ML Algorithm Synthesizing Domain Knowledge for Fungal Spores Concentration Prediction
The pulp and paper manufacturing industry requires precise quality control to ensure pure, contaminant-free end products suitable for various applications. Fungal spore concentration is a crucial metric that affects paper usability, and current testing methods are labor-intensive with delayed results, hindering real-time control strategies. To address this, a machine learning algorithm utilizing time-series data and domain knowledge was proposed. The optimal model employed Ridge Regression achieving an MSE of 2.90 on training and validation data. This approach could lead to significant improvements in efficiency and sustainability by providing real-time predictions for fungal spore concentrations. This paper showcases a promising method for real-time fungal spore concentration prediction, enabling stringent quality control measures in the pulp-and-paper industry.
Code (1)
Tasks
Time SeriesSimilar Papers 제목 키워드 기반
Synthetic Fungi Datasets: A Time-Aligned Approach
Fungi undergo dynamic morphological transformations throughout their lifecycle, forming intricate networks as they transition from spores to mature mycelium structures. To support the study of these time-dependent proces…
Interactions of Fungi with Concrete: Significant Importance for Bio-Based Self-Healing Concrete
The goal of this study is to explore a new self-healing concept in which fungi are used as a self-healing agent to promote calcium mineral precipitation to fill the cracks in concrete. An initial screening of different s…
X-Ray Diffraction (XRD)Leaf Tar Spot Detection Using RGB Images
Tar spot disease is a fungal disease that appears as a series of black circular spots containing spores on corn leaves. Tar spot has proven to be an impactful disease in terms of reducing crop yield. To quantify disease …
TARExploring Fungal Morphology Simulation and Dynamic Light Containment from a Graphics Generation Perspective
Fungal simulation and control are considered crucial techniques in Bio-Art creation. However, coding algorithms for reliable fungal simulations have posed significant challenges for artists. This study equates fungal mor…
Image SegmentationSemantic SegmentationTime SeriesTime Series Generation+1Spores: Stateless Predictive Onion Routing for E-Squads
Mass surveillance of the population by state agencies and corporate parties is now a well-known fact. Journalists and whistle-blowers still lack means to circumvent global spying for the sake of their investigations. Wit…