Efficient Model Selectionn Through Standard Operating Procedure Using Hybrid Of Sparse And Robust Estimators
The Internet of Things (IoT) is becoming more critical as time passes by. The use of IoT-related products helps to reduce human effort and can provide the highest possible quality at a minimum of time. Solar dryer is one of the uses of IoT in the agricultural sector for the drying of goods. This stu...
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| Format: | Thesis |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://eprints.usm.my/52547/1/Pages%20from%20Final%20thesis%20file%20with%20password.pdf |
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| Summary: | The Internet of Things (IoT) is becoming more critical as time passes by. The use of IoT-related products helps to reduce human effort and can provide the highest possible quality at a minimum of time. Solar dryer is one of the uses of IoT in the agricultural sector for the drying of goods. This study focuses on the identification of factors affecting the collector’s solar dryer efficiency and the removal of seaweed moisture ratio. The Standard Operational Procedure (SOP) is provided on the basis of four Phases for this purpose. A hybrid model based on a sparse and robust regression analysis is intended for this purpose. Six types of hybrid estimators are developed using sparse and robust estimators and the best combination is selected for the medium and large data set. Interaction effects in all possible models are primarily addressed in this study. |
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