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Introducing Prior Knowledge for a Hybrid Accident Prediction Model
Ali Mansour Khaki,Abolfazl Karimpour,Hadi Sadoghi Yazdi 대한토목학회 2017 KSCE JOURNAL OF CIVIL ENGINEERING Vol.21 No.5
This study aims to address two potential issues regarding accident prediction models. (a) What are the benefits of using the prior information on the accuracy of prediction model, and (b) how to include the available prior knowledge of accident occurrences data in the prediction process? In accident databases, the prior knowledge can be defined as the most probable points in which an accident has happened in the earlier years and is closely correlated to its upcoming years. Large databases such as traffic and accident databases, inevitably contain noisy data. Therefore, to have accurate results, using approaches to alleviate the impact of these anomalies is significant. In this research, a hybrid method based on a module of prediction and a prior knowledge block is proposed. The module used for prediction is Recursive Least Square filter and Maximum a Posterior (MAP) estimator is used as the prior knowledge block. Results indicate an increase in accuracy of prediction by using the proposed hybrid model.
Soroush Maghsoudy,Ali Mansour Khaki,Barat Mojaradi,Behrooz Ghobadipour,Fereydoun Naghibi 한국자원공학회 2015 Geosystem engineering Vol.18 No.2
This article describes the application of a well-known multi-criteria decision-making technique called analytical hierarchy process (AHP) to locate emergency medical service (EMS) along US interstate highway I-65 from Montgomery to Birmingham, Alabama. Five weighting methods were applied, including Row Sum, Column Sum, Arithmetic Average, Geo-Mean, and Eigen Vector to determine weights of criteria. A number of experts were asked to evaluate the importance of selected criteria according to a nine-point scale (the Saaty rating scale). Afterwards, a weighted overlay method was applied to evaluate pixel adequacy and to identify areas with highest potential to establish the EMS along the road. After that all alternatives were ranked with the AHP method, and finally, sensitivity analysis of criteria weights was performed. The proposed method shows that locating EMS stations is very sensitive to Distance to City, Distance to Intersection, and Distance to Police Station criteria weights, and it should be considered in selecting experts and criteria weighting process.