In the structure of ANFIS, there are two different parameter groups: premise and
consequence. Training ANFIS means determination of these parameters using an …

With the rapid growth in foreign trade business and the continuous expansion of customs
functions, the amount of data obtained by customs monitoring systems has drastically …

Adaptive Neuro‐Fuzzy Inference System (ANFIS) blends advantages of both Artificial Neural
Networks (ANNs) and Fuzzy Logic (FL) in a single framework. It provides accelerated …

Air pollution is increasing for many reasons, such as the crowding of cities, the failure of
planning to consider the benefit of society and nature, and the non-implementation of …

Estimating cognitive workload levels is an emerging research topic in the cognitive
neuroscience domain, as participants' performance is highly influenced by cognitive …

Steady-state visual evoked potential (SSVEP) is one of the most popular neural patterns
used to develop brain-computer interface (BCI). To address the issue of …

In order to detect human operator performance degradation or breakdown, this paper
proposes an adaptive support vector machine-based method to classify operator mental …

In recent years, multivariate synchronization index (MSI) algorithm, as a novel frequency
detection method, has attracted increasing attentions in the study of brain-computer …

Miners' unsafe behavior is the main cause of accidents in coal mines, and unsafe state have
an important influence on unsafe behavior among miners. To minimize accidents from the …

This paper proposed two psychophysiological-data-driven classification frameworks for
operator functional states (OFS) assessment in safety-critical human-machine systems with …