T Suganya
Dados Biográficos
| ID | 8419976 |
|---|---|
| NOME | T Suganya |
| PRENOMES | T |
| SOBRENOME | Suganya |
| ASSINATURA | SUGANYA T |
| AFILIAÇÕES | University of Moratuwa |
| VERIFICADO | Não |
| TOTAL DE OBRAS | 2 |
| TOTAL DE CITAÇÕES | 0 |
| TOTAL COMO AUTOR | 2 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2022 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 0 |
Assessment of Long-Term Residential Satisfaction of Postdisaster Resettled Communities
Millions of people are displaced globally due to natural hazards, conflicts, and development projects, necessitating resettlement processes that often fail to meet long-term community needs. This study aims to evaluate the long-term residential satisfaction of postdisaster resettled communities and propose actionable improvement strategies. A mixed-methods approach was employed, combining quantitative and qualitative data. Quantitative data were …
Machine learning based prediction of house price
Getting a house of our wishes within our budget in a residential area of our customization is quite a tedious process. In order to overcome this, we have developed a model to get a houses of our interest with religious belief and budget this Implemented model is of linear regression and k nearest neighbor’s algorithm with gradient descent optimization to make an optimal model for predicting house prices using the dataset. Performed feature engine…
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Machine learning based prediction of house price
Getting a house of our wishes within our budget in a residential area of our customization is quite a tedious process. In order to overcome this, we have developed a model to get a houses of our interest with religious belief and budget this Implemented model is of linear regression and k nearest neighbor’s algorithm with gradient descent optimization to make an optimal model for predicting house prices using the dataset. Performed feature engine…
Assessment of Long-Term Residential Satisfaction of Postdisaster Resettled Communities
Millions of people are displaced globally due to natural hazards, conflicts, and development projects, necessitating resettlement processes that often fail to meet long-term community needs. This study aims to evaluate the long-term residential satisfaction of postdisaster resettled communities and propose actionable improvement strategies. A mixed-methods approach was employed, combining quantitative and qualitative data. Quantitative data were …
Algorithm (1 obras) · Artificial Intelligence (1 obras) · Artificial neural network (1 obras) · Community development (1 obras) · Computer Science (1 obras) · Data mining (1 obras) · Economics (1 obras) · Engineering (1 obras) · Feature (linguistics (1 obras) · Feature selection (1 obras)