# Seasonal Shifts and Smart Stats: Improving Biodrying in Waste Management
## 4 Results
### Influence of Amount of Waste Loaded into the Bioboxes on Drying Efficiency  
Figure 4 illustrates the relationship between the amount of waste filled into the bioboxes and the resulting drying efficiency. In the left panel, the scatter plot illustrates the relationship between the amount of waste filled into the bioboxes and drying efficiency (%). Each data point represents an observation, revealing the distribution and variability of drying efficiency across different input volumes. The plot highlights a general trend where higher tonnage corresponds to slightly improved drying efficiency, though the variation in data points suggests other  
Figure 4: Scatter plots illustrating the relationship between the amount of waste filled into bioboxes and drying efficiency. The left panel shows the distribution of data points, while the right panel includes a fitted linear regression line (slope = 0.59), indicating that for every additional ton of waste filled, drying efficiency increases by approximately 0.59%. A moderate positive correlation (r = 0.41) is observed, suggesting that larger waste loads are associated with slightly higher drying efficiencies. Figure 3: Boxplot showing the distribution of drying efficiency across 12 bioboxes. The boxes represent the interquartile range (IQR), the horizontal line within each box represents the median (50 th percentile), and the whiskers indicate the range of values within 1.5 times the IQR. Small circles represent outliers, which are values that fall outside this range, observed for certain bioboxes due to variability in the drying efficiency data. While slight variations in efficiency are observed, an ANOVA test confirms no statistically significant differences in performance among the bioboxes, indicating consistent operation. factors may also contribute to this relationship. In the right panel, the scatter plot includes a linear regression line that quantifies the relationship between tonnage filled and drying efficiency (%). The regression line, derived from a statistical model, demonstrates a positive trend, indicating that drying efficiency increases slightly as the amount of waste filled into the bioboxes rises. The regression analysis reveals a moderate positive correlation (r = 0.41) with a statistically significant relationship (\(p\) < 0.00001), suggesting that higher input tonnage contributes to slightly improved drying efficiency. This improvement is likely due to enhanced heat retention and thermal dynamics during the biodrying process, which are more effective in larger waste loads. Together, these visualizations offer a clear depiction of the interaction between waste tonnage and process efficiency, providing critical insights for optimizing biobox loading strategies in biodrying operations. A multiple linear regression model was constructed to predict drying efficiency based on the following three key predictors: the amount of waste loaded into the bioboxes (\"Loaded (t)\"), the biobox number, and the month of operation. The target variable was the percentage of water removed during the biodrying process. To ensure a robust evaluation of the model, the dataset was divided into training (80%) and testing (20%) subsets. The regression equation derived from the analysis is as follows:  
\[Dry.effici.(\%)=0.46*(Loaded\;(t))-0.034*(Biobox\;no.)-0.36*(Month)+49.96 \tag{3}\]  
The analysis produced an R-squared value (R2) of 0.25, indicating that the model explains 25% of the variability in drying efficiency (\"_Dry. Effic._\"). While this suggests some predictive power, a significant portion of the variability remains unexplained, pointing to the influence of additional factors not included in the model. The Mean Squared Error (MSE) of 34.90 reflects the average squared difference between the predicted and actual drying efficiencies. Among the predictors, \"_Loaded (t)_\" had the strongest positive influence, with a coefficient of 0.46. This indicates that for every additional ton of waste filled, drying efficiency increased by approximately 0.46%.