A fuzzy expert system for earthquake prediction, case study: the Zagros range
원문 초록
A methodology for the development of a fuzzy expert system (FES) with application to earthquake prediction is presented. The idea is to reproduce the performance of a human expert in earthquake prediction. To do this, at the first step, rules provided by the human expert are used to generate a fuzzy rule base. These rules are then fed into an inference engine to produce a fuzzy inference system (FIS) and to infer the results. In this paper, we have used a Sugeno type fuzzy inference system to build the FES. At the next step, the adaptive network-based fuzzy inference system (ANFIS) is used to refine the FES parameters and improve its performance. The proposed framework is then employed to attain the performance of a human expert used to predict earthquakes in the Zagros area based on the idea of coupled earthquakes. While the prediction results are promising in parts of the testing set, the general performance indicates that prediction methodology based on coupled earthquakes needs more investigation and more complicated reasoning procedure to yield satisfactory predictions.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Earthquake magnitude prediction in Hindukush region using machine learning techniques
Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins
Cautious Next Token Prediction
Where, What, Why: Towards Explainable Driver Attention Prediction
Out-of-Distribution Semantic Occupancy Prediction
Demystifying Distributed Training of Graph Neural Networks for Link Prediction
토론
이 논문과 연결된 포럼 글이 아직 없습니다.