|
|
|
|
|
Partha Sarathi Paul, Anurag Dhungel, Maisha Sadia, Md Razuan Hossain and Md Sakib Hasan
This paper presents a general method, called ?self-parameterization?, for designing one-dimensional (1-D) chaotic maps that provide wider chaotic regions compared to existing 1-D maps. A wide chaotic region is a desirable property, as it helps to provide...
ver más
|
|
|
|
|
|
|
|
|
Yukun Wang, Lingxi Guo, Zhiming Guo, Liaoni Wu, Fuqiang Bing, Quanwen Hu and Zonghua Sun
The main focus of this article is on the jump-takeoff method for autogyros. On the basis of a high-confidence autogyro model, we design a jump-takeoff simulation experiment to study and optimize jump-takeoff performance. Using a simplified version of bla...
ver más
|
|
|
|
|
|
|
|
|
Duc-Anh Pham and Seung-Hun Han
The sliding mode controller stands out for its exceptional stability, even when the system experiences noise or undergoes time-varying parameter changes. However, designing a sliding mode controller necessitates precise knowledge of the object?s exact mo...
ver más
|
|
|
|
|
|
|
|
|
Saci Medileh, Abdelkader Laouid, Mohammad Hammoudeh, Mostefa Kara, Tarek Bejaoui, Amna Eleyan and Mohammed Al-Khalidi
In today?s hyperconnected world, the Internet of Things and Cloud Computing complement each other in several areas. Cloud Computing provides IoT systems with an efficient and flexible environment that supports application requirements such as real-time c...
ver más
|
|
|
|
|
|
|
|
|
Konstantinos Filippou, George Aifantis, George A. Papakostas and George E. Tsekouras
In this paper, we built an automated machine learning (AutoML) pipeline for structure-based learning and hyperparameter optimization purposes. The pipeline consists of three main automated stages. The first carries out the collection and preprocessing of...
ver más
|
|
|
|