國立臺灣科技大學營建工程系資料基準:2026年7月

工程AI與後設啟發式資源

保存原網站彙整之人工智慧、資料科學、最佳化方法、軟體、資料集與工程資訊學資源。

資料整合原則: 本頁依原網站完整資料重整,保留原始名稱、年代與語言以利查考;若與新版摘要數據不同,以2026年7月28日送印版申請書及新版頁面為準。

AI-Inspired Metaheuristic Algorithms for Intelligent Engineering Optimization

Advancing next-generation engineering solutions through creative computational intelligence, innovative algorithm design, and data-driven optimization for smart, resilient, and adaptive infrastructure systems.

My research program focuses on the development of AI-inspired metaheuristic algorithms and their application to complex engineering optimization problems. Drawing inspiration from nature, human behavior, cultural practices, and scientific inquiry, we design novel optimization frameworks—such as JSO, FBI, PWO, ATO, AEIO, ED, SAPSO, AAA, and others—that advance both the theoretical foundations and practical capabilities of computational intelligence. These algorithms empower innovative solutions in structural design, civil infrastructure systems, geotechnical assessment, environmental risk modeling, and automated engineering decision making. Through the integration of large language models, computer vision, machine learning, and metaheuristic optimization, our work aims to enhance engineering performance, enable data-driven planning and design, and contribute to the next generation of smart, resilient, and adaptive engineering systems.