A Methodology for Calculating Greenhouse Effect of Aircraft Cruise Using Genetic Algorithm-Optimized Wavelet Neural Network
Reliable assessment on the environmental impact of aircraft operation is vital for the performance evaluation and sustainable development of civil aviation. A new methodology for calculating the greenhouse effect of aircraft cruise is proposed in this paper. With respect to both cruise strategies an...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/7141320 |
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| _version_ | 1832560185449644032 |
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| author | Yong Tian Lina Ma Songtao Yang Qian Wang |
| author_facet | Yong Tian Lina Ma Songtao Yang Qian Wang |
| author_sort | Yong Tian |
| collection | DOAJ |
| description | Reliable assessment on the environmental impact of aircraft operation is vital for the performance evaluation and sustainable development of civil aviation. A new methodology for calculating the greenhouse effect of aircraft cruise is proposed in this paper. With respect to both cruise strategies and wind factors, a genetic algorithm-optimized wavelet neural network topology is designed to model the fuel flow-rate and developed using the real flight records data. Validation tests demonstrate that the proposed model with preferred network architecture can outperform others investigated in this paper in terms of accuracy and stability. Numerical examples are illustrated using 9 flights from Beijing Capital International Airport to Shanghai Hongqiao International Airport operated by Boeing 737–800 aircraft on October 2, 2019, and the generated fuel consumption, CO2 and NOx emissions as well as temperature change for different time horizons can be effectively given through the proposed methodology, which helps in the environmental performance evaluation and future trajectory planning for aircraft cruise. |
| format | Article |
| id | doaj-art-68f7540b6adb4f8fb15ffa3bc8234d1a |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-68f7540b6adb4f8fb15ffa3bc8234d1a2025-02-03T01:28:10ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/71413207141320A Methodology for Calculating Greenhouse Effect of Aircraft Cruise Using Genetic Algorithm-Optimized Wavelet Neural NetworkYong Tian0Lina Ma1Songtao Yang2Qian Wang3College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaSchool of Mechanical Engineering, University of Leeds, Leeds, LS2 9JT, UKCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaReliable assessment on the environmental impact of aircraft operation is vital for the performance evaluation and sustainable development of civil aviation. A new methodology for calculating the greenhouse effect of aircraft cruise is proposed in this paper. With respect to both cruise strategies and wind factors, a genetic algorithm-optimized wavelet neural network topology is designed to model the fuel flow-rate and developed using the real flight records data. Validation tests demonstrate that the proposed model with preferred network architecture can outperform others investigated in this paper in terms of accuracy and stability. Numerical examples are illustrated using 9 flights from Beijing Capital International Airport to Shanghai Hongqiao International Airport operated by Boeing 737–800 aircraft on October 2, 2019, and the generated fuel consumption, CO2 and NOx emissions as well as temperature change for different time horizons can be effectively given through the proposed methodology, which helps in the environmental performance evaluation and future trajectory planning for aircraft cruise.http://dx.doi.org/10.1155/2020/7141320 |
| spellingShingle | Yong Tian Lina Ma Songtao Yang Qian Wang A Methodology for Calculating Greenhouse Effect of Aircraft Cruise Using Genetic Algorithm-Optimized Wavelet Neural Network Complexity |
| title | A Methodology for Calculating Greenhouse Effect of Aircraft Cruise Using Genetic Algorithm-Optimized Wavelet Neural Network |
| title_full | A Methodology for Calculating Greenhouse Effect of Aircraft Cruise Using Genetic Algorithm-Optimized Wavelet Neural Network |
| title_fullStr | A Methodology for Calculating Greenhouse Effect of Aircraft Cruise Using Genetic Algorithm-Optimized Wavelet Neural Network |
| title_full_unstemmed | A Methodology for Calculating Greenhouse Effect of Aircraft Cruise Using Genetic Algorithm-Optimized Wavelet Neural Network |
| title_short | A Methodology for Calculating Greenhouse Effect of Aircraft Cruise Using Genetic Algorithm-Optimized Wavelet Neural Network |
| title_sort | methodology for calculating greenhouse effect of aircraft cruise using genetic algorithm optimized wavelet neural network |
| url | http://dx.doi.org/10.1155/2020/7141320 |
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