Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- LSTM (2)
- Time Series (2)
- CNN (1)
- Convolutional (1)
- Deep Learning (1)
-
- Demand Forecasting (1)
- Detect (1)
- Detection (1)
- Dump (1)
- Ensemble Model (1)
- Forecasting (1)
- Fraud (1)
- Fraudulent (1)
- Market (1)
- Markets (1)
- Multivariate Analysis (1)
- NFT (1)
- NFTs (1)
- Neural network (1)
- Non-fungible (1)
- Nonfungible (1)
- Pattern (1)
- Patterns (1)
- Pump (1)
- Supply Chain (1)
- Time series classification (1)
- Token (1)
- Tokens (1)
- Transaction (1)
- Transactions (1)
Articles 1 - 4 of 4
Full-Text Articles in Business
Fraud Pattern Detection For Nft Markets, Andrew Leppla, Jorge Olmos, Jaideep Lamba
Fraud Pattern Detection For Nft Markets, Andrew Leppla, Jorge Olmos, Jaideep Lamba
SMU Data Science Review
Non-Fungible Tokens (NFTs) enable ownership and transfer of digital assets using blockchain technology. As a relatively new financial asset class, NFTs lack robust oversight and regulations. These conditions create an environment that is susceptible to fraudulent activity and market manipulation schemes. This study examines the buyer-seller network transactional data from some of the most popular NFT marketplaces (e.g., AtomicHub, OpenSea) to identify and predict fraudulent activity. To accomplish this goal multiple features such as price, volume, and network metrics were extracted from NFT transactional data. These were fed into a Multiple-Scale Convolutional Neural Network that predicts suspected fraudulent activity based …
Demand Forecasting In Wholesale Alcohol Distribution: An Ensemble Approach, Tanvi Arora, Rajat Chandna, Stacy Conant, Bivin Sadler, Robert Slater
Demand Forecasting In Wholesale Alcohol Distribution: An Ensemble Approach, Tanvi Arora, Rajat Chandna, Stacy Conant, Bivin Sadler, Robert Slater
SMU Data Science Review
In this paper, historical data from a wholesale alcoholic beverage distributor was used to forecast sales demand. Demand forecasting is a vital part of the sale and distribution of many goods. Accurate forecasting can be used to optimize inventory, improve cash ow, and enhance customer service. However, demand forecasting is a challenging task due to the many unknowns that can impact sales, such as the weather and the state of the economy. While many studies focus effort on modeling consumer demand and endpoint retail sales, this study focused on demand forecasting from the distributor perspective. An ensemble approach was applied …
Demand Forecasting For Alcoholic Beverage Distribution, Lei Jiang, Kristen M. Rollins, Meredith Ludlow, Bivin Sadler
Demand Forecasting For Alcoholic Beverage Distribution, Lei Jiang, Kristen M. Rollins, Meredith Ludlow, Bivin Sadler
SMU Data Science Review
Forecasting demand is one of the biggest challenges in any business, and the ability to make such predictions is an invaluable resource to a company. While difficult, predicting demand for products should be increasingly accessible due to the volume of data collected in businesses and the continuing advancements of machine learning models. This paper presents forecasting models for two vodka products for an alcoholic beverage distributing company located in the United States with the purpose of improving the company’s ability to forecast demand for those products. The results contain exploratory data analysis to determine the most important variables impacting demand, …
Demand Forecasting: An Open-Source Approach, Murtada Shubbar, Jared Smith
Demand Forecasting: An Open-Source Approach, Murtada Shubbar, Jared Smith
SMU Data Science Review
In this paper, we compare demand forecasting methods used by the supply chain department at Bilports to open-source forecasting methods. The design and implementation of the open-source forecasting system also attempts to use several external datasets such as consumer sentiment, housing permit starts, and weather to improve prediction quality. Additionally, the performance of the forecast is evaluated by the reduction of shipment lead times from China, the company’s primary vendor. The objective of our paper is to improve Bilports’s forecasting capabilities. The primary motivation of this paper is to increase forecasting accuracy and identify the weaknesses of the methods used …