Investigating the Correlation between Cognition and Emotion Charateristics and Judgmental Time-Series Forecasting Using a Self-Organizing Neural Network

자기조직 신경망을 이용한 인지 및 감성 특성의 직관적 시계열 예측과의 상관성 조사

Though people frequently rely on intuition in managing activities, they rarely use it in developing effective decision-making support systems. In this report, we investigate the correlations between characteristics of cognition and emotion and judgmental time-series forecasting accuracy, and compare their strengths by using a self-supervised adaptive neural network. Through the experiments, we hope to help find a desirable atmosphere for decision-making. Our experiments showed that both cognition characteristics and emotion characteristics had correlations with the time-series forecasting accuracy, and that cognition characteristics had larger correlation than emotion characteristics. We also found that conceptual style had larger correlation than behavioral or analytical styles with the accuracy.