Predicting mental health state of an IT company environment using CNN and time-series predictions
| dc.contributor.advisor | Silva, T | |
| dc.contributor.author | Abeydeera, SS | |
| dc.date.accept | 2023 | |
| dc.date.accessioned | 2025-08-19T06:14:40Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Technology is a fascinating subject. It changes rapidly in a way that makes us curious about what new product will change the world entirely within the next few hours, days, or months. When it comes to modern technology, artificial intelligence (AI) is playing a major role in the industry. Because, with the advancement of AI, most of the complex tasks can be handled by AI systems. Apart from taking care of complex tasks, AI can help people to enhance their quality of life. In order to enhance the quality of life, people have developed smart gadgets like wearable small health measuring and prediction gadgets, recommendation systems like hairstyle recommendations, makeup recommendations, food recommendations, and so on. Apart from them, there are so many different types of applications to improve the quality of life. And another concept is emerging in the modern world. That is predicting human mental status for upcoming months and adjusting the environment accordingly to maintain good mental status. If people can make adjust the environments for their day-to-day life, it will ultimately increase the quality of everything. Within a night or two people can not achieve this hard goal. It will take many years to achieve. But researchers all around the world have been working on several kinds of applications for many years. After completing all of these small tasks in the future, people will integrate everything into one system and that could make a healthy environment for humankind. | |
| dc.identifier.accno | TH5391 | |
| dc.identifier.citation | Abeydeera, S.S. (2023). Predicting mental health state of an IT company environment using CNN and time-series predictions [Master’s theses, University of Moratuwa]. , University of Moratuwa]. Institutional Repository University of Moratuwa. https://dl.lib.uom.lk/handle/123/23980 | |
| dc.identifier.degree | MSc in Artificial Intelligence | |
| dc.identifier.department | Department of Computational Mathematics | |
| dc.identifier.faculty | IT | |
| dc.identifier.uri | https://dl.lib.uom.lk/handle/123/23980 | |
| dc.language.iso | en | |
| dc.subject | EMOTION CLASSIFICATION | |
| dc.subject | MACHINE LEARNING | |
| dc.subject | CONVOLUTIONAL NEURAL NETWORKS | |
| dc.subject | DEEP LEARNING | |
| dc.subject | STATISTICAL METHODS-Time-Series Analysis | |
| dc.subject | COMPUTATIONAL MATHEMATICS-Dissertation | |
| dc.subject | MSc in Artificial Intelligence | |
| dc.title | Predicting mental health state of an IT company environment using CNN and time-series predictions | |
| dc.type | Thesis-Abstract |
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