# Lunar Calendar Usage to Improve Forecasting Accuracy Rainfall via Machine Learning Methods
## 1 Introduction  
The forecasting of time-series data, particularly on a monthly scale, is integral to various sectors, including agriculture, disaster management, and environmental planning. Adjustments to the number of days in a month, whether in the Gregorian or lunar calendar, can influence the accuracy of forecast results [1, 2]. Therefore, using the appropriate calendar system for forecasting can lead to more accurate seasonal projections and monthly trends [3]. Additionally, precise monthly forecasting is essential for planning and decision-making, such as disaster mitigation in cases of extreme rainfall [4]. In agriculture, accurate forecasts are especially valuable for the early planning of planting seasons [5, 6, 7]. In the environmental field, accurate rainfall forecasting is necessary to anticipate disasters such as floods and landslides [8]. Rainfall significantly impacts construction projects by causing delays, increasing safety risks, and affecting material integrity [9, 10, 11, 12]. Accurate rainfall forecasting is necessary for effective project planning and risk management in construction. By predicting rainfall more accurately, construction managers can adjust schedules to avoid delays and allocate resources effectively. This not only ensures the safety of workers but also helps maintain the integrity of materials used in construction. Thus, integrating accurate rainfall forecasts into construction planning is crucial for minimizing disruptions and costs. Artificial intelligence in virtual design and construction (VDC) enhances these forecasts, allowing for better scheduling and resource allocation [13; 14]. The present status of AI in VDC shows promising improvements in predictive modeling and real-time data integration. These advancements enable construction managers to make informed decisions based on accurate weather predictions. Future challenges include further refining these models for greater accuracy and expanding their applications to anticipate and mitigate weather-related disruption in construction [14]. By addressing these challenges, the construction industry can better prepare for and respond to the impacts of rainfall, ensuring safer and more efficient project execution. In rainfall forecasting, Gregorian and Lunar calendars are two of the world's most widely used calendar systems, offering distinct advantages and challenges for time-series analysis. Both have an impact on the analysis and prediction of time-series data [15]. The Gregorian calendar, based on the solar cycle, enables consistent scheduling, particularly in the context of international business [16]. In contrast, the lunar calendar, which follows the lunar cycle, is commonly used to plan religious events in Asian and Middle Eastern countries [17; 18]. These differences between calendar systems can impact how we forecast seasonal phenomena, such as rainfall or consumption patterns [19]. While both calendar systems provide frameworks for structuring time, their impact on forecasting methodologies varies significantly. The Gregorian calendar's fixed solar cycle aligns with statistical tools and international standards, making it the default choice for most predictive models [20; 21]. However, this alignment can overlook certain seasonal cycles that follow lunar patterns, which are particularly relevant in regions where agricultural or climatic phenomena depend on the lunar calendar. Integrating these unique temporal patterns into forecasting models can yield deeper insights, especially for predicting rainfall and other periodic events. This highlights the importance of tailoring forecasting approaches to the calendar system that is best suited to the natural cycles under study. The Gregorian calendar is commonly used to model and forecast rainfall levels in various countries. It serves as the basis for modeling time-series data in several statistical models [22; 23].