracy improvements. The recently proposed bat algorithm (BA), compared with cla...
ver más
|
|
|
|
|
|