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A wavelet-based 21-point model for vehicle noise feature extraction was established, as was a NN model.
For that purpose, Euler Lagrange equation is used to obtain a mathematical model for vehicle active suspension system.
A hybrid algorithm based on the artificial immune system is also proposed to solve the model for vehicle routing problem with interval demands.
Thus a hybrid model for vehicle frame system is established and successfully validated via a dummy vehicle riding in different conditions.
An improved model for vehicle routing problem proposed by Heung-Suk Hwang (2002) was recently published in Computer & Industrial Engineering Journal to solve the time constraint vehicle routing problem based on improved genetic algorithm.
The purpose of the paper is to develop a combinational disruption recovery model for vehicle routing problem with time windows (VRPTW), trying to handle a variety and a combination of delivery disruption events.
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We analyze this concept from an economic perspective by developing and evaluating a business model for vehicle-grid integration.
In this study, a discretionary cut-in risk model for vehicles is developed on the basis of field driving data and machine learning methods, namely, decision trees and Support Vector Machine (SVM).
Based on a fuel cell system model for vehicles, OER performance was analyzed for different stack currents and temperatures in this paper, and the results show that the optimal OER was affected weakly by the stack temperature.
Based on a fuel cell model for vehicles, the relation between OER and net power under various stack currents, and the relation between OER and stack temperature were analyzed.
Mathematical models for vehicle movement and sensor behavior are developed.
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