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Articles 1 - 7 of 7
Full-Text Articles in Computer Sciences
Crime Prediction Using Machine Learning: The Case Of The City Of Little Rock, Zurab Sabakhtarishvili, Sijan Panday, Clayton Jensen
Crime Prediction Using Machine Learning: The Case Of The City Of Little Rock, Zurab Sabakhtarishvili, Sijan Panday, Clayton Jensen
ATU Research Symposium
Crime is a severe problem in the city of Little Rock, Arkansas. In this study, we aim to develop a machine-learning model to predict criminal activities in the city and provide insights into crime patterns. We will analyze publicly available crime datasets from Little Rock Police Department from January 2017 to March 2023 to identify trends and patterns in crime occurrence. We used data cleaning and exploratory data analysis techniques, such as figured-based visualizations, to prepare the data for machine learning. We will employ the Neural Prophet, a time-series machine learning model, to predict daily crime counts. The model will …
Nviz: Unraveling Neural Networks Through Visualization, Kevin Hoffman
Nviz: Unraveling Neural Networks Through Visualization, Kevin Hoffman
Mathematics and Computer Science Presentations
The growing utility of artificial intelligence (AI) is attributed to the development of neural networks. These networks are a class of models that make predictions based on previously observed data. While the inferential power of neural networks is great, the ability to explain their results is difficult because the underlying model is automatically generated. The AI community commonly refers to neural networks as black boxes because the patterns they learn from the data are not easily understood. This project aims to improve the visibility of patterns that neural networks identify in data. Through an interactive web application, NVIZ affords the …
R Text Analysis For Adam Smith Cie Selected Works, Charlotte Grahame
R Text Analysis For Adam Smith Cie Selected Works, Charlotte Grahame
Mathematics and Computer Science Presentations
Text mining and text analysis is a way of understanding text documents using r coding that is more frequently used for numbered data. It helps with understanding portions of the text and drawing conclusions from there. This research looks specifically at the Adam Smith required documents that are used in the CIE course designated for freshmen. It looks at sentiments of the documents, including word sentiment, sentence sentiment, page and overall document sentiment as well. It provides visuals of word clouds to portray word frequency, tf-idf (which is explained in the presentation) and bigram analysis.
Cie Text Analysis: Narrative Of The Life Of Frederick Douglass, The Declaration Of Independence, And The Declaration Of Sentiments, Arianna Knipe
Cie Text Analysis: Narrative Of The Life Of Frederick Douglass, The Declaration Of Independence, And The Declaration Of Sentiments, Arianna Knipe
Mathematics and Computer Science Presentations
Our STAT-451 class has worked with analyzing the words from CIE texts and assigning them to a sentiment or feeling and comparing them with one another using RStudio. This project analyzes texts from three sources: The Narrative of the Life of Frederick Douglass, The Declaration of Independence and the Declaration of Sentiments.
Temporal Tensor Factorization For Multidimensional Forecasting, Jackson Cates, Karissa Scipke, Randy Hoover, Kyle Caudle
Temporal Tensor Factorization For Multidimensional Forecasting, Jackson Cates, Karissa Scipke, Randy Hoover, Kyle Caudle
SDSU Data Science Symposium
In the era of big data, there is a need for forecasting high-dimensional time series that might be incomplete, sparse, and/or nonstationary. The current research aims to solve this problem for two-dimensional data through a combination of temporal matrix factorization (TMF) and low-rank tensor factorization. From this method, we propose an expansion of TMF to two-dimensional data: temporal tensor factorization (TTF). The current research aims to interpolate missing values via low-rank tensor factorization, which produces a latent space of the original multilinear time series. We then can perform forecasting in the latent space. We present experimental results of the proposed …
From Computer Curriculum That Works For The Use Of Computer Intellignece Computer Science, Malachi B. Bacchus
From Computer Curriculum That Works For The Use Of Computer Intellignece Computer Science, Malachi B. Bacchus
Publications and Research
Computer interconnection can link different networks by using electrical artificial flow ways that can travel through different connections. these are called data network which travels through different sectors of the network simulation of service computer network using artificial intelligence to enhanced further understanding the computations, I've also demonstrated knowing by using the network to get better understanding of how ethical computing can be learned through universities and collegiate that can help established knowledge and healthy computer information. The main tools for the research are using data networking, ethical learning and translation towards different computer systems.
Analyze And Examine Wildfire Events In California, Aleena Hoodith, Sakim Zaman, Safoan Hossain, Jiehao Huang
Analyze And Examine Wildfire Events In California, Aleena Hoodith, Sakim Zaman, Safoan Hossain, Jiehao Huang
Publications and Research
•A wildfire is an unplanned, unwanted, uncontrolled fire in an area of combustible vegetation starting in rural areas and urban areas. •Recent studies have shown that the effect of anthropogenic climate change has fueled the wildfire events, leading to an increase in the annual burned areas and number of events. •California is one of the places having the most deadliest and destructive wildfire seasons. With the global warming effect of 1°C since 1850, the 20 largest wildfires events that have occurred in California, 8 of them were in 2017. (Center For Climate And Energy Solutions) •Climate change is primarily caused …