结合决策风格来预测大城市地区道路交通事故中驾驶员受伤严重程度:一种基于机器学习的方法

Q3 Engineering

International Journal of Services and Operations Management Pub Date : 2023-01-01 DOI:10.1504/ijsom.2023.10058497

M. Nasiri, Mahdi Hamid, M. Hamid, A. Ghazizadeh

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Incorporating decision-making styles to predict driver-injury severity in road accidents in a large metropolitan area: a machine-learning-based approach

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来源期刊

International Journal of Services and Operations Management Engineering-Industrial and Manufacturing Engineering

CiteScore

1.20

自引率

0.00%

发文量

期刊介绍： Globalisation of market and operations places tremendous pressure on productive management of services and manufacturing enterprises. Services are increasingly important in today''s developed economies. Nevertheless, manufacturing plays a major role in national economies and is essential for the survival of service organisations. Considering the globalisation of services and manufacturing, a journal focusing on global perspective of operations management is of paramount importance. IJSOM focuses on new strategies, techniques and technologies for improving productivity and quality in both manufacturing and services. Topics covered include: • Operations strategy in services/manufacturing, SMEs • Designing service/manufacturing enterprises, virtual enterprises • Value chain perspectives • Service blue printing • Service delivery process, performance measures/metrics • Managing capacity • Managing and measuring quality • Information technology, MRP, ERP • Human resources • Production planning and control, scheduling, JIT • Lean/agile production • Supply chain/inventory management • Product and process design • E-commerce and operations • Location and facility planning