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Artificial Neural Network Modeling of Healthy Risk Level Induced by Aircraft Pollutant Impacts around Soekarno Hatta International Airport 被引量:1
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作者 salah khardi Jermanto Setia Kurniawan +1 位作者 Irwan Katili Setyo Moersidik 《Journal of Environmental Protection》 2013年第8期28-39,共12页
Aircraft pollutant emissions are an important part of sources of pollution that directly or indirectly affect human health and ecosystems. This research suggests an Artificial Neural Network model to determine the hea... Aircraft pollutant emissions are an important part of sources of pollution that directly or indirectly affect human health and ecosystems. This research suggests an Artificial Neural Network model to determine the healthy risk level around Soekarno Hatta International Airport-Cengkareng Indonesia. This ANN modeling is a flexible method, which enables to recognize highly complex non-linear correlations. The network was trained with real measurement data and updated with new measurements, enhancing its quality and making it the ideal method for this research. Measurements of aircraft pollutant emissions are carried out with the aim to be used as input data and to validate the developed model. The obtained results concerned the improved ANN architecture model based on pollutant emissions as input variables. ANN model processes variables—hidden layers—and gives an output variable corresponding to a healthy risk level. This model is characterized by a 4-10-1 scheme. Based on ANN criteria, the best validation performance is achieved at epoch 28 from 34 epochs with the Mean Squared Error (MSE) of 9 × 10-3. The correlation between targets and outputs is confirmed. It validated a close relationship between targets and outputs. The network output errors value approaches zero. Further research is needed with the aim to enlarge the scheme of the ANN model by increasing its input variables. This is one of the major key defining environmental capacities of an airport that should be applied by Indonesian airport authorities. These would institute policies to manage or reduce pollutant emissions considering population and income growth to be socially positive. 展开更多
关键词 AIRCRAFT POLLUTANT Emissions Artificial Neural Network HEALTHY Risk Level
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Road traffic nanoparticle characteristics:Sustainable environment and mobility
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作者 Ines Belkacem Ali Helali +2 位作者 salah khardi Amani Chrouda Khalifa Slimi 《Geoscience Frontiers》 SCIE CAS CSCD 2022年第1期388-403,共16页
Human effects and environment impacts associated with nanoparticles generated from road traffic have recently attracted wide attention.Knowledge of the influencing variables on both number and mass of nanoparticles,so... Human effects and environment impacts associated with nanoparticles generated from road traffic have recently attracted wide attention.Knowledge of the influencing variables on both number and mass of nanoparticles,sources,characteristics and limitations of advanced commercially accessible instruments for monitoring nanoparticles,are still scarce and not sufficient to make regulatory decision on solid particles smaller than 23 nm(SPN<23 nm).Given the harmful effects of nanoparticles on human health(i.e.visibility impairment,cardiac-rhythm disturbance,heart attacks,premature death,etc.),their control and assessment seem to be an absolute priority.In this overview,we classify and analyze the existing knowledge of nanoparticles in road traffic atmosphere,recent progress,and emerging priorities in research related to these topics.The major aspects of ongoing research in this field,and a brief discussion of the main sources of atmosphere nanoparticles are presented.The subsequent section focuses on the influencing parameters of nanoparticles including climate conditions,height above the road surface and distance between source(road traffic)and sampling site.The next section provides a comprehensive summary on sampling measurement methodologies and instrumental techniques.We also review the health and environment implications associated with particle exposure.Finally,an evaluation of the state of research related to nanoparticles together with highlights for future research activities are also presented. 展开更多
关键词 Road traffic NANOPARTICLES Sustainable environment Air pollution HEALTH
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An Efficient Non-Linear Application Algorithm Predictive Model for a Multi Aircraft Landing Dynamic System <i>AIRLADYS R</i>2019<i>A</i><sup>+</sup>
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作者 Fulgence Nahayo salah khardi 《Open Journal of Optimization》 2020年第2期15-26,共12页
The aim of this paper is to set up an efficient nonlinear application algorithm predictive model for a multi aircraft landing dynamic system called “Aircraft Landing Dynamic System, Release 2019<em>A</em>... The aim of this paper is to set up an efficient nonlinear application algorithm predictive model for a multi aircraft landing dynamic system called “Aircraft Landing Dynamic System, Release 2019<em>A</em><sup>+</sup> version “<em>AIRLADYS R</em>2019<em>A</em><sup>+</sup>”. This programming software combines dynamic programming technic for mathematical computing and optimisation run under AMPL and KNITRO Solver. It uses also a descriptive programming technic for software design. The user interfaces designed in Glade are saved as XML, and by using the GtkBuilder GTK+ object these can be loaded by applications dynamically as needed. By using GtkBuilder, Glade XML files can be used in numerous programming languages including C, C++, C#, Java, Perl, Python, AMPL, etc. Glade is Free Software released under the GNU GPL License. By these tools, the solved problem is a mathematical modelization problem as a non-convex optimal control governed by ordinary non-linear differential equations. The dynamic programming technic is applied because it is a sufficiently high order and it does not require computation of the partial derivatives of the aircraft dynamic. This application will be coded with Linux system on 64 bit operating system, but it can also be run on the windows system. High running performances are obtained with results giving feasible trajectories with a robust optimizing of the objective function. 展开更多
关键词 Glade Software Aircraft Dynamic System Optimal Control System Dynamic Programming GUI GPL Application AIRLADYS R2019A+
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