Coupling Gaussian generalised regression neural network and mutable smart bee algorithm to analyse the characteristics of automotive engine coldstart hydrocarbon emission-Reference-Cited by-同舟云学术

Coupling Gaussian generalised regression neural network and mutable smart bee algorithm to analyse the characteristics of automotive engine coldstart hydrocarbon emission

Published:2014-07-03 Issue:3 Volume:27 Page:253-272
ISSN:0952-813X
Container-title:Journal of Experimental & Theoretical Artificial Intelligence
language:en
Short-container-title:Journal of Experimental & Theoretical Artificial Intelligence

Author:

Mozaffari Ahmad,Azad Nasser L.

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Theoretical Computer Science,Software

Link

http://www.tandfonline.com/doi/pdf/10.1080/0952813X.2014.924588

Reference31 articles.

1. Determining Model Accuracy Requirements for Automotive Engine Coldstart Hydrocarbon Emissions Control

2. Chaotic particle swarm optimization for data clustering

3. Modeling a shape memory alloy actuator using an evolvable recursive black-box and hybrid heuristic algorithms inspired based on the annual migration of salmons in nature

4. Recurrent neural network training for energy management of a mild Hybrid Electric Vehicle with an ultra-capacitor

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3. Calibration of catalyst temperature in automotive engines over coldstart operation in the presence of different random noises and uncertainty: Implementation of generalized Gaussian process regression machine;Frontiers of Mechanical Engineering;2015-09-02

4. Online optimization of automotive engine coldstart hydrocarbon emissions control at idle conditions;Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering;2015-08-14

5. A robust time delay auto-regressive exogenous fuzzy inference system for real-time estimation of catalyst temperature over engines coldstart operation: a multiobjective implementation scenario;International Journal of Dynamics and Control;2014-10-11