… used in controls and machine learning applications. Interval … in decision-making and machine
learning, then introduces basic … applications in controls and machine learning. Finally, it …

… objectively evaluate the neural network prediction capability. The results show that, compared
with the traditional prediction method, the time-span input framework model can achieve …

… The goal of this article is to reveal the bibliographic landscape associated with humor study
in terms of neuroscience and cognitive science, and identify thematic patterns, key articles …

… Require big data processing and analysis, artificial intelligence, and machine learning 需要
大数据处理与分析,… TIV associated more with neuro AEs, including severe GBS and paralysis …

… , support vector machines (SVMs), Ensembles, Bayesians, hybrids, and neuro-fuzzy, deep
learning) are applied to provide different solutions for this sector. After energy, health, urban …

… Researches from neuroscience have demonstrated that brain activation under certain …
With the advent of deep learning, computational works are conducted to fulfill the disease …

… This study presents a novel concept for a model operating on complex data called a Complex
Number based Neuro-Fuzzy Inference System (CNNFIS). With the neural framework of …

… of neuroscience and informatics supporting the integration of various sub-disciplines (behavioural
neuroscience, … Especially the integration of neuroimaging with machine learning …