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Title: :  Optimizing machine learning algorithms applied to the context of intelligent vehicles
PaperId: :  15720
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 7 Issue 6 2021
DUI:    16.0415/IJARIIE-15720
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
RAMAROLAHIVONJITIANA Frédéric JoëlTASI, ED-STII, Antananarivo, Madagascar
RANDRIAMITANTSOA Paul AugusteTASI, ED-STII, Antananarivo, Madagascar
RANDRIAMITANTSOA Andry AugusteTASI, ED-STII, Antananarivo, Madagascar

Abstract

Computer Science & Engineering
Machine learning, Cost function, Lost function, Dimensionality reduction, Intelligent vehicles
Securing open networks, optimizing the performance of datacenters, and even getting more value from data are all part of the future of information technology. An important issue in its own right is the use and / or valuation of data produced and exchanged between these connected objects due to the number of nodes considered, the heterogeneity of the technologies for their connectivity, and the exponential evolution of needs expressed, given the volume of data available. Controlling and mastering connected and autonomous objects are becoming major societal and economic concerns. This has sparked intense activity in academia and industry in the area of machine learning research. Inside intelligent vehicle, machine learning algorithms are implemented in the detection, perception and decision subsystems to ensure localization, object recognition, trajectory planning, action prediction until obstacle avoidance. With the ultimate goal of optimizing these algorithms, we implemented cost functions, also called lost function, for a predictive model of a desired trajectory and motion planning. Moreover, several technics like dimensionality reduction, function approximation and model selection can be employed. We were able to determine the cost function of a cyberattack. Also, we used the dimensionality reduction technique for motion planning optimization to map the collision.

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IJARIIE RAMAROLAHIVONJITIANA Frédéric Joël, RANDRIAMITANTSOA Paul Auguste, and RANDRIAMITANTSOA Andry Auguste. "Optimizing machine learning algorithms applied to the context of intelligent vehicles" International Journal Of Advance Research And Innovative Ideas In Education Volume 7 Issue 6 2021 Page 909-923
MLA RAMAROLAHIVONJITIANA Frédéric Joël, RANDRIAMITANTSOA Paul Auguste, and RANDRIAMITANTSOA Andry Auguste. "Optimizing machine learning algorithms applied to the context of intelligent vehicles." International Journal Of Advance Research And Innovative Ideas In Education 7.6(2021) : 909-923.
APA RAMAROLAHIVONJITIANA Frédéric Joël, RANDRIAMITANTSOA Paul Auguste, & RANDRIAMITANTSOA Andry Auguste. (2021). Optimizing machine learning algorithms applied to the context of intelligent vehicles. International Journal Of Advance Research And Innovative Ideas In Education, 7(6), 909-923.
Chicago RAMAROLAHIVONJITIANA Frédéric Joël, RANDRIAMITANTSOA Paul Auguste, and RANDRIAMITANTSOA Andry Auguste. "Optimizing machine learning algorithms applied to the context of intelligent vehicles." International Journal Of Advance Research And Innovative Ideas In Education 7, no. 6 (2021) : 909-923.
Oxford RAMAROLAHIVONJITIANA Frédéric Joël, RANDRIAMITANTSOA Paul Auguste, and RANDRIAMITANTSOA Andry Auguste. 'Optimizing machine learning algorithms applied to the context of intelligent vehicles', International Journal Of Advance Research And Innovative Ideas In Education, vol. 7, no. 6, 2021, p. 909-923. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Optimizing_machine_learning_algorithms_applied_to_the_context_of_intelligent_vehicles_ijariie15720.pdf (Accessed : 28 May 2024).
Harvard RAMAROLAHIVONJITIANA Frédéric Joël, RANDRIAMITANTSOA Paul Auguste, and RANDRIAMITANTSOA Andry Auguste. (2021) 'Optimizing machine learning algorithms applied to the context of intelligent vehicles', International Journal Of Advance Research And Innovative Ideas In Education, 7(6), pp. 909-923IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Optimizing_machine_learning_algorithms_applied_to_the_context_of_intelligent_vehicles_ijariie15720.pdf (Accessed : 28 May 2024)
IEEE RAMAROLAHIVONJITIANA Frédéric Joël, RANDRIAMITANTSOA Paul Auguste, and RANDRIAMITANTSOA Andry Auguste, "Optimizing machine learning algorithms applied to the context of intelligent vehicles," International Journal Of Advance Research And Innovative Ideas In Education, vol. 7, no. 6, pp. 909-923, Nov-Dec 2021. [Online]. Available: https://ijariie.com/AdminUploadPdf/Optimizing_machine_learning_algorithms_applied_to_the_context_of_intelligent_vehicles_ijariie15720.pdf [Accessed : 28 May 2024].
Turabian RAMAROLAHIVONJITIANA Frédéric Joël, RANDRIAMITANTSOA Paul Auguste, and RANDRIAMITANTSOA Andry Auguste. "Optimizing machine learning algorithms applied to the context of intelligent vehicles." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 7 number 6 (28 May 2024).
Vancouver RAMAROLAHIVONJITIANA Frédéric Joël, RANDRIAMITANTSOA Paul Auguste, and RANDRIAMITANTSOA Andry Auguste. Optimizing machine learning algorithms applied to the context of intelligent vehicles. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2021 [Cited : 28 May 2024]; 7(6) : 909-923. Available from: https://ijariie.com/AdminUploadPdf/Optimizing_machine_learning_algorithms_applied_to_the_context_of_intelligent_vehicles_ijariie15720.pdf
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