Sustainable supply chain management and green technologies: a bibliometric review of literature
To attain ecological sustainability and transition to sustainable supply chain management
(SSCM), effective technological innovation (TI) and solid waste management (SWM), as …
(SSCM), effective technological innovation (TI) and solid waste management (SWM), as …
[HTML][HTML] Deep neural networks in the cloud: Review, applications, challenges and research directions
Deep neural networks (DNNs) are currently being deployed as machine learning technology
in a wide range of important real-world applications. DNNs consist of a huge number of …
in a wide range of important real-world applications. DNNs consist of a huge number of …
Supply chain viability in the context of COVID-19 pandemic in small and medium-sized enterprises: implications for sustainable development goals
Purpose The recent outbreak of the coronavirus disease 2019 (COVID-19) pandemic has
severely disrupted the operations of global supply chains (SCs) providing an opportunity for …
severely disrupted the operations of global supply chains (SCs) providing an opportunity for …
Machine learning models for evaluating the benefits of business intelligence systems
Due to the uncertainty of the market and the intensity of rivalry, business owners and
managers are often compelled to experiment with a wide variety of strategies for enhancing …
managers are often compelled to experiment with a wide variety of strategies for enhancing …
[PDF][PDF] The role of machine learning in transforming business intelligence
JP Bharadiya - International Journal of Computing …, 2023 - computersciencejournals.com
Abstract Machine Learning (ML) has emerged as a transformative force in the field of
Business Intelligence (BI), revolutionizing the way organizations extract insights from vast …
Business Intelligence (BI), revolutionizing the way organizations extract insights from vast …
The derived demand for advertising expenses and implications on sustainability: a comparative study using deep learning and traditional machine learning methods
In recent years, machine learning models based on big data have been introduced into
marketing in order to transform customer data into meaningful insights and to make strategic …
marketing in order to transform customer data into meaningful insights and to make strategic …
[BOOK][B] Artificial intelligence for fashion: How AI is revolutionizing the fashion industry
L Luce - 2018 - books.google.com
Learn how Artificial Intelligence (AI) is being applied in the fashion industry. With an
application focused approach, this book provides real-world examples, breaks down …
application focused approach, this book provides real-world examples, breaks down …
[PDF][PDF] Prediction of cloud ranking in a hyperconverged cloud ecosystem using machine learning
Cloud computing is becoming popular technology due to its functional properties and variety
of customer-oriented services over the Internet. The design of reliable and high-quality cloud …
of customer-oriented services over the Internet. The design of reliable and high-quality cloud …
Streamlining Inventory Forecasting with Weighted Moving Average Method at Parta Trading Companies
K Suryadana, IBG Sarasvananda - Jurnal Galaksi, 2024 - ejournal.pancawidya.or.id
The process that is currently running at Parta trading companies, along with its development,
problems that often occur in the warehouse section arise, namely the accumulation of stock …
problems that often occur in the warehouse section arise, namely the accumulation of stock …
Addressing Seasonality and Trend Detection in Predictive Sales Forecasting: A Machine Learning Perspective
MDR Hasan - Journal of Business and Management Studies, 2024 - al-kindipublisher.com
Sales prediction plays a paramount role in the decision-making process for organizations
across various industries. Nonetheless, accurately predicting sales is challenging because …
across various industries. Nonetheless, accurately predicting sales is challenging because …