Approach to Sustainable Development Scenario using Machine Learning Algorithms

Tarangini Mukherjee1

1

Publication Date: 2025/01/10

Abstract: The world is evolving at a fast pace but the attention to resources has been neglected by mankind for several decades. It is high time we aim at development which is sustainable and good for the present and future generation. In this paper we will be exploring how machine learning algorithms can help us choose the best materials, approach ,style, process, design for Sustainable development.

Keywords: No Keywords Available

DOI: https://doi.org/10.5281/zenodo.14613873

PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24DEC2050.pdf

REFERENCES

  1. Roopam Gupta; Thomas Rincy N; “A Survey on Machine Learning Approaches and Its Techniques,’’2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS), 2020, pp. 1-6
  2. Mikko Koho; Seppo Torvinen; Alexandre Torres Romiguer;“Objectives, enablers and challenges of sustainable development and sustainable manufacturing: Views and opinions of Spanish companies,’’ 2011 IEEE International Symposium on Assembly and Manufacturing (ISAM),2011, pp. 1-5
  3. Xinhui Yue; Yuan-Hua Ni;“Accelerated Distributed Composite Nesterov Gradient Descent Algorithm,’’2022 41st Chinese Control Conference (CCC),2022,pp. 1-5
  4. Halyna Padalko; Kseniia Bazilevych; Mykola Butkevych; “Heart Failure Development Prediction using Stochastic Gradient Descent Optimization,”2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T),2022, pp 297-300
  5. Shiyou Yan; Min Yang; “Alternating direction method of multipliers with variable stepsize for partially parallel MR image reconstruction,’’2017 36th Chinese Control Conference (CCC),2017, pp 10886 - 10889
  6. Andrey Pazderin; Sergey Yuferev,“Power flow calculation by combination of Newton-Raphson method and Newton's method in optimization,’’2009 35th Annual Conference of IEEE Industrial Electronics,2009, pp 1693 - 1696