高技术通讯2025，Vol.35Issue(7)：734-745,12.DOI:10.3772/j.issn.1002-0470.2025.07.006
基于ANFIS-MBTI的人格类型指标自动检测方法
Automatic detection method for personality type indicators based on ANFIS-MBTI
摘要
Abstract
Myers-Briggs type indicator(MBTI)is regarded as one of the most popular and reliable methods for predicting personality types.However,traditional detection approaches such as questionnaire surveys or professional consulta-tions face high human and time costs as well as potential privacy leakage risks during implementation.To address these issues,this paper proposes an MBTI classification model(ANFIS-MBTI)based on the adaptive-network-based fuzzy inference system(ANFIS).By organically integrating deep neural networks with fuzzy logic reasoning,the model can flexibly adapt to and accurately capture nonlinear,ambiguous,and uncertain features hidden in social text data through self-learning and parameter optimization strategies.This enables automatic identification of user behav-ior patterns in social media datasets,thereby revealing psychological traits and personality characteristics in informa-tion acquisition,decision-making,and behavioral patterns.Experimental results demonstrate that the proposed AN-FIS-MBTI model efficiently and accurately identifies 16 distinct MBTI personality types from social texts.Its multi-level feature fusion mechanism significantly enhances the automation level of personality classification tasks,while fuzzy rule constraints effectively control manual intervention requirements and data privacy risks,providing a scala-ble innovative technical pathway for large-scale online personality analysis.关键词
迈尔斯-布里格斯人格类型指标分类/机器学习/自适应神经模糊推理系统/模糊逻辑Key words
Myers-Briggs type indicator/machine learning/adaptive-network-based fuzzy inference system/fuzzy logic引用本文复制引用
刘昱昕,张延华..基于ANFIS-MBTI的人格类型指标自动检测方法[J].高技术通讯,2025,35(7):734-745,12.基金项目
国家自然科学基金(61901011),北京市自然科学基金(L211002)和北京市教育委员会科技计划(KM202110005021)资助项目. （61901011）
