Predicting the outcome of H-1B visa using ANN algorithm
Raghav Khaterpal1, Harit Ahuja2, Jatin Goel3, Karanveer Singh4, Rahul Manoj5
1Raghav Khaterpal, Department of Mechanical Engineering, Thapar Insti- tute if Engineering and Technology, Patiala, India
2Harit Ahuja, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai, India.
3Jatin Goel, Department of Information Technology, SRM Institute of Science and Technology, Kattankulathur, Chennai, India.
4Karanveer Singh, Department of Mechanical Engineering, Thapar Institute if Engineering and Technology, Patiala, India.
5Rahul Manoj, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai, India.
Manuscript received on April 30, 2020. | Revised Manuscript received on May 06, 2020. | Manuscript published on May 30, 2020. | PP: 2421-2424 | Volume-9 Issue-1, May 2020. | Retrieval Number: A2917059120/2020©BEIESP | DOI: 10.35940/ijrte.A2917.059120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: H-1B visa allows US employers to employ nonimmi- grant workers on a temporary basis. This visa only allows specialty workers to gain employment in the United States which means people who have a bachelor’s degree or equivalent work experience are eligible. The duration of H-1B visa is 3 years and it may extend to 6 years. The H-1B visa is the most sought after visa in the world, however it has a low approval rate. In 2019, 200000 people applied for the visa worldwide of which only 85000 people were selected which means an approval rate of only 42%. This fight to obtain the visa is getting more competitive as the US Economy improves. This selection depends upon a number of factors such as employer, wage etc. This paper helps to predict whether an individual can gain the H1B visa or not taking in account all the relevant factors. The proposed system secured a high accuracy of 96% by using ANN algorithm.
Keywords: ANN, One-hot encoding, H-1B visa, ReLU.
Scope of the Article: Artificial Nerul Network