GANs Applications in Chemical Engineering
9th World Conference on Soft Computing, WConSC 2024, Baku, Azerbaycan, 25 - 27 Eylül 2024, cilt.2048 LNNS, ss.113-119, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Cilt numarası: 2048 LNNS
- Doi Numarası: 10.1007/978-3-032-04803-5_14
- Basıldığı Şehir: Baku
- Basıldığı Ülke: Azerbaycan
- Sayfa Sayıları: ss.113-119
- Anahtar Kelimeler: Artificial intelligence, Chemical engineering, Generative adversarial networks
- Atatürk Üniversitesi Adresli: Evet
Özet
In the field of machine learning, Generative Adversarial Networks (GANs) have arisen as an influential tool demonstrating exceptional capabilities in generating synthetic data that closely comply with real-world samples. The last decade has seen remarkable advances in speech, image and language recognition tools that have been made available to the public through computer and mobile devices’ applications in broad area of sciences, including Chemical Engineering. In this paper, existing and future potential applications of GANs in Chemical Engineering have been given in detail. GANs have a strong potential to revolutionize in chemical engineering and its multiple subfields such as process optimization, molecular design, and materials science. Based on the searches on recent literature and case studies, generating realistic molecular structures, fault diagnosis and predicting chemical properties, optimizing process parameters, and designing novel materials are some of the GANs applications in chemical engineering. Challenges and opportunities associated with the integration of GANs into traditional chemical engineering workflows have also been discussed. Additionally, future potential applications of GANs have been examined with examples, in this paper.