Tag: Applied AI Modeling

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Subbu Pazhani 0
Simulated Annealing (SA) Metaheuristic in SAS Optimization

Authors: Subbu Pazhani and Rob Pratt Large-scale real-world optimization problems with advanced business rules are often difficult to solve with standalone traditional optimization algorithms. Metaheuristic algorithms often complement these traditional optimization techniques. These are a class of powerful and flexible algorithms designed to address complex optimization problems, which traditional methods

Advanced Analytics | Artificial Intelligence
Jay King 0
Fighting fraud, waste, and abuse in health care: How SAS is democratizing AI for payment integrity

Health care fraud, waste, and abuse (FWA) cost the industry billions each year—but what if we could outsmart it? Enter SAS Payment Integrity for Health Care: Detect and Prevent, a groundbreaking solution that is redefining how we can tackle FWA. As the first to offer models-as-a-service in a Commercial Off-The-Shelf

Advanced Analytics
Bahar Biller 0
Optimize spare parts inventory under uncertainty with SAS: A simulation-based approach

Authors: Bahar Biller, Jagdishwar Mankala, and Jinxin Yi Managing spare parts inventory is a critical aspect of asset performance management, especially in industries where equipment downtime is costly. This post, based on a real-world project with a major aircraft manufacturer, explores how to optimize spare parts inventory under uncertainty. We

Artificial Intelligence | Innovation
Glynn Newby 0
Ready-made AI models: The next industrial revolution in manufacturing

The manufacturing industry is at a fascinating crossroads, brimming with potential for groundbreaking advancements. We find ourselves in an era of unprecedented data surges, intricate supply chain networks and a relentless drive to innovate. This dynamic environment, now known as Industry 4.0 – 5.0, has cultivated a fertile ground where

Advanced Analytics | Artificial Intelligence | Innovation
Lindsey Coombs 0
Ready-made AI models: Faster access to AI at lower cost and risk

Fast-paced technology like AI can have barriers to entry. Whether infrastructure, data limitations, talent gaps or complying with rapidly changing regulations. Organizations from health care to manufacturing and the public sector are often stymied by these obstacles that can slow AI adoption and use. Ready-made AI models can bypass the

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