The Genetic algorithm comprises the steps of : a) Generate initial population b) Evaluate the fitness value of each chromosome from the current population; c) Apply crossover and mutation to generate new population; d) Apply crossover and mutation to generate new population; e) Evaluate fitness of new generation; f) Repeat the process until a termination criterion is met. The genetic algorithm has an optimal value obtained is 0.000585, which is better than the 0.0022336 obtained. The algorithm helped in improving the result by reducing the error by 0.0016486. The proposed method gave an optimal value of 0.000105, and hence, the proposed algorithm helped in improving the result by 10-1
Application ID | 202211026916 |
Invention Field | COMPUTER SCIENCE |
Date of Application | 2022-05-10 |
Publication Number | 19/2022 |
Name | Address | Country | Nationality |
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Apeejay Stya University | Apeejay Stya University, Sohna - Palwal Road, Sohna - 122103, Gurugram, Haryana | India | India |
Name | Address | Country | Nationality |
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Moin Uddin | Professor Emeritus and Chief Mentor Research, Department of Computer Science and Engineering, School of Engineering and Technology, Apeejay Stya University, Gurugram, Haryana, INDIA | India | India |
Chhavi Mangla | Research Scholar, Department of Applied Sciences and Humanities, Jamia Millia Islamia, New Delhi | India | India |
Musheer Ahmad | Professor, Department of Computer Science and Engineering, School of Engineering Sciences & Technology, Jamia Hamdard, New Delhi | India | India |
Name | Date |
202211026916-POWER OF AUTHORITY [10-05-2022(online)].pdf | 2022-05-10 |
202211026916-FORM-9 [10-05-2022(online)].pdf | 2022-05-10 |
202211026916-FORM 1 [10-05-2022(online)].pdf | 2022-05-10 |
202211026916-DRAWINGS [10-05-2022(online)].pdf | 2022-05-10 |
202211026916-COMPLETE SPECIFICATION [10-05-2022(online)].pdf | 2022-05-10 |
Applicant | Section | Controller | Decision Date | URL |