![An analysis of the feasibility of SARIMAX-GARCH through load forecasting](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBbmNNIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--cd6bf5674c62d705ccd9f962b08b34dbd4057ca8/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJYW5CbkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--a3b53ba1a0f83efef18f6e75a8d4ce784384bee2/JEI-22-085.jpg)
The authors found that SARIMAX-GARCH is more accurate than SARIMAX for load forecasting with respect to energy consumption.
Read More...An analysis of the feasibility of SARIMAX-GARCH through load forecasting
The authors found that SARIMAX-GARCH is more accurate than SARIMAX for load forecasting with respect to energy consumption.
Read More...The influence of purpose-of-use on information overload in online social networking
Here, seeking to understand the effects of social media in relation to social media fatigue and/or overload in recent years, the authors used various linear models to assess the results of a survey of 27 respondents. Their results showed that increased duration of use of social media did not necessarily lead to fatigue, suggesting that quality may be more important than quantity. They also considered the purpose of an individual's social media usage as well as their engagement behavior during the COVID-19 pandemic.
Read More...Friend or foe: Using DNA barcoding to identify arthropods found at home
Here the authors used morphological characters and DNA barcoding to identify arthropods found within a residential house. With this method they identified their species and compared them against pests lists provided by the US government. They found that none of their identified species were considered to be pests providing evidence against the misconception that arthropods found at home are harmful to humans. They suggest that these methods could be used at larger scales to better understand and aid in mapping ecosystems.
Read More...Similarity Graph-Based Semi-supervised Methods for Multiclass Data Classification
The purpose of the study was to determine whether graph-based machine learning techniques, which have increased prevalence in the last few years, can accurately classify data into one of many clusters, while requiring less labeled training data and parameter tuning as opposed to traditional machine learning algorithms. The results determined that the accuracy of graph-based and traditional classification algorithms depends directly upon the number of features of each dataset, the number of classes in each dataset, and the amount of labeled training data used.
Read More...Presence of Vegetation in Relation to Slope in Yosemite Valley, California
This study examined the relationship between the slope of a terrain and vegetation, measured by the normalized difference vegetation index (NDVI). It was hypothesized that lower slope ranges would be more supportive of vegetation growth than higher slope ranges. Analysis showed that no slope (even as extreme as 85–90°) prohibits the growth of vegetation completely; even the steepest slopes examined contain plant life. Knowing that steep slopes can still support plant life, agriculturalists can begin to explore and start planting additional crops and plants at these extreme slopes.
Read More...Bacterial Load Consistency Among Three Independent Water Distribution Systems
Clean drinking water is an essential component to maintaining public health. The authors of this study tested the bacterial load of water from three different disinfection and filtration systems in order to determine which system might be superior.
Read More...The effects of algaecides on Spirulina major and non-target organism Daphnia magna
Algal blooms pose a threat to ecosystems, but the methods used to combat these blooms might harm more than just the algae. Halepete, Graham, and Lowe-Schmahl demonstrate negative effects of anti-algae treatments on a cyanobacterium (Spirulina major), and the water fleas (Daphnia magna) that live alongside these cyanobacteria.
Read More...PCR technology for screening genetically modified soybeans
In order to determine whether unmarked soybeans in the market were genetically modified crops, the authors developed a polymerase chain reaction (PCR) screen for DNA lectin.
Read More...Slowing the Mold Growth on Stored Corn: The Effects of Vinegar, Baker’s Yeast, and Yogurt on Corn Weight Loss
Chemical preservatives are often used to reduce grain spoilage due to mold, but can have harmful heath and environmental effects. In this study, the authors tested three low toxic compounds for their effects on mold growth on corn kernels and found that all three were successful at slowing growth.
Read More...Cardiovascular Disease Prediction Using Supervised Ensemble Machine Learning and Shapley Values
The authors test the effectiveness of machine learning to predict onset of cardiovascular disease.
Read More...Search articles by title, author name, or tags