In this Letter, the Logical Jaya optimisation is proposed as an extension of the Jaya optimisation algorithm to improve the cognitive workload (CW) assessment technique where channel selection for the EEG signal act as a binary optimisation problem. Channel selection is very crucial, time-consuming and requires expertise, specially when brain cognitive load is considered. The proposed approach is designed such that it not only improves the performance of the assessment model of CW but also reduces the computational cost. The approach also helps in the automation of brain analysis. The results obtained show that performance is improved by 22% than existing approaches to an average of >90% accuracy in different scenarios. The channels obtained using the approach also provided accurate active brain regions during CW analogous to previous studies.

中文翻译：

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基于LJaya优化的信道选择方法提高认知工作量评估技术的性能

在这封信中，逻辑 Jaya 优化被提议作为 Jaya 优化算法的扩展，以改进认知工作负载 (CW) 评估技术，其中 EEG 信号的通道选择充当二元优化问题。通道选择非常关键、耗时且需要专业知识，特别是在考虑大脑认知负荷时。所提出的方法被设计为不仅提高了 CW 评估模型的性能，而且还降低了计算成本。该方法还有助于大脑分析的自动化。获得的结果表明，在不同场景下，性能比现有方法提高了 22%，平均准确率超过 90%。与以前的研究类似，使用该方法获得的通道还提供了 CW 期间准确的活跃大脑区域。