Roadway traffic crash prediction using a state-space model based support vector regression approach
نویسندگان
چکیده
منابع مشابه
Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach
Accurate wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. Particularly, reliable short-term wind speed prediction can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed....
متن کاملSupport vector regression for prediction of gas reservoirs permeability
Reservoir permeability is a critical parameter for characterization of the hydrocarbon reservoirs. In fact, determination of permeability is a crucial task in reserve estimation, production and development. Traditional methods for permeability prediction are well log and core data analysis which are very expensive and time-consuming. Well log data is an alternative approach for prediction of pe...
متن کاملEnsemble Kernel Learning Model for Prediction of Time Series Based on the Support Vector Regression and Meta Heuristic Search
In this paper, a method for predicting time series is presented. Time series prediction is a process which predicted future system values based on information obtained from past and present data points. Time series prediction models are widely used in various fields of engineering, economics, etc. The main purpose of using different models for time series prediction is to make the forecast with...
متن کاملPrediction of daily evaporation using hybrid support vector regression-firefly optimization algorithm and multilayer perceptron
Prediction of daily evaporation is a valuable and determinant tool in sustainable agriculture and hydrological issues, especially in the design and management of water resources systems. Therefore, in this study, the ability of artificial intelligence models of multi-layer perceptron (MLP), support vector regression (SVR), and the hybrid model of support vector regression-firefly optimization a...
متن کاملThe Porosity Prediction of One of Iran South Oil Field Carbonate Reservoirs Using Support Vector Regression
Porosity is considered as an important petrophysical parameter in characterizing reservoirs, calculating in-situ oil reserves, and production evaluation. Nowadays, using intelligent techniques has become a popular method for porosity estimation. Support vector machine (SVM) a new intelligent method with a great generalization potential of modeling non-linear relationships has been introduced fo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLOS ONE
سال: 2019
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0214866