Advancements in Machine Learning Algorithms for Generating Secure and Efficient Path

Authors

  • Prof. D. R. Kamble  Department of Computer Engineering, S. B. Patil College of Engineering, Indapur, Maharashtra, India
  • K. R. Khade  Department of Computer Engineering, S. B. Patil College of Engineering, Indapur, Maharashtra, India
  • A. L. Kharade  Department of Computer Engineering, S. B. Patil College of Engineering, Indapur, Maharashtra, India
  • Y. M. Magar  Department of Computer Engineering, S. B. Patil College of Engineering, Indapur, Maharashtra, India
  • S. R. Zagade  Department of Computer Engineering, S. B. Patil College of Engineering, Indapur, Maharashtra, India

Keywords:

Machine Learning, Graph Neural Network, Genetic Algorithm, Risk identification, Secure path, Shortest path problem, Risk assessment.

Abstract

Now days the security of person is huge concern when it travelling new regions, where People use Google map to find Shortest path to her designation. But Map are only providing Shortest path it ignores the security aspect of People. So we use trending Machine Learning technique to overcome this issue. In traditional path planning algorithm, it in this project, were view recent advances in shortest path finding incomplex graph, focusing primarily on Neural Network, Genetic Algorithm. We discuss the application of these techniques to provide Security along with Shortest path. The project’s key concept is integrating GNN model with Genetic algorithm to work on complex graphs and learning Security-related features from dataset. GNN model insights are used in Genetic algorithm to Path investigation.

References

  1. Isabel Mora,AndreaSerna,Mauricio Toro -”PREVENTION OF STREET HARASSMENT THROUGH CONSTRAINEDSHORTESTPATHALGORITHMS.”
  2. YihanKe-”Comparative Analysis of Path Planning Algorithms and Prospects for Practical Appli- cation.”
  3. JandersonFerreira, AgostinhoA.F. Junior,YvesM. Galvao,PabloBarros-”PerformanceImprove- ment of Path Planning algorithms with Deep Learning Encoder Model.”
  4. -RalphAbboud,RadoslavDimitrov,˙Ismail˙IlkanCeyla-”ShortestPathNetworksforGraphProp- erty Prediction.”
  5. B.K. Patle , Ganesh BabuL , Anish Pandey , D.R.K. Parhi , A. Jagadeesh -” A review:On path planning strategies for navigation of mobile robot.”
  6. NINGSUN1,HUIZHUSHI,GUANGJIEHAN,BINWANG1,ANDLEISHU-”DynamicPath PlanningAlgorithmsWithLoadBalancingBasedonDataPredictionforSmartTransportation Systems.”
  7. E. Hemalatha Jai Kumari , Dr.Kannammal-” Dynamic Shortest Path Routing In MobileAdhoc Networks Using Modified Artificial Bee Colony Optimization Algorithm .”
  8. Shatha Abdullah Rasheed-” SolvingShortest Path Problems UsingGenetic Algorithms.”
  9. HoussemJmal, Firas Ben Hmida, NardineBasta, Muhammad Ikram, Mohamed Ali Kaafar and AndyWalker-”SPGNN-API:ATransferableGraphNeuralNetworkforAttackPathsIdentification and Autonomous Mitigation.”
  10. Zhijian Wang , Jianpeng Yang , Qiang Zhang and Li Wang - ”Risk-Aware Travel Path Planning Algorithm Based on Reinforcement Learning during COVID-19.”
  11. Dhakane, Vikas Nivrutti, and Jalinder Nivrutti Ekatpure. "Super Resolution of License Plates Using Generalized DAMRF Image Modeling."

Downloads

Published

2023-10-30

Issue

Section

Research Articles

How to Cite

[1]
Prof. D. R. Kamble, K. R. Khade, A. L. Kharade, Y. M. Magar, S. R. Zagade, " Advancements in Machine Learning Algorithms for Generating Secure and Efficient Path" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 10, pp.57-61, September-October-2023.