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Mohammad H. Nadimi-Shahraki, Zahra Asghari Varzaneh, Hoda Zamani and Seyedali Mirjalili
Feature selection is an NP-hard problem to remove irrelevant and redundant features with no predictive information to increase the performance of machine learning algorithms. Many wrapper-based methods using metaheuristic algorithms have been proposed to...
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José Manuel Porras, Juan Alfonso Lara, Cristóbal Romero and Sebastián Ventura
Predicting student dropout is a crucial task in online education. Traditionally, each educational entity (institution, university, faculty, department, etc.) creates and uses its own prediction model starting from its own data. However, that approach is ...
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Shiqi Shen, Hui Wang, Yaojing Feng, Mengqiu Li and Yichang Zhong
In this paper, a predictive phase current control (PCC) scheme based on a local linear phase voltage model for a switched reluctance motor is proposed. The current is controlled by regulating the average voltage through PWM, ensuring a fixed switching fr...
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Kwang Hyeon Kim, Woo-Jin Choi and Moon-Jun Sohn
This study aimed to analyze feature importance by applying explainable artificial intelligence (XAI) to postural deformity parameters extracted from a computer vision-based posture analysis system (CVPAS). Overall, 140 participants were screened for CVPA...
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Suhwan Lee, Marco Comuzzi and Nahyun Kwon
The development of models for process outcome prediction using event logs has evolved in the literature with a clear focus on performance improvement. In this paper, we take a different perspective, focusing on obtaining interpretable predictive models f...
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