A novel assessment and forecasting system for traffic accident economic loss caused by air pollution
Authors:
- 30 April 2021
- journal article
- research article
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 28 (35) , 49042-49062
Abstract
Air pollution greatly reduces the visibility of the air, leading to frequent traffic accidents (TA), and the resulting economic losses cannot be ignored. In order to better control and mitigate the traffic accident economic losses of air pollution, this paper proposes a novel assessment and forecasting system for TA economic loss of air pollution, which contains assessment module and forecasting module. In the assessment module, a reasonable assessment of TA economic loss is provided which also analyzes the efficiency of air pollution control based on data envelope analysis directional distance function. In the forecasting module, this system develops a rolling nonlinear optimized initial self-adapting grey model based on multi-objective optimization algorithm to forecast the TA economic loss of air pollution. The results from the proposed system indicate that the proposed system has outstanding performance which can provide great information assistant for a decision-maker.Keywords
This publication has 45 references indexed in Scilit:
- Non-iterative procedure incorporated into the fuzzy identification on a hybrid method of functional randomization for time series forecasting modelsApplied Soft Computing, 2019
- Pathways to sustainable urban mobility in developing megacities: A socio-technical transition perspectiveTechnological Forecasting and Social Change, 2019
- A novel self-adapting intelligent grey model for forecasting China's natural-gas demandEnergy, 2018
- Harmonic analysis of hybrid renewable microgrids comprising optimal design of passive filters and uncertaintiesElectric Power Systems Research, 2018
- Multi-step-ahead crude oil price forecasting using a hybrid grey wave modelPhysica A: Statistical Mechanics and its Applications, 2018
- Do undesirables matter on the examination of banking efficiency using stochastic directional distance functionsThe Quarterly Review of Economics and Finance, 2017
- A PSO based virtual sample generation method for small sample sets: Applications to regression datasetsEngineering Applications of Artificial Intelligence, 2017
- Multi-output profit efficiency and directional distance functionsOmega, 2016
- Productivity and Undesirable Outputs: A Directional Distance Function ApproachJournal of Environmental Management, 1997
- Control problems of grey systemsSystems & Control Letters, 1982