Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội
➤ Gửi thông báo lỗi ⚠️ Báo cáo tài liệu vi phạmNội dung chi tiết: Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội
Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội
HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER’S GRADUATION THESISPM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decod Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội der ModelNGUYEN MINH H1EU hieu.nm202511 in@sis.husi.edu. VIIMajor: Data Science and Artificial IntelligenceThesis advisor:Institute:Dr. Nguyen Phi Le---------------School of Information and Communication Technology1Graduation Thesis AssignmentName: Nguyen Minh HieuPhone:Email: hieu.nm202511m@sis.hus Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội t.edu.vnClass: 20BKHDL-EAffiliation : Hanoi University of Science and TechnologyI - Nguyen Minh Hieu - hereby warrants that the work and presentationLuận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội
in this thesis performed by myself under the supervision of Dr. Nguyen Phi Le. All the results presented in this thesis are truthful and are not copieHANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER’S GRADUATION THESISPM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decod Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội hy. I will take full responsibility for even one copy that violates school regulations.Hanoi, 28th September, 2021AuthorAttestationofNguyen Minh Hieu thesisadvisor:Hanoi, 28th September, 2021Thesis AdvisorDr. Nguyen Phi LecmentsFirst of all, 1 would like to deeply thank my family, especially my pare Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội nts - who have worked hard to raise me. My parents have always been with me and created the best3conditions for me to have all the necessities neededLuận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội
for my studies. Parents are the spiritual fulcrum, helping me to have a springboard to overcome difficulties and challenges.1 would like to express myHANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER’S GRADUATION THESISPM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decod Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội who has guided me from the first day I worked with her. Moreover, 1 would like to thank Dr. Nguyen Thanh Hung, who has spent his precious time supporting, giving me advice and along with Dr. Nguyen Phi Le, giving me opportunities to work in many amazing projects.My sincere thanks also go to all the Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội people in the ICN laboratory of the BK.A1 center. I have a wonderful time working with talented and special peers. 1 learned a lot from them and theyLuận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội
always spread positive energy for me.Finally, I would like to thank my friends who have always stood by me, shared joys and sorrows, and always supporHANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER’S GRADUATION THESISPM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decod Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội 5 micrometers and smaller, is a vital air quality index. Such particles can penetrate deep into the human lungs and severely affect human health. This paper studies accurate PM2.5 prediction, which can potentially contribute to reducing or avoiding the negative consequences. Our approach’s novelty i Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội s to utilize the genetic algorithm (GA) and an encoder-decoder (E-D) model for PM2.5 prediction. The GA benefits feature selection and remove outliersLuận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội
to enhance the prediction accuracy. The encoder-decoder model with long short-term memory' (LSTM), which relaxes the restrictions between the input aHANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER’S GRADUATION THESISPM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decod Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội and Taiwan. The evaluation results show that our model achieves excellent performance. By merely using the E-D model, we can obtain more accurate (up to 53.7%) predictions than those of previous works. Moreover, the GA in our model has the advantage of obtaining the optimal feature combination for p Luận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội redicting the PM2.5 concentration. By combining the GA-based feature selection algorithm and the E-D model, our proposed approach further improves theLuận văn tốt nghiệp thạc sĩ tiếng Anh Đại học Bách Khoa Hà Nội
accuracy by at least 13.7%.4HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER’S GRADUATION THESISPM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-DecodHANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER’S GRADUATION THESISPM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-DecodGọi ngay
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