Changes in extreme rainfall can cause disasters or losses for the wider community, so information about future is also needed. Rainfall included category of time series data. One methods that be used Autoregressive Integrated Moving Average (ARIMA) Seasonal ARIMA (SARIMA). However, this model only involves one variable without involving its dependence on other variables. factors affect wind spe...

Abstract The analysis of the high volume data spawned by web search engines on a daily basis allows scholars to scrutinize relation between user’s preferences and impending facts. This study can be used in variety economics contexts. purpose this is determine whether it possible anticipate unemployment rate examining behavior. method uses cross-correlation technique combine from Google Trends w...

Port environmental problems have gradually become the primary concern of port authorities. The future trend carbon emissions is crucial to authorities and managers in formulating regulations optimizing operation schedules. Owing limitations current prediction methods complex social–environmental impact, estimation results insufficient accuracy support development future. In this work, stochasti...

Demand forecasting is becoming increasingly important as firms launch new products with short life cycles more frequently. This paper provides a framework based on state-of-the-art techniques that enables to use quantitative methods forecast sales of newly launched, short-lived are similar previous when there limited availability historical data for the product. In addition exploiting using tim...

The objective of this research is to analyze the impact causal factors relationship over changes in future scenario management under sustainability policy Thailand by creating a model with validity called “Partial Least Square Path Modeling based on Autoregressive Integrated Moving Average Observed Variables (PLS Modeling-ARIMAx). results showed that three latent variables (economic, social, an...

The present study emphasizes the forecast of Andhra Pradesh's total marine fish production and catch commercially important fishes, viz., Indian Mackerel, Oil Sardine, Horse Lesser Sardines for next 5 years by different statistical machine learning approaches under climate change scenario. Forecasting is done with without inclusion climatic environmental parameters in models. Exogenous variable...